Presumption of Creditworthiness

Nakita Q. Cuttino* December, 2025

Creditworthiness, or the likelihood that one will repay one’s debts, is typically signaled through a three-digit number known as a credit score. Yet, over thirty-two million adult-aged consumers lack adequate consumer credit reports and therefore do not have a traditional credit score. As a result of being unscored, these consumers are generally presumed uncreditworthy and foreclosed from mainstream credit markets. Unscored consumers are often relegated to extractive, fringe credit markets that neither require nor build credit scores. More insidiously, however, a growing number of non-credit contexts, including rental housing, utility services, and employment markets, look to creditworthiness to determine eligibility and price. Thus, unscored consumers face barriers beyond credit markets in ways that can marginalize them socially and entrench financial hardships. Innovations in the credit markets have aimed to serve unscored consumers by expanding scoring models to include nontraditional data metrics, such as alternative underwriting, or evading credit scores altogether, such as through earned wage access (EWA) programs. Such innovations have indeed had some success reducing the number of unscored consumers or the negative impacts related thereto, but they have also imposed on unscored consumers disproportionate costs while failing to offer them a comprehensive escape from the scarlet letter awarded by being unscored.

The plight of the unscored consumer rests upon an as-yet-resolved conundrum of our credit scoring system: To build a fair credit score, a consumer first needs access to fair credit, which in turn requires a fair credit score. This classic chicken-and-egg dilemma is based on the maxim that past behavior is predictive of future conduct. Yet, for unscored consumers who lack credit history, the maxim is unduly distorted to treat those with no past behavior as those with poor past behavior. Specifically, the system creates a form of adverse selection that harms unscored consumers and market providers alike. This Article argues that eliminating the marginalized “unscored” consumer status with a presumption of creditworthiness would better achieve the efficiency and equity goals undergirding the credit scoring system. Alternative approaches abroad may prove instructive, though they reflect distinct policy and cultural priorities, since they avoid the marginalized “unscored” status. By surfacing the sociopolitical nature of credit scoring, this Article creates space to reimagine the U.S. system in light of its market failures.

Introduction

American creditworthiness was not determined by wealth or privilege; it was embedded in the individual’s sense of moral obligation and responsibility.

—Josh Lauer¹

If cash is king, then a credit score is kingmaker. Credit scores gatekeep consumer access to credit that is essential to pay for day-to-day goods and services, make large home or vehicle purchases, or invest in businesses.² They influence the price of credit, which in turn operates as a premium on the homes, vehicles, and other essentials financed with it.³ They reach beyond the credit markets, affecting direct prices set for utility services and auto insurance policies, and influencing whether a person gets approved for an apartment or offered a job.⁴ And with new dating apps set to screen singles based on credit scores, they may even affect one’s ability to find love.⁵ In sum, credit scores can affect a consumer’s cost of living, income levels, savings rates, and social networks. Yet, despite their consequence, credit scores are not available to all consumers.

Credit scores are numerical outputs of statistical models that seek to predict whether a consumer is creditworthy, or likely to repay their debts.⁶ This default risk is critical for lenders to assess in order to limit loan losses and maximize profits. FICO created the most commonly used statistical models,⁷ which are deployed by the three major U.S. credit rating agencies: Experian, TransUnion, and Equifax.⁸ These agencies maintain robust records on more than 200 million Americans, traditionally tracking consumer credit histories such as credit account openings and closures, loan balances, repayment habits, court judgments, and bankruptcies.⁹ The agencies input these credit reports into the FICO models to create FICO credit scores. This seemingly objective approach to assessing creditworthiness was adopted in the 1970s in response to concerns that prior subjective assessments conducted by biased humans resulted in inconsistent and discriminatory credit determinations.¹⁰ By turning this tedious process over to quicker and more precise computer models, the credit markets promised to be more efficient and equitable.

The shift to the FICO score, however, highlighted (if not created) a conundrum that adversely affects many adult-aged consumers. Due to the backward-looking nature of credit scoring models, consumers must have a credit history to generate a credit score.¹¹ Moreover, a longer credit history, and the type of credit history, can improve a consumer’s credit score. Yet, to build a credit history, consumers must have access to credit that, in turn, typically requires a credit score.¹² Put simply, today’s credit scoring system creates a classic chicken-and-egg conundrum—to build a fair credit score, a consumer first needs access to fair credit, which requires a fair credit score. So, which does a consumer acquire first? Many consumers first acquire access to fair credit while attending a college or university,¹³ by paying a deposit equal to the amount of the credit line to be received,¹⁴ or by being added to an established credit account managed by a relative.¹⁵ With such credit access, they can then build credit histories that eventually generate credit scores. Effectively, the privileges of education, excess money, and social networks afford some consumers a presumption of creditworthiness as an on-ramp to the mainstream credit markets. Other consumers are not so lucky.

Over thirty-two million consumers are characterized as “unscored.”¹⁶ They either have no credit history, not enough history, or too old of a history to generate a credit score and therefore cannot prove their creditworthiness under the traditional credit scoring system. These consumers include those that transact primarily in cash, have only recently reached the age of maturity and have yet to enter credit markets, or are recent immigrants with no credit history in the United States.¹⁷ Without the privileges of education, excess money, or social networks, these unscored consumers are unknown risks, traditionally treated by lenders as akin to consumers who are poor credit risks.¹⁸ As a result, unscored consumers are often unable to secure credit at mainstream costs—relegated to fringe credit markets with onerous terms, foreclosed from the housing market, and screened out of living in desirable communities.¹⁹ This economic marginalization disproportionately effects minority and low-income consumers. Indeed, more than a quarter of Black and Latinx adults are unscored, and nearly half of consumers in low-income neighborhoods are unscored.²⁰ These market disparities contribute to consumer advocate concerns that the credit scoring system is inherently biased and exacerbates economic inequality.²¹

Recent studies and market efforts show that a not insignificant portion of unscored consumers are very likely to repay their debts.²² Thus, equating unscored consumers to consumers with poor credit does more than just marginalize the unscored—it falsely signals negative creditworthiness that causes market providers to overcharge unscored consumers or forego opportunities to serve them altogether. And when unduly subject to more onerous credit terms, unscored consumers are at a greater risk of defaulting because of the credit product’s design.²³ Unscored consumers are set up to fail, and the false signal becomes a self-fulfilling prophecy. As such, the current credit scoring system’s inability to identify creditworthy unscored consumers is both inequitable and inefficient. Together with concerns regarding unchecked errors in consumer reports²⁴ and data breaches that pose privacy risks,²⁵ these shortcomings in the credit scoring system have led to congressional hearings,²⁶ legislative proposals,²⁷ presidential campaign promises,²⁸ and regulatory rulemaking²⁹ to advance efforts to reform the system. Additionally, consumer advocates have called for a range of progressive changes to credit scoring, including restrictions on the use of credit scores in nonborrowing contexts³⁰ and the creation of a public credit scoring system.³¹

For its part, the market has proffered innovations that aim to either enhance the traditional credit scoring system or evade it completely. Enhancement innovations seek to add nontraditional data points to individualized creditworthiness assessments conducted by lenders or to credit reports used to build credit scores.³² For example, alternative data models assess creditworthiness based on oft-innumerable factors, including rent repayment history, how one manages their bank account, academic affiliations, standardized test scores, or even social networks.³³ Evasion innovations seek to issue cash advances without relying on credit scores.³⁴ For example, earned-wage-access (EWA) programs³⁵ and buy-now-pay-later (BNPL) products rely on pre-authorized automatic withdrawals from a payroll account, bank account, or credit card to repay cash advances or point-of-sale payments for goods and services.³⁶ A recent June 2025 study suggests that at least some of these innovations have made inroads to reduce the number of unscored consumers.³⁷

Notwithstanding, enhancement and evasion innovations provide only limited, symptomatic relief for the credit score conundrum, and such relief is outweighed by their significant costs. For example, alternative data in underwriting allows for more narrowly tailored creditworthiness evaluations that have been shown to increase access to credit for some unscored consumers.³⁸ Yet, the use of such data heightens disparate risks of privacy violations and racial discrimination while also penalizing cost-saving strategies—like living at home with parents—despite being the fiscally responsible thing to do.³⁹ Similarly, although EWA programs and BNPL products enable cash advances for some unscored consumers, they do so on terms that rival onerous terms in the fringe credit market, and they to date do not aid consumers in building credit scores.⁴⁰ In many ways, market innovations aimed at remedying the credit scoring system’s shortcomings maintain the status quo or, at worst, exacerbate the credit score conundrum with heightened risks.

This Article contends that these market innovations fail to address the root cause of the conundrum that creates unscored consumers. It seeks to answer a fundamental question: Must consumers prove their creditworthiness as a prerequisite to access the marketplace? The U.S. market accepts as a foregone conclusion that consumers bear the burden to prove their creditworthiness through the responsible use of credit. It is based on a maxim that past behavior is predictive of future behavior. However, the maxim has limited applications and does not reasonably support treating no past behavior akin to poor past behavior—yet, amid a form of adverse selection, that is the unscored consumer’s reality. In the absence of privileged access points that effectively presume creditworthiness, some consumers find themselves in a metaphorical credit purgatory with no reasonable on-ramp to the mainstream credit market. Other consumers find themselves enmeshed with credit terms that all but ensure they end up with poor credit scores.

Eliminating the marginalized status that is “unscored consumers” by presuming their creditworthiness would better achieve the efficiency and equity goals undergirding the credit scoring system.⁴¹ Such a presumption would place consumers on similar footing in accessing first-time credit while still maximizing the productive use of credit in the broader marketplace. It would also create equitable access to, and broaden the customer base in, noncredit markets that rely on creditworthiness for eligibility and pricing. Developed credit markets in other countries demonstrate that measuring creditworthiness is not a science but a policy choice. And given the current system’s market failures, this Article highlights that the United States could benefit from making a different choice.⁴²

Part I gives an overview of how credit scoring has become a gatekeeper to essential credit services. It details consumer dependence on credit to sustain every aspect of their daily life, including daily expenses, home and vehicle purchases, and entrepreneurial ambitions. This consumer demand, however, must be balanced against lenders’ basic business needs to mitigate losses and optimize profits. Credit markets partially achieve this by effectively assessing which consumers would be the most likely to repay their debts—that is, the most creditworthy. Part I traces the evolution of creditworthiness determinations into the modern credit scoring system and the inadvertent consequence that is unscored consumers.

Part II details market efforts to broaden credit access for unscored consumers, which may be categorized by two dichotomous objectives. In the first category, market efforts seek to expand credit scoring by considering alternative data or selling credit account histories. In doing so, unscored consumers would obtain credit reports that could generate a credit score or would otherwise obtain credit at mainstream rates that could be used to build their credit score. In the second category, market efforts seek to evade credit scoring akin to fringe credit markets but on terms that are purportedly more favorable. As a result, being unscored would not disadvantage consumers because the fringe market, though separate, would be more equal. However, these efforts impose undue costs on unscored consumers with benefits too limited to justify relying exclusively on the market to redress the frictions unscored consumers face.

Part III sets forth the thesis of this Article: A presumption of creditworthiness at the outset would be the most efficient and equitable solution to eliminate the “unscored” consumer status and, consequently, resolve the economic and social harms caused by such status. It explains how the root cause of the credit score conundrum is a consumer burden to prove creditworthiness upon entering the credit market, which need not be the case. The intuitive appeal of such a burden is misguided with respect to unscored consumers who lack a reliable past behavior pattern to justify their market treatment. And in the absence of such evidence, the current system produces a form of adverse selection that remains unresolved by recent market efforts. Part III provides a rare look into how several other countries evaluate and define creditworthiness, illustrating the different available policy choices. It then concludes by detailing the efficiency and equity benefits that credit markets would accrue with a presumption of creditworthiness while weighing the merits of potential counter positions.

Part IV proposes three ways to move the market towards a presumption of creditworthiness. In the credit context, there should be a “special purpose credit program” (SPCP) established pursuant to rarely used exemptions under federal antidiscrimination laws, under which lenders provide first-time credit to unscored consumers on terms akin to those offered to consumers with “very good” or “excellent” credit. Alternatively, policymakers should expand antidiscrimination legislation to prohibit credit rejections based on a consumer’s unscored status. To be sure, these efforts are likely to face challenges considering current efforts to dismantle long-standing antidiscrimination protections. Arguably, though, the SPCP’s race-neutral implementation or legislative expansion may allow either policy to survive political scrutiny. Finally, there should be creditworthy presumption laws enacted to ban the use of credit scores in nonlending contexts, including employment decisions, rental housing applications, and insurance policies.

I. The Credit Score Conundrum

Credit has proven to be an essential part of everyday life, but access to it is not guaranteed. Creditors purportedly aim to allocate credit efficiently—that is, in a way that mitigates their losses and optimizes their profits. However, their methods of identifying creditworthy consumers have not always served this goal and have often introduced equity concerns. The U.S. credit scoring system emerged to facilitate credit decisions in both an efficient and equitable manner. Yet, the system’s design has created a class of unscored consumers that face significant barriers to accessing credit and noncredit markets alike. This Part outlines the consumer credit market and the credit scoring system.

A. Essential Credit

Credit, or money that is borrowed for repayment in the future, is indispensable for most U.S. households. It is necessary for large but common purchases like homes and vehicles. Take, for example, a “starter” home, which costs the median household more than three years’ worth of annual income.⁴³ The housing market would be inaccessible without the ability to spread the purchase payment over twenty- to thirty-five-year periods. Indeed, nearly 97% of first-time home buyers use mortgage loans to finance their purchases.⁴⁴ Similarly, the average cost of a new car is nearly two-thirds of the median household’s annual salary,⁴⁵ and thus, cannot be purchased outright by most consumers. As such, nearly 80% of new car buyers rely on credit. ⁴⁶ Though cheaper, used cars have an average cost equal to roughly 30% of the median household’s annual salary, ⁴⁷ resulting in nearly 40% of such purchases being financed with credit.⁴⁸ What’s more, nearly half of households face monthly expenses that exceed their after-tax income.⁴⁹ Thus, credit often proves necessary even for smaller, routine purchases. Unsurprisingly, nearly half of U.S. households rely on personal credit cards to cover daily expenses.⁵⁰

Beyond facilitating mere financial subsistence, credit is essential for wealth accumulation. It allows consumers to leverage future earnings for present-day investments that build equity and generate income. The most common example is the home mortgage. With the help of credit markets, homeowners can save income via mortgage amortization mechanisms and increase the value of their assets as their home appreciates over time, which they can then leverage for additional investments.⁵¹ Homeownership also provides tax savings,⁵² income subsidies through home sharing ventures,⁵³ and access to low-cost credit using the home’s equity.⁵⁴ Another example is the small business loan.⁵⁵ Self-employed families have a median net worth that is four times higher than that of wage-earning families.⁵⁶ And although the self-employed tend to be wealthier than workers even before launching small businesses,⁵⁷ capital’s disproportionate growth rate and tax advantages over income contribute to the wealth-compounding effects of small business ownership.⁵⁸ But to start a small business, over 25% of entrepreneurs rely on small business loans or personal credit cards.⁵⁹ In sum, credit fuels economic activity in the United States.⁶⁰

Still, consumer access to credit is not guaranteed. Since credit is repaid at a future date, lenders who extend credit risk financial losses if borrowers fail to repay as agreed.⁶¹ Excessive losses on loan portfolios can lead to a lender’s failure or costly regulatory intervention.⁶² Therefore, the borrower’s creditworthiness, or their likelihood of repayment, is critical to credit access—and the viability of credit markets in general. Lenders typically assess creditworthiness by evaluating the so-called “five Cs”: conditions, capacity, collateral, capital, and character.⁶³ Conditions refer to the state of the market, including the state of the overall economy, the demand and pricing in credit markets, and, for business loans, the relevant industry trends.⁶⁴ Lenders also consider whether a would-be borrower has assets on hand for a down payment (capital), assets to secure the loan and repossess in case of default (collateral), or sufficient future earnings to cover their expenses (capacity).⁶⁵ These factors are relatively objective and easy to assess, thus raising few concerns for observers.

However, the final factor—character—refers to the general trustworthiness and credibility of a would-be borrower, which is not as readily quantifiable. It highlights that just because a person can pay a debt does not mean he will.⁶⁶ And for many creditors, it is the most consequential factor. Indeed, John Pierpont Morgan once famously quipped that a borrower’s character is something money cannot buy and “a man [he did] not trust could not get money from [him] on all the bonds in Christendom.”⁶⁷ But identifying creditworthy character in an equitable, objective, and economically sound manner has been elusive since the nineteenth century.

B. Scoring Character

1. Subjective Creditworthiness

Through most of the nineteenth century, since creditors⁶⁸ and borrowers were neighbors, creditworthy character was commonly assessed based on a creditor’s first-hand insights, local rumor, and innuendo.⁶⁹ By the early twentieth century, amid increasing industrialization and urbanization, consumer credit reporting agencies emerged to make local reputations accessible to interstate creditors.⁷⁰ These agencies collected data on consumer debts and habits that spoke to their moral character, such as drinking or gambling history.⁷¹ Even incredibly personal hardships, including having a stillborn child or premature birth, would show up in credit reports.⁷² Agencies shared this information with credit managers at retail stores and installment lenders who evaluated it to determine creditworthiness. Credit managers balanced credit reports, referrals, and other third-party sources with their own intuitions about potential customers.⁷³ In particular, they highly valued in-person interviews to subjectively assess creditworthiness, based, in part, on a consumer’s appearance, mannerisms, race, gender, and marital status.⁷⁴ By many accounts, this subjective, individualized creditworthiness evaluation was effective. Scholars at the time speculated that the remarkably low losses on consumer credit were attributable to the effectiveness of credit managers’ systems.⁷⁵

A rapid explosion of consumer credit, however, quickly revealed two frictions with these then-typical credit reports and creditworthiness evaluations. First, detailed credit reports and individualized evaluations became increasingly inefficient. Credit reporting was paper-intensive, with a costly footprint for storing ever-increasing details about a growing number of consumers. Sharing paper files with retailers also had physical limits since a file could only be in one place at a time, which occasionally slowed credit determinations.⁷⁶ Credit management, for its part, was a labor- and time-intensive endeavor. As the credit market expanded, individual interviews and thorough credit report analyses for each credit applicant became impracticable.⁷⁷ In response, credit managers first sought truncated credit reports that summarized only negative consumer data, but these reports risked defamation suits.⁷⁸ Meanwhile, reliance on the specialized art of credit manager “intuition” led to many credit departments being understaffed.⁷⁹ There were few skilled managers and fewer resources to train new staff to keep pace with ballooning demand for consumer credit.⁸⁰

Second, creditworthiness evaluations were unjustifiably inequitable. Relying on their intuitions, credit managers often defined creditworthiness through biased lenses.⁸¹ For example, credit managers denied Black military veterans credit regardless of whether objective indicators signaled their capacity to repay debts.⁸² Without justification, as one lender admitted, “it [was] almost impossible for a [Black] man to get a loan.”⁸³ Managers routinely recorded racial markers such as an applicant’s “color” in underwriting documents because of the presumption that racial minorities were inherently uncreditworthy.⁸⁴

Gender also explicitly shaped creditworthiness determinations due to the assumption that women could not manage their finances. Single and divorced women were denied credit or required to have a male co-signer.⁸⁵ And married women were compelled to apply for credit under their husband’s name, since they would either become dependent on their husband if they had a child⁸⁶ or—if divorced, separated, or widowed—they would be automatically deemed a “bad credit risk . . . without male support, financial or otherwise.”⁸⁷ By the 1960s, such long-standing discriminatory practices against people of color and women faced increasing scrutiny as growing consumer dependency on credit markets revealed their indefensibly detrimental welfare effects.⁸⁸

2. Statistical Creditworthiness

Market participants and policymakers promised two solutions to these inefficiencies and inequities: computers and statistical models. Computerized systems alleviated some inefficiencies by reducing costs related to paper files, reducing times for sharing and updating files, and enabling simultaneous access to records.⁸⁹ These efficiencies, however, came with a key tradeoff. Computer databases designed for formulaic inputs did not readily accommodate the detailed, personal narratives that were included in paper-based consumer records.⁹⁰ Consequently, many credit reporting agencies shifted to remove nonfinancial data from computerized reports for easier coding.⁹¹ Computerization also brought about industry consolidation that resulted in the “big three” credit reporting agencies—Equifax, Experian, and TransUnion.⁹² These firms synthesized consumer data from a variety of creditors into uniform tradelines,⁹³ thereby standardizing consumer reports⁹⁴ used by creditors and other third parties nationally.

Computers also facilitated the use of statistical models, which created efficiencies in creditworthiness evaluations.⁹⁵ Statistical models analyze data inputs and draw out correlations to signal a consumer’s likelihood to repay debts in the form of a “credit score.” Through the 1960s, the first generation of these models was customized for retailers’ and lenders’ in-house use,⁹⁶ reducing labor costs as low-skilled workers could easily track the resulting credit scores.⁹⁷ Specialized credit managers were no longer needed for each evaluation. Interviews and reviews of credit reports could be limited to select applicants, expediting lending decisions.⁹⁸ And the statistical models underlying the credit scores proved to be more accurate than overworked credit managers.⁹⁹ Moreover, the models could more precisely identify those consumers who fell at the bottom end of a creditor’s risk pool to increase loan volumes and maximize profits,¹⁰⁰ ultimately facilitating the emergence of risk-based interest rate adjustments in the 1980s.

Proponents touted credit scores as a solution to then-pervasive bias and discriminatory practices.¹⁰¹ During congressional hearings considering antidiscrimination regulation, market providers assured the legislature that statistical models’ “reliance on numerical values removes the possibility that an individual credit manager will be biased or prejudiced against any individual or segment of applicants.”¹⁰² The consideration by statistical models of characteristics such as age or marital status was one of many factors motivated solely by objective economic reasoning, rather than human bias.¹⁰³ Under statistical models, creditworthiness was no longer an assessment of willingness or ability to pay; rather, it was a tool predictive of paying in a particular context.¹⁰⁴ And because of this, credit scoring was “the only available method that meets the criterion of fairness.”¹⁰⁵ Notwithstanding congressional scrutiny, many policymakers thought credit scores were indispensable for functional credit markets.¹⁰⁶

3. Traditional FICO Score

By the 1980s, in-house statistical models gave way to more generalized models that evaluate broader consumer pools.¹⁰⁷ The data analytics firm FICO—originally Fair, Isaac and Company—powers the most ubiquitous credit score each of the “big three” credit reporting agencies issue—the FICO score.¹⁰⁸ Though a creditor may reference many versions of the FICO score, including industry-specific scores, the most widely referenced version is FICO score 8.¹⁰⁹ This FICO score is based on five categories of financial data: payment history, credit utilization, length of credit, new credit inquiries, and credit mix.

Payment history accounts for up to 35% of the FICO score.¹¹⁰ It consists of timely and delinquent payment records for credit accounts as reported to the agencies, as well as recent bankruptcies.¹¹¹ The more recent, numerous, or sizeable payment delinquencies are, the greater the negative effect on the FICO score. Credit utilization, or the amount of credit used by a consumer, makes up 30% of the FICO score.¹¹² It weighs the total balances on all credit accounts, type and number of accounts carrying balances, and the percentage of available credit remaining across accounts. The more debt outstanding relative to the amount made available, the greater the negative effect on the FICO score. Length of credit history, or the average time credit accounts have been open, accounts for 15% of the FICO score.¹¹³ The longer the credit history (or the older the first credit account), the greater the positive effect on the FICO score.

New credit makes up 10% of the FICO score and reflects recent credit demand.¹¹⁴ These datapoints include the number of new accounts opened within a short period, the number of credit “inquiries” made by potential new lenders within the last twelve months, and the length of time since the last credit account was opened. The more numerous and recent the credit openings and credit inquiries, the greater the negative effect on the FICO score.¹¹⁵ Credit mix accounts for the final 10% of the FICO score and reflects the variety in type of credit products a consumer holds. The greater the mix of revolving credit lines (like credit cards) and installment loans (like mortgages or student loans), the greater the positive effect on the FICO score.¹¹⁶ Scoring models periodically take a snapshot of credit activity in the foregoing categories to output a three-digit FICO score between 300 and 850.¹¹⁷ These scores signal whether consumers are an exceptional, very good, good, fair, or poor credit risk.¹¹⁸

Thus, no matter the age, race, gender, or lifestyle, FICO scoring models would likely signal a consumer as having the highest creditworthy character when they have a long credit history with a mix of credit products that they timely repay and sparingly use or have otherwise significantly paid down. Consequently, the FICO score became the model of efficiency and equity for market participants and policymakers alike.¹¹⁹ Indeed, in the 1990s, the federal government endorsed and institutionalized the FICO score by requiring its consideration in mortgage underwriting.¹²⁰ Unlike in-house scores based on an individual creditor’s narrow customer base, the FICO score reflected the broad, diverse pool of American consumers for a more comprehensive and universally usable creditworthiness assessment.

Since its adoption, the FICO score has become a primary factor in determining credit access. Consumers with poor scores are least likely to be approved for mainstream credit. Consumers with poor scores open just 10% of new credit card accounts and typically require a security deposit for access.¹²¹ Moreover, individuals with poor scores have an even slimmer chance of getting an auto loan¹²² or home mortgage.¹²³ The FICO credit score is also a key factor in setting credit terms, including loan amounts and interest rates. Adjusting terms based on the FICO score helps to optimize lender profits but can be costly to consumers. For example, over the life of a thirty-year, $400,500 mortgage issued on August 21, 2025, a consumer with a fair score will pay over $62,000 more in interest fees than a consumer with an exceptional score.¹²⁴ What’s more, many marketing departments segment and target consumers based on FICO scores—meaning an individual’s credit score determines which incentives and marketing materials, such as discounted credit cards or personal loan mail offerings, they receive.¹²⁵

C. Marginalizing the “Unscored”

However, the credit scoring system’s backward-looking nature creates a conundrum: To obtain a credit score, one needs to have a history of using credit, but to build a history of using credit, one typically needs to have a credit score. The unfortunate consequences of this conundrum are so-called credit invisible and unscorable consumers. Lenders unduly treat these “unscored consumers” like those with low credit scores based on poor credit histories, marginalizing unscored consumers in mainstream credit markets and subjecting them to costly penalties in other facets of their economic lives.

1. Unscored Consumers

According to recent reports, approximately 12.5% of the U.S. adult population, or 32.25 million people, are credit invisible or credit unscorable.¹²⁶ Credit invisibles have zero mainstream credit activity and thus have no credit reports with any of the big three credit reporting agencies.¹²⁷ In contrast, credit unscorables have sparse or outdated credit activity. As a result, they may have credit reports with one or more of the big three credit reporting agencies, but those reports are insufficient to generate a credit score. To qualify for a FICO score, a consumer must have at least one credit account open for six months and reported to a credit bureau within that period.¹²⁸ Consequently, credit rating agencies traditionally have been unable to issue a score for both credit invisibles and credit unscorables—hence, the label “unscored consumers.” Without a credit score, the creditworthiness of an unscored consumer is unknown, which lenders translate into high risk akin to that of a consumer with a poor credit score.¹²⁹

In recent years, inefficiencies and inequities in the treatment of unscored consumers that belie the credit scoring system’s original promise have come into sharp focus. The inefficiency is evidenced in part by so-called “invisible prime” consumers. Invisible prime consumers have, under the traditional credit scoring system, no score or poor scores but are likely to repay their loans at a rate akin to borrowers with “fair” credit scores—and often even higher.¹³⁰ One study of a fintech lender’s loan portfolio found that consumers with poor credit scores had an actual default rate similar to consumers with a 760 or higher credit score.¹³¹ A separate FICO study suggested that nearly half of credit invisibles were sufficiently creditworthy for mainstream lenders with risks akin to credit scores above 620.¹³² Consequently, FICO discouraged lenders from auto-rejecting unscored consumers because doing so disadvantages the consumer and represents a significant opportunity cost for lenders.¹³³ Though useful for predicting defaults on credit cards and mortgages, a credit score is not equally predictive for all types of borrowings. One study found “no relationship between the probability of defaulting [on personal loans] and credit scores below 700.”¹³⁴ However, undergoing a more comprehensive creditworthiness assessment requires a cost-benefit analysis by lenders that harkens back to a pre-credit score era. Would the benefit of accurately identifying a low-credit-risk consumer for greater returns outweigh the cost of a more thorough, individualized assessment? Historically, the market’s answer to this question has been “no.”¹³⁵

The inefficiency of miscalculating the risks posed by unscored consumers causes the credit scoring system to exacerbate inequalities in the credit market, particularly for minorities, low-income individuals, and recent immigrants.¹³⁶ Racial disparities in the likelihood of being unscored are smallest between ages eighteen and nineteen, when all consumers first enter adulthood, though white consumers in this age group have a slight edge on their peers.¹³⁷ However, racial disparities rapidly widen for consumers aged twenty to twenty-four and persist throughout each subsequent age group.¹³⁸ Overall, although 28% of Black adults and 26% of Latinx adults are unscored, only 16% of white adults are similarly situated.¹³⁹ Furthermore, 46% of consumers in low-income neighborhoods are unscored compared to just 9% in high-income neighborhoods.¹⁴⁰ Recent immigrants are likely also overrepresented in the unscored consumer category because, despite potentially favorable credit histories in their native countries, they lack credit history in the United States.¹⁴¹ Some nonprofits offer “fresh start” loans, which are zero-interest, small-dollar loans to aid recent migrants’ essential credit score building, though such efforts are inevitably limited in scope.¹⁴² These disparities suggest that already marginalized consumers are at a disproportionate risk of being incorrectly characterized as poor credit risks. The inadvertent creation of unscored consumers frustrates the credit scoring system’s promise to mitigate discrimination and promote equity.

2. Marginalized in Markets

Notwithstanding, the credit scoring system is used to justify marginalizing unscored consumers in the marketplace with excessive barriers, fees, and punitive measures. When likened to consumers with poor credit scores, unscored consumers face similar rates of rejection or similarly burdensome terms in mainstream credit markets. Unscored consumers are also relegated to fringe credit markets for their essential credit needs. Fringe credit markets do not rely on traditional credit scores to offer credit products. However, these products—such as payday loans, auto title loans, pawnshop loans, rent-to-own leases, and tax refund anticipation loans—often carry high costs and onerous, short-term repayment terms and are routinely associated with devastating wealth effects.

Specifically, fringe credit products are structured in ways that often trap low-income consumers in cycles of debt and financial precarity. Payday loans, though small and short-term, come with extremely high fees and interest rates and are typically repaid via automatic bank account withdrawals—often leading to overdrafts and financial instability with ripple effects on local economies.¹⁴³ Slightly less expensive auto title loans are secured by a borrower’s vehicle, which can be repossessed upon default,¹⁴⁴ undermining employment for those without alternative transportation. Rent-to-own leases and pawnshop loans carry similarly high costs and result in the loss of valuable personal property if payments are missed, with borrowers forfeiting any equity or prepayments made.¹⁴⁵

Tax refund anticipation loans, based on expected tax refunds, also pose risks by prioritizing lender repayment from IRS deposits before the borrower receives any remaining funds. Hidden fees, automatic repayment, and smaller-than-anticipated refunds can leave consumers without the adequate funds, leading to more borrowing.¹⁴⁶ Collectively, these lending practices disproportionately affect low-income individuals, which drains wealth from vulnerable communities. A recent study reported that, in Texas alone, such loans accounted for $1.6 billion in economic losses and over 21,000 lost jobs.¹⁴⁷

Moreover, being relegated to the fringe credit market generally can have devastating physical and mental health effects.¹⁴⁸ Yet, even if borrowers overcome the high odds of default and repay fringe credit balances on time, they are often not deemed any more creditworthy. In many cases, fringe lenders do not report positive payment history to credit reporting agencies, meaning this credit activity does not help borrowers build positive credit scores.¹⁴⁹ Without a pathway to lower-cost, mainstream credit products, unscored borrowers remain trapped in a perpetual and costly cycle within the fringe credit market.

Unscored consumers may also suffer costly penalties in other areas of their economic lives. For starters, unscored consumers are generally foreclosed from the wealth-building housing market. Less than 0.1% of federally subsidized home mortgages go to consumers without credit scores.¹⁵⁰ Moreover, character or risk assessments in nonlending contexts—including rental housing, utility services, auto insurance, and employment—increasingly use credit scores. Nearly half of landlords perform credit checks in rental application screenings.¹⁵¹ For one congressman, a six-figure income and powerful job position could not overcome the foreclosing effect of a poor credit score.¹⁵² Unscored consumers face similar limitations to their housing options even if they have the income to support rental or mortgage payments.¹⁵³ Credit scores are also used to price heat, electricity, and water services. Service providers may force consumers without a sufficient credit score to pay security deposits equal to one or more monthly payment.¹⁵⁴ In the context of auto insurance, if treated akin to those with poor credit scores, unscored consumers risk paying premiums that are 44% and 115% greater than consumers with fair and excellent credit scores respectively, resulting in premiums averaging over $1,000 annually.¹⁵⁵ Unscored consumers may also have curtailed job prospects as an increasing number of hiring managers run credit checks to screen candidates.¹⁵⁶

* * *

In sum, credit is essential for both financial security and wealth accumulation. Most households rely on credit to cover day-to-day expenses, purchase homes, and build businesses. Lenders seeking to maximize profits from this demand rely, in part, on credit scores to identify creditworthy consumers—that is, consumers most likely to repay their loans. Credit scores were developed to increase efficiency and reduce discrimination in the credit underwriting process.¹⁵⁷ Today, they serve as a ubiquitous gatekeeping mechanism not only in credit markets, but also in other vital markets, including the job market. However, the credit scoring system’s backward-looking nature has created a class of over thirty-two million unscored consumers¹⁵⁸ who are indiscriminately presumed to be high credit risks, even though most are likely to repay their debts. This false signal unduly creates financial hurdles and market frictions that disproportionately impact minority, low-income, and immigrant consumers while also inhibiting profit-maximizing opportunities for lenders. Rather than remedy the inefficiencies and inequities of credit underwriting, the credit scoring system has in some ways repackaged these harmful shortcomings in the sheep’s clothing of statistical models.

II. Siloed Solutions

Consumer advocates have long critiqued the financial hurdles faced by unscored consumers.¹⁵⁹ Typical workarounds—using secured credit cards, becoming an authorized user, or opening a student credit card—reflect privileged access points not available to all unscored consumers. Yet, as this Part details, the market’s innovative efforts to self-correct are insufficient. Specifically, the market has responded in two siloed ways: expanding scoring model inputs to better evaluate the creditworthiness of unscored consumers or evading scoring models altogether and offering fringe services based solely on capacity to pay and often on more favorable terms than traditional fringe options. However, the costs of these market efforts likely outweigh their limited benefits and, critically, fail to redress the credit score conundrum’s root cause.

A. Alternative Underwriting

1. Innovation

The most popular innovation within the “expand” category is alternative underwriting. Fintech firms, such as marketplace lenders,¹⁶⁰ ushered in innovations in their underwriting processes that supplement traditional credit scores with “alternative data,” or consumer data not traditionally included in consumer reports.¹⁶¹ Such data may include supplemental financial information—such as cash flow data in bank accounts, additional income verifications, or child support information. According to a recent industry survey, 59% of mainstream lenders now use supplemental financial data. ¹⁶² Alternative data can also be nonfinancial. Lenders like Upstart Network, Inc. and Climb Credit look to academic institutions, degree programs, and standardized test scores to assess creditworthiness.¹⁶³ Although not yet openly used in the U.S. credit markets, a growing number of researchers, consumer advocates, and fintech lenders see predictive value in data such as social media contacts,¹⁶⁴ location,¹⁶⁵ shopping habits,¹⁶⁶ mobile app usage,¹⁶⁷ and health information.¹⁶⁸ Thanks to big data technology and machine learning algorithms, the number of alternative data points that may factor into loan underwriting now exceeds tens of thousands.¹⁶⁹ Some lenders enthusiastically endorse the use of any and all available information in the creditworthiness calculus.¹⁷⁰

Proponents believe alternative data can improve the creditworthiness signals for scored consumers and expand credit access for unscored consumers.¹⁷¹ This argument is most intuitive for alternative financial data. Cash flow data, for example, discloses the transaction details for deposit or prepaid card accounts.¹⁷² With access to account-level credit and debit details, lenders can directly assess a consumer’s net income, spending habits, and financial management. According to a recent, albeit limited, study by the Consumer Financial Protection Bureau (CFPB), such details may reveal positive creditworthiness that contradicts low credit scores.¹⁷³ By extension, such details also belie the negative implication of having no credit score.

Less intuitive is the use of nonfinancial alternative data, which relies on the black box of algorithmic models that weigh data points to find correlations that predict creditworthiness.¹⁷⁴ For example, lenders that consider educational institutions, degree programs, and standardized test scores correlate individual creditworthiness with the average economic outcomes of graduates from similar institutions or backgrounds.¹⁷⁵ And a robust body of literature on social networks and creditworthiness finds statistically significant correlations between a borrower’s creditworthiness and the size and socioeconomic status of their social circles.¹⁷⁶

2. Promise & Perils

By relying upon statistical models to correlate between creditworthiness and nonfinancial data, lenders can look beyond traditional credit scores to conduct more thorough, individualized creditworthiness assessments that were once too costly. Alternative underwriting demonstrably expands access to credit. A recent study indicates that alternative underwriting models based on education and employment data reduce the likelihood of credit application rejections for a group of consumers with credit scores below 640 by 70% to 100%.¹⁷⁷ This study also shows a greater correlation between ex ante creditworthiness determinations under the alternative underwriting model and ex post default probability.¹⁷⁸ That is to say, the alternative underwriting model more accurately predicts a consumer’s default risk than their poor credit score. Similarly, firms like Upstart assert that alternative underwriting allows them to extend credit to 35% more Black borrowers and 46% more Latinx borrowers than would a credit-score-only underwriting approach.¹⁷⁹ Upstart also boasts that it can lower the costs of borrowing for these groups as well.¹⁸⁰

By ignoring erroneous credit score signals, lenders can increase profits while their consumers are able to access credit that demonstrably facilitates higher credit scores, new home purchases, and economic stability in future months.¹⁸¹ Consequently, when treated akin to consumers with poor scores, unscored consumers are likely to fare better under an alternative underwriting model. Moreover, by relying on data other than credit history, alternative underwriting mitigates the credit scoring system’s chicken-and-egg dilemma and provides unscored consumers with an on-ramp to otherwise score-dependent, mainstream credit.

Despite its promise, alternative underwriting imposes a host of unduly high costs on unscored consumers that exacerbate market inequalities. These costs include disparate privacy risks, heightened surveillance, and discriminatory impact.

a. Privacy Risks

To benefit from alternative underwriting, consumers must share increasingly sensitive personal data, such as bank or utility account logins. In the wrong hands, this information can pose serious financial and even physical risks. Although this is alarming for any consumer, it is particularly concerning for low-income and minority consumers, who are most likely to share such sensitive data to improve creditworthiness determinations. In the event that a lender using alternative underwriting experiences a data breach, these consumers are especially easy targets for identity thieves.¹⁸² Because of lengthy and complex remedial processes, these consumers are less likely to pursue complaints.¹⁸³ Even when they do, delays obtaining relief make it insufficient to repair the cascading harms that likely result from already precarious financial circumstances.¹⁸⁴

There are also arguable risks to physical and emotional well-being posed by such privacy breaches. Anyone with sensitive data, such as bank account logins, stands to accumulate countless other highly personal data points, including where the consumer lives, which daycare they send their children to, which coffee shop they visit every morning, if and where they seek mental health therapy, and other sensitive consumer habits. Utility login information grants insights into what times of day a person is usually home. It is not difficult to imagine how this information, in the wrong hands, can pose serious security risks to consumers.

b. Surveillance Risks

Alternative underwriting also subjects consumers to greater surveillance. And since unscored consumers are uniquely dependent on these innovations to prove creditworthiness, they are compelled into inequitable data sharing that exacerbates the outsized surveillance that many may already experience.¹⁸⁵ Specifically, many minority and low-income consumers can only access necessary housing, groceries, or even smartphone services subject to heightened surveillance.¹⁸⁶ By adding the credit scoring system to the list of services that require outsized surveillance for these groups, the system exacerbates their disproportionate surveillance risks as well. Specifically, such inequitable data sharing gives firms the enhanced ability to influence the purchasing decisions of unscored consumers compared to those consumers who opt out.¹⁸⁷ And such influence is especially potent for unscored consumers, who face limited options in the marketplace and limited access to sound financial advice. Often, such influence is used to nudge consumers toward products that are profitable for the provider but extractive for the consumer.¹⁸⁸

c. Discrimination Risks

As others have noted, the use of alternative data risks entrenching discrimination in creditworthiness assessments.¹⁸⁹ Though federal law now prohibits credit decisions based on protected class identities, the use of alternative data can result in credit decisions based on proxies to such identities.¹⁹⁰ Perhaps most problematically, the use of alternative data within the black box of algorithmic underwriting makes it near impossible to discern just which data points drive a credit decision.¹⁹¹ For example, although Upstart advertises that it extends credit to more minority borrowers than traditional models, its model has also been accused of charging higher fees to graduates of historically Black colleges and universities (HBCUs) compared to students with identical financial profiles from non-HBCU institutions.¹⁹² These concerns have contributed to congressional hearings investigating algorithmic underwriting and the use of alternative data.¹⁹³ In its defense, Upstart asserts that its model does not consider the racial makeup of schools but instead relies on the aggregated performance of graduates from similar institutions.¹⁹⁴ Yet this approach penalizes borrowers who may have chosen colleges for cultural, geographic, financial, or other personal reasons that have little to do with their individual creditworthiness. Similarly, the promise of looking at social networks to assess creditworthiness would penalize friendship dynamics that merely reflect the reality that most American communities are racially and socioeconomically segregated. In doing so, creditworthy consumers from disadvantaged backgrounds may be penalized for preserving social and community ties that predate their upward mobility. Thus, alternative underwriting raises questions about the appropriate level of aggregation to facilitate creditworthiness assessments without unfairly discriminating against cultural or social, rather than economic, choices.

B. Enhanced Scoring Models

1. Innovation

Seemingly in response to alternative underwriting, credit reporting agencies have begun incorporating certain alternative data into traditional scoring models. In 2018, FICO and Experian partnered to launch the “UltraFICO” score, which is a free, opt-in service that allows consumers to share cash flow data from their deposit accounts for a more comprehensive credit score.¹⁹⁵ Consumers may sign up through the FICO website and link their bank accounts, which are scanned by a proprietary algorithm that outputs an UltraFICO score based on the consumer’s cash flow management and how long their deposit accounts were open.¹⁹⁶ Experian also offers “Experian Boost,” which allows consumers to share payment history for rental housing, utility services, telecom services, and select streaming services.¹⁹⁷ To sign up, consumers must share their credit card or banking login for Experian’s model to scan transaction history for qualifying payments. The model only considers on-time payments, so late payments do not lower credit scores. Equifax’s “OneScore” credit score similarly incorporates alternative financial data like payment histories for utilities, telecom and streaming services, and fringe market loans.¹⁹⁸ TransUnion, for its part, offers its new “TruVision” credit scores, which incorporate both alternative financial data and trended data.¹⁹⁹ With trended data, TruVision scores reflect trends in credit history over a thirty-month period rather than a single snapshot of the overall credit history. As a result, positive, incremental improvements in payment history over time are thought to benefit consumers more under a TruVision score than under a traditional credit score.²⁰⁰ TransUnion culls its alternative financial data from 3 billion records for 260 million consumers, including property tax and deed records, deposit account history, payday loans, and address stability.²⁰¹

2. Promises & Perils

Like alternative underwriting, enhanced scoring models promise to make creditworthiness determinable for unscored consumers who do not have traditional credit history. Indeed, Equifax promises to make more than 20% of unscored consumers scorable.²⁰² And TransUnion advertises that its enhanced model can assess the creditworthiness of more than 90% of unscored consumers.²⁰³ These models also promise to improve the standing of scored consumers. On average, Experian Boost reports increasing FICO credit scores by thirteen points near instantly, though some consumers may not see any meaningful change in their credit scores.²⁰⁴ Moreover, enhanced scoring models have a slight edge over alternative underwriting. Because these changes occur at the credit rating agencies, rather than in-house at individual lenders, the benefits of alternative data in credit scoring could extend to the broader range of economic activities that rely on credit scores for eligibility and pricing. Providers in these contexts are less likely to have in-house underwriting models as they do not issue credit despite relying on credit scores. The unique promise of enhanced scoring models is the breadth of their ability to redefine creditworthiness in the marketplace.

However, like alternative underwriting, more information risks more problems. The same privacy risks arise in enhanced scoring models and may even be more acute. In 2017, Equifax announced that the personal information of 147 million people—including names, addresses, and social security numbers—had been accessed by unauthorized parties.²⁰⁵ As a result, Equifax settled with financial regulators to pay up to $425 million to repair financial harms and provide identity theft protection to affected consumers.²⁰⁶ By adding, for example, bank account logins to the data stored at credit reporting agencies, would-be identity thieves could steal directly from consumer bank accounts.²⁰⁷ The costs of such breaches would likely skyrocket while the reparability of the harms produced would decline. The surveillance and nudging risks mirror those in the alternative underwriting context; the only difference is the source. The credit rating agencies can themselves advertise partner services to consumers or sell consumer data to market providers that can nudge directly.

Such costs have fewer offsetting practical benefits for enhanced scoring models than alternative underwriting. Despite improving a credit score’s numerical value, alternative data has done little to boost a credit score’s substantive value—that is, to move a consumer from “poor” to “fair” or from “fair” to “good.” ²⁰⁸ This suggests that reporting agencies assign alternative data less predictive value than traditional data in enhanced scoring models, which rarely results in meaningfully altering credit scores. This muted influence may stem from the limited reporting of alternative data to reporting agencies, despite agencies now welcoming the data.²⁰⁹ Providers of new payment histories—such as landlords, utility firms, and fringe creditors—have limited market incentive and no legal obligation to bear the costs of reporting tradelines to the credit bureaus. Even when nudged to report, these providers may view doing so as futile. Moreover, most market participants continue to rely on older FICO models, like FICO Score 8, that exclude alternative data altogether.²¹⁰

C. Third-Party Tradeline Services

1. Innovation

A burgeoning tradeline market offers new access points for building credit histories that generate credit scores. In this market, providers sell tradelines—credit accounts that are reported to the credit rating agencies.²¹¹ For example, rent reporting firms are tradeline providers that, as the name suggests, facilitate tradelines for rental housing.²¹² Rent reporting services are typically fee-based,²¹³ with fees paid by landlords,²¹⁴ renters,²¹⁵ or both.²¹⁶ Esusu, a popular rent reporting firm, reports rental data to the big three credit rating agencies and charges landlords a $3,500 startup fee and $2 per reporting rental unit.²¹⁷ It also charges renters a $120 annual subscription fee.²¹⁸ However, Esusu has recently partnered with Fannie Mae to offer a rent reporting program that is free to consumers.²¹⁹ Though still nascent, the market for rent reporting services is growing rapidly, attracting robust private equity interest. Within just four years of its founding, Esusu became a “unicorn,” reaching a $1 billion valuation and drawing celebrity investors.²²⁰

“Piggybacking,” a more fringe tradeline service, sells authorized user status.²²¹ An authorized user is a consumer added to another consumer’s—the primary cardholder—credit card account. The credit card is typically issued in the authorized user’s name but uses the account number of the primary cardholder. As a result, the authorized user can make purchases on the account, but only the primary cardholder is responsible for repayment. It is common for the primary cardholder’s account history to be reported on the authorized user’s credit report.²²² Authorized users can build credit by “piggybacking” on the primary cardholder’s credit history. This practice is expected among relatives or parties in an agent-assignee relationship. For instance, an authorized user may be a significant other with whom one already shares household expenses, a child for whom one is helping to build credit, or an employee who is authorized to make expenditures on behalf of a firm.²²³ However, a for-profit market for piggybacking has emerged, pairing primary cardholders and authorized users who are complete strangers. Consumers may be charged $300 to $1,750 to become authorized users, with the promise that a new tradeline reflecting positive payment history will appear on their credit report and boost their credit score almost instantly.²²⁴

2. Promises & Perils

Unlike other credit innovations, tradeline providers promise to increase credit data that boosts traditional credit scores, rather than feed rarely used enhanced scoring models. Esusu, for example, reports that its services have raised consumer credit scores by an average of forty-five points and established credit scores for more than 107,000 previously unscored consumers.²²⁵ For some consumers, such a substantive score increase motivates more positive repayment history in other areas to maintain it.²²⁶ Even the more fringe tradeline services, though frowned upon, address an inequity in the current system. Through piggybacking, unscored consumers can purchase the on-ramp to credit markets enjoyed by those with privileged social networks.

However, these narrowly tailored services can foster their own unscored consumer dilemma. Take rent reporting firms: With a singular focus on rental history, these firms cannot assist consumers who do not have rental leases in their own names. Yet nearly 45% of consumers between the ages of eighteen and twenty-nine live in their parents’ homes.²²⁷ And although racial disparities between young adults living with parents significantly declined during the pandemic, Black and Hispanic young adults were, and continue to be, more likely to live at home²²⁸ and less likely to view doing so negatively.²²⁹ Moreover, a 2018 study found that Black consumers are five times more sensitive to rent increases than white consumers when deciding whether to remain in their parents’ home.²³⁰ With exponentially rising rental costs, rent reporting firms cannot aid those consumers who make economically sound decisions to live with their parents.²³¹ Additionally, third-party tradeline reporting services take time to build traditional credit reports—at least six months to establish reports and likely even longer to create “good” scores. Such a delay, combined with additional out-of-pocket costs and the persistent risk of remaining unscored, renders third-party tradeline reporting a suboptimal solution to the credit score conundrum.

Piggybacking similarly offers limited benefits to unscored consumers. Although it may provide a near-term score boost, the extent of that improvement is questionable. Recent litigation suggests that piggybacking firms mislead consumers by grossly overstating potential credit score increases.²³² Even effective piggybacking services risk generating false signals of positive creditworthiness for those with poor credit activity. Piggybacking assumes the relationship between an authorized user and primary cardholder is a credible proxy for creditworthiness; but that proxy becomes noisy when the relationship is transactional rather than real. And contrary to the age-old adage,²³³ the ability to purchase the proxy crudely suggests creditworthiness may be bought. This may explain why many view these services as ethically questionable.²³⁴

Finally, these innovations risk burdening unscored consumers with a unique “tax” or additional monetary costs to obtain a credit score. Many third-party tradeline services create a “pay to play” dynamic in the market, placing additional costs on consumers who have the least disposable income. Rent reporting services highlight that renters, unlike homeowners, must take on additional time, costs, and privacy burdens to be deemed creditworthy for their timely housing payments. Piggybacking services, meanwhile, highlight the privileges of some social networks over others whose members must pay for access to beneficial authorized user statuses. These market dynamics undoubtedly contribute to an already troubling broader market concern of low-income consumers paying more for financial services.²³⁵

D. Earned Wage Access & Buy-Now, Pay-Later

1. Innovation

Turning to the “evade” category, earned-wage-access (EWA) providers offer cash advances based on earned, but unpaid, wages.²³⁶ The dollar amount of EWA cash advances is typically capped at a percentage of net earnings accrued by the date of the consumer’s request, though some providers allow a limited number of withdrawals from such earnings. Many EWA providers partner with firms and are integrated into the latter’s payroll systems to assess consumers’ daily or hourly earnings as accrued in real time. Other programs estimate accrued earnings by relying on data received from the consumer, such as time sheet data or location data to show commutes.²³⁷ For this service, many EWA providers are compensated through various fee structures, including monthly subscription fees, per-withdrawal fees, or fees for expedited money transfers.²³⁸ Other EWA providers advertise free services subject to optional tips. Consumers repay EWA cash advances by their next payday via a direct garnishment deducted automatically from their paycheck or by a pre-authorized transfer from their bank account. By ensuring payment in such manners, EWA providers insulate themselves from consumer default.²³⁹ Consequently, EWA providers have little incentive to consider creditworthy character or, in turn, consumer credit scores. Thus, EWA providers promise to fill a lending void to low-wage workers²⁴⁰ and particularly unscored consumers.²⁴¹

Similarly, point-of-sale financing or buy-now-pay-later (BNPL) products largely bypass traditional credit scoring systems. BNPL products allow consumers to opt for installment payments at the time of purchase instead of paying in full for retail goods or services. When a consumer selects the installment option, the BNPL provider immediately pays the retailer in full on the consumer’s behalf and is then repaid by the consumer over the installment period. In a typical transaction, there are four installments: The first is paid at the time of purchase, and the remaining three are paid every two weeks thereafter.²⁴² This flexibility is usually available at no charge to consumers, subject to a late payment fee up to $15 or 25% of the installment amount.²⁴³ Instead, merchants pay BNPL providers through fees justified by potential increases in online sales. Indeed, one BNPL provider advertises that merchants can see a 12% increase in revenues with their BNPL product.²⁴⁴ For consumers, BNPL products function much like credit cards, except they are subsidized by merchants. In shifting the service costs to merchants, BNPL providers have little incentive to evaluate creditworthiness. Some do not consider credit scores at all,²⁴⁵ while others conduct a “soft” credit check with incredibly flexible access thresholds.²⁴⁶

2. Promises & Perils

EWA and BNPL services promise to expand access to credit in the absence of a credit score. Unscored consumers can turn to these services as an alternative to fringe credit products like payday loans. Over 30% of consumers use BNPL services when faced with limited access to mainstream credit products.²⁴⁷ EWA and BNPL services also promise lower costs and risks as compared to traditional fringe credit products. Specifically, EWA providers often disclaim offering credit products at all; instead, EWA providers market their programs as interest-free payment services that are offered at nominal or optional fees.²⁴⁸ Though most BNPL providers concede to offering credit products, they similarly claim to offer interest-free services, subject to nominal fixed, low-cost fees. Nearly 60% of BNPL consumers report using the products to avoid paying interest on mainstream credit products.²⁴⁹

However, EWA or BNPL services are, at best, band-aids on an untreated wound and, at worst, salt in it. Though they increase access to credit, a recent survey found that most BNPL consumers have credit scores.²⁵⁰ Rather than serving unscored consumers, these services typically expand access for consumers with existing poor credit histories.²⁵¹ Additionally, the apps that power these services raise the same surveillance and nudging concerns surrounding alternative underwriting. By linking to payroll and bank accounts, the apps enable providers to steer consumers toward complimentary credit products, often with longer repayment terms and high interest rates.²⁵² Moreover, usage patterns among EWA²⁵³ and BNPL²⁵⁴ consumers suggest that the supposedly nominal fees can, over time, pose financial risks akin to those posed by high-cost payday lending.

Further, even if unscored consumers made meaningful use of these services, EWA and BNPL programs fail to bridge the gap between the fringe and mainstream credit markets. To date, EWA programs and BNPL products are rarely reported to credit bureaus,²⁵⁵ preventing consumers from building credit scores. These services therefore reinforce the status quo of the credit scoring conundrum—the creditworthiness of unscored consumers remains unknown. In recognizing this shortcoming, FICO recently announced a new scoring model expected to be released in the fall of 2025 that will incorporate BNPL products.²⁵⁶ The new models are expected to treat all BNPL loans as a single tradeline to avoid penalizing consumers for customarily opening multiple BNPL credit lines.²⁵⁷ Early data from one BNPL provider showed that reporting to FICO had a maximum ten-point impact on credit scores for 85% of BNPL users, though the majority of such consumers saw limited improvements or no change at all.²⁵⁸ The benefits for unscored consumers appear limited. Moreover, two key BNPL providers recently announced that they will not share consumer data with FICO.²⁵⁹ These firms remain concerned that FICO’s scoring models will penalize BNPL consumers for mere usage.²⁶⁰ Consequently, without industry cooperation, it is unlikely that BNPL data will be effectively incorporated into credit scores for any consumers.

Finally, even if EWA and BNPL services were made comparable to mainstream credit services, effectively eliminating the need for a credit score to access fair credit, unscored consumers would still struggle to access the many economic activities that rely on credit scores. As a result, unscored consumers would remain suspended between a rock—reliance on fringe credit markets—and a hard place—continued marginalization in the mainstream market.

* * *

Unscored consumers without privileged access points may rely on recent market innovations that either expand opportunities for a more favorable creditworthiness determination or offer liquidity solutions that bypass the inquiry altogether. Yet, these innovations carry costs that likely outweigh their limited benefits. Most troubling, they fail to resolve the credit score conundrum. Efforts to evade the system ignore the credit score’s essential role not only in mainstream credit services, but in other essential sectors of economic life as well. Thus, unscored consumers largely remain unscored and economically marginalized.

In contrast, efforts to improve the system presume the necessity of a backward-looking metric. Thus, while not relying on credit history per se, they often rely on a history of something, such as education, social connections, or payment activity. To be sure, these efforts may offer some unscored consumers favorable scores, albeit at a price. Others, lacking such histories, will remain unscored. Still others will cement a “poor” score status based on personal characteristics correlated with credit risk, rather than their personal financial behavior.

Given how mission-critical credit scores have become to full participation in the economy, these symptomatic and costly market interventions raise a fundamental question: Is proving creditworthiness an indispensable prerequisite to receiving a credit score?

III. The Burden of Proving Creditworthiness

This Part interrogates the intuitive appeal of requiring unscored consumers to first prove their creditworthiness and explains how such a requirement leads to a form of adverse selection. By examining the ways in which other developed credit markets define creditworthiness, this Part contends that burdening consumers with proving their creditworthiness is a U.S. policy choice that should be reevaluated. This Part argues that presuming creditworthiness upon first entry to the marketplace would better serve the efficiency and equity goals undergirding the credit scoring system, thereby eradicating the “unscored” consumer status.

A. Destined for Market Failure

A look at the psychology and economics literature reveals that, although backward-looking metrics may be useful for creditworthiness determinations, they must be narrowly tailored and properly balanced against factors outside the consumer’s control that affect their default risk. In each case, the literature counsels against backward-looking credit scoring, whether traditional or with alternative data, for unscored consumers. The result is a form of adverse selection, which can be addressed only by sharing relevant information or government intervention.

1. “Past Behavior” Limits

A common assumption is that creditworthiness determinations are necessarily backward-looking because past behavior is the best indicator of future conduct. ²⁶¹ This view has intuitive appeal and support in both psychology²⁶² and economics²⁶³ literature. However, there are key limitations to this justification.

In psychology, scholars suggest that past conduct must be nearly identical to the future behavior being predicted.²⁶⁴ They note that the predictive value of past behavior wanes over time and is shaped by changes in context, the person’s perception of the conduct’s consequences, and their self-perception.²⁶⁵ In economics, it remains unsettled which patterns of past activity have the optimal predictive value for future default risks.²⁶⁶ For example, recent studies suggest that traditional credit scoring models overstate the predictive value of factors like the length of credit history and number of credit inquiries.²⁶⁷ Rather, high credit balances are better indicators of default risk.²⁶⁸ Behavioral economists, in turn, surface psychological effects, such as impulsivity, as key indicators of default risk.²⁶⁹ And still, others highlight that credit products’ terms, rather than just the borrower’s past behavior, affect default risks.²⁷⁰

Consequently, treating the absence of credit activity like the presence of poor credit activity may be misguided. From a psychology perspective, unscored consumers lack the strongest indicator of future borrowing activity in mainstream credit markets: a history of borrowing mainstream credit. If the past behavior should be nearly identical to future behavior to be effectively predictive, then such literature may suggest that alternative financial activity, including fringe credit usage or rent repayment, is poorly matched to predict activity in mainstream credit markets. The harsher terms of fringe credit products likely heighten default risks that would be lower in the mainstream credit market. Some consumers are also likely to weigh the benefit of making timely rent or utility payments against timely debt repayments differently, and the balance may shift under varying economic conditions.²⁷¹ Indeed, consumers even distinguish repayment between types of debt, such as opting to timely repay credit cards over home mortgages.²⁷²

From an economics perspective, if high credit balances are better indicators of credit risk than past credit activity, then unscored consumers could be viewed as good credit risks by having nominal or zero credit balances. And although impulsivity may be demonstrated by nonborrowing behavior, an unscored consumer’s lack of indebtedness may reasonably be viewed in their favor. Yet, if the terms of credit contribute to default risks, then relegating unscored consumers to fringe products or other credit with onerous terms upon market entry all but ensures these consumers become poor risks over time, despite not inherently being so at the outset.

To be sure, the foregoing does not dispel the benefit of alternative data grounded in statistical correlations to creditworthiness. But it does suggest that such data may be suboptimal when compared to comparable borrowing activity. If alternative data is indeed suboptimal compared to borrowing activity, then the disparate reliance on it for unscored consumers, as opposed to scored consumers, raises inextricably intertwined efficiency and equity concerns. In sum, while the maxim that past behavior predicts future conduct offers the best rationale for a system that judges consumers with existing credit activity, the maxim reveals such a system is a misfit for consumers with no credit activity.

2. Adverse Selection

How the marketplace treats unscored consumers may be best understood through the lens of adverse selection. Under this principle, information asymmetries in a marketplace lead to systemically pricing out high quality, bargain-cost options. As these options exit the market, prices become progressively worse for the remaining lower-quality options, thereby pricing out the next tier of quality options and so on and so on.²⁷³ This downward spiral is famously illustrated by the “market for lemons.” The used-car market assumes that people with defective cars (“lemons”) are more likely to sell their cars than people with good cars. Because buyers cannot distinguish between the two car qualities when shopping, they are only willing to pay low prices that reflect the high risk of the purchased car being a lemon.²⁷⁴ Those low prices drive sellers with good cars to opt out of the market altogether, increasing the proportion of lemons and further depressing prices. The downward dance between quality and price problematically thins the market and distorts prices and, at its worst, becomes the self-reinforcing “death spiral” that collapses the market altogether.²⁷⁵

A similar, but more problematic, iteration of this phenomenon emerges with unscored consumers. When consumers do not have a credit score, lenders and other providers perceive a key data point as missing. An information asymmetry exists as to whether unscored consumers are creditworthy or risky. According to the principle of adverse selection, unscored consumers who are “lemons” (poor credit risks) are presumed to be more likely to seek credit than those that are high-quality credit risks. Lenders thus offer credit—if at all—on onerous terms that reflect the perceived high risk that unscored applicants are poor credit risks. Yet, due to the essentiality of credit, only the most “privileged” of quality unscored consumers will opt out, such as those who can operate solely in cash or who borrow from relatives. The remaining unscored consumers will be compelled to opt in, which should avoid a death spiral, since there remain quality unscored consumers. However, in this context, the death spiral is driven less by quality consumers exiting in the market than by the onerous lender terms that amplify default risk, effectively converting quality consumers into bad ones, which further entrenches fringe lenders and locks unscored consumers out of mainstream credit markets.

Economists have identified several ways to mitigate adverse selection. The first is through information acquisition.²⁷⁶ This approach is reflected in ongoing market efforts to incorporate alternative data into credit scoring or to collect traditional data through additional channels. As discussed in Part II, fintech lenders and FICO research demonstrates that most unscored consumers who seek credit are quality credit risks.²⁷⁷ But such information acquisition is a costly yet incomplete solution, benefiting only a small subset of unscored consumers.²⁷⁸

The second strategy is to limit lender risk exposure through contractual mechanisms, such as limited principal amounts or automatic repayments systems.²⁷⁹ This approach is reflected in the efforts adopted by fringe creditors like payday lenders and fintech firms like EWA and BNPL providers. Unfortunately, these mechanisms shift the risk back onto consumers, often contributing to a heightened risk of financial precarity.

Finally, a third approach is government intervention through mandatory participation.²⁸⁰ In the typical insurance example, such a mandate might require all individuals to purchase insurance and pay premiums equal to the average risk.²⁸¹ Applied to the credit market, such a policy might mandate that consumers who are quality credit risks subsidize those that are poor credit risks to ensure a market exists for those who are unknown risks—i.e., unscored consumers. Alternatively, it might mandate that lenders extend introductory mainstream credit on favorable terms to unscored consumers while absorbing—or being subsidized for—the associated risk. Despite its potential, such government intervention has yet to be considered.

B. Proving vs. Presuming: A Policy Choice

A look at the international landscape reveals that a presumption of creditworthiness for unscored consumers is not farfetched. Indeed, the U.S. approach to defining creditworthiness is less a neutral market necessity and more a deliberate policy choice. The practices of countries like Germany, the Netherlands, Spain, Japan, and France bring the United States’ distinct—albeit not unique²⁸²—choice into sharper focus.

1. Introductory Scores

In Germany, creditworthiness is similarly backward-looking, except for new market entrants. The central credit rating agency, SCHUFA,²⁸³ functions as both a data aggregator and a score provider, essentially acting as both FICO and the “big three.” Nearly 9,000 partner firms—including lenders, telecommunication providers, and rental agencies—share consumer data with SCHUFA.²⁸⁴ SCHUFA then uses this data, including activity the United States might classify as “alternative,” to generate its own proprietary credit scores.²⁸⁵ Unlike the United States’ approach, all consumers—rather than an unprivileged few—are subject to this surveillance. By some accounts, a SCHUFA record is automatically generated for anyone that opens a bank account, purchases internet or mobile phone services, or registers a home address.²⁸⁶ A basic score²⁸⁷ is expressed as a percentage, with scores above 97% signifying excellent creditworthiness.²⁸⁸

In contrast to the United States, consumers with no payment histories can, upon request, receive a SCHUFA score. Although sometimes described as starting consumers with a “perfect” score, SCHUFA does not guarantee a perfect initial score.²⁸⁹ Instead, consumers typically begin with a neutral to moderately positive probability score, often in the 90% range, assuming no adverse data.²⁹⁰ Lenders are likely to view these consumers as reasonable credit risks, subject to the lender’s independent underwriting assessment.²⁹¹ This score decreases as a consumer exhibits behaviors associated with risk, such as taking out too many loans, maintaining high balances on credit accounts, or having financial court judgments.²⁹² Missed or late payments on utility, mobile phone, and other consumer contracts that constitute ongoing obligations can also reduce a consumer’s score. Alternatively, this score would increase as the consumer develops a positive payment history.²⁹³ Thus, to use the U.S. credit scoring terminology, the German system likely presumes unscored consumers are “good” to “fair” credit risks. Moreover, the German system rewards financial conservatism—maintaining fewer credit and deposit accounts, consolidating loans, and paying down loan balances over taking on new debt—rather than onerously penalizing the absence of borrowing history.

2. Blacklists

In the Netherlands and Spain, consumers do not receive a score at all. Instead, each country assesses creditworthiness largely through the absence or presence of negative credit activity, with positive credit activity playing only a minimal or indirect role. Specifically, the Netherlands’s National Credit Register (BKR) tracks two types of registries—a positive registry for account openings and a negative registry for nonpayment activity (a “blacklist”). Although some accounts are exempt from a positive registry, no nonpayment is exempt from a negative registry.²⁹⁴ And though creditors can review both registries held for a consumer, a negative registry—which remains on the BKR for five years—is weighed more heavily in assessing creditworthiness.²⁹⁵ In contrast, under Spain’s Risk Management Centre (CIR), such negative histories remain on private registries for six years.²⁹⁶ Spain is otherwise similar to the Netherlands in that it tracks all credit data, though only nonpayment activity operates to hinder creditworthiness.²⁹⁷ Consumers in these countries are presumed creditworthy unless they appear on a blacklist. And since positive activity minimally influences creditworthiness, these systems treat consumers with no credit history more akin to those with positive credit history—unlike the United States’ approach, which treats consumers with no credit history more akin to those with poor credit history. By evaluating creditworthiness in this manner, these countries, like Germany, reward consumer cultures that favor cash payments and delay credit consumption for large purchases.

3. Relational Underwriting

In Japan and France, there are no centralized, nationalized credit scoring systems.²⁹⁸ Credit histories are tracked in these countries, but they are secondary considerations. Rather, creditworthiness relies primarily on banking relationships, income stability, and cash flow assessments.²⁹⁹ Japan does have three private credit bureaus that track consumer credit activity once a consumer opens a credit account.³⁰⁰ However, these agencies do not generate credit scores.³⁰¹ Individualized bank assessments use these records but give heavier weight to the consumer’s relationship with the bank, employment history, and income.³⁰² Although France maintains a negative registry similar to the Netherlands and Spain, individualized bank assessments prioritize an individual’s income and cash flow to determine creditworthiness. ³⁰³ Each system effectively eliminates the credit score conundrum unscored consumers face in the United States. The way to signal creditworthiness in Japan and France begins with cash savings or positive cash management, neither of which first requires a credit score or other creditworthiness assessment.

4. Preliminary Lessons

Preliminary takeaways suggest more flexible or inclusive approaches to assessing creditworthiness do not inherently result in riskier credit markets. The United States’ household debt exceeds $18.39 trillion,³⁰⁴ far surpassing Germany ($2.4 trillion),³⁰⁵ the Netherlands ($1.2 trillion),³⁰⁶ Spain ($0.8 trillion),³⁰⁷ France ($2.3 trillion),³⁰⁸ and Japan ($2.7 trillion).³⁰⁹ And in 2022, over 77% of American households carried debt, ³¹⁰ compared with approximately 40%–60% in most of these countries around the same period. ³¹¹ Perhaps the size of U. S. credit markets warrants more conservative credit allocation. Yet, despite more inclusive creditworthiness systems, the comparator countries often exhibit lower default rates in key credit markets, including residential mortgages.³¹² This indicates that a presumption of creditworthiness is not inherently flawed.

To be sure, these cross-national comparisons are limited and invite further study due to the major differences in credit market size, household leverage, welfare state capacity, and cultural attitudes toward debt. Nonetheless, they hint at possible policy levers: By decoupling credit access from rigid scoring systems and pairing it with prudent underwriting or structural supports, the United States might reduce the exclusionary effects of its current system without necessarily increasing credit risk.

* * *

In sum, the United States largely accepts the burden placed on consumers to prove their creditworthiness upon entering the marketplace as a default framework within which it must tinker at the edges to make it more effective. However, examples from several countries illustrate that this burdensome framework is not a foregone requirement, but a policy choice. Despite the arguably more inclusive approach to credit scoring, most of these countries boast better debt default rates in some consumer credit categories than the United States. Certainly, cultural norms and complimentary policy choices such as social safety nets facilitate their approach to credit scoring. But this is precisely the point. Legal and policy choices that dictate the contours of consumer access to credit markets define creditworthiness.³¹³ And there are strong efficiency and equity reasons informing why U.S. policymakers should consider a presumption of creditworthiness to reduce the current barriers that unscored consumers face.

C. The Case for a Presumption

Policymakers pushed the credit score as a “cheaper and more just measure of creditworthiness.”³¹⁴ Specifically, credit scoring promised to improve the “speed, accuracy, and consistency” of creditworthiness determinations “while reducing costs.”³¹⁵ Yet, the existence of unscored consumers reveals that this promise of efficiency and equity in credit scoring has not been fully realized. A presumption of creditworthiness would better optimize the system’s core purposes by resolving the credit score conundrum.

1. The Efficiency Case

In the allocative sense of efficiency,³¹⁶ a credit scoring system should function to facilitate credit flows in a manner that serves three goals: (1) maximize the productive use of credit, (2) match consumers with credit terms that reflect—but do not exacerbate—their default risks, and (3) prioritize consumers most likely to repay. Presuming creditworthiness at the outset would serve all three goals. Under such a presumption, each consumer’s introductory credit product would be offered on favorable terms based on only objective indicators of their ability to repay. This maximizes the productive use of credit in several ways.

First, it would eliminate the current pressure for consumers to hoard credit merely to build a credit score, even when they do not need it. To be sure, unused credit can serve as emergency liquidity on reserve for unexpected expenses. However, unused credit optimizes credit utilization rates and extends credit histories to build credit scores without active credit use.³¹⁷ Consequently, innumerable personal finance experts encourage consumers to open credit accounts as early as possible,³¹⁸ steadily increase credit lines,³¹⁹ and hoard unused credit so as to game the credit scoring system.³²⁰ As of March 2025, unused credit card lines were valued at approximately $4.8 trillion, a record high.³²¹ Such unused credit remains a liability for lenders, likely constraining the supply of credit to meet more immediate consumer demands.

By removing the incentive for premature or excessive credit hoarding, a presumption of creditworthiness would allow lenders to reallocate the excess supply of credit to consumers with more productive—consumptive or investment-oriented—needs for such credit. Such a reallocation would help offset increased demand when once-unscored consumers enter the credit market. Additionally, consumers would be less tempted to prematurely use credit and irresponsibly incur costly debt simply to build a credit history, ³²² mitigating their risk of experiencing the many financial perils oft associated with debt.

Second, a presumption of creditworthiness would expand access to home mortgages and small business loans for many of the over 32 million unscored consumers currently foreclosed from those markets. Approximately 20% of middle-income consumers and 10% of upper-income consumers are unscored.³²³ These consumers may have the means to repay loans according to their income levels and cash savings but being unscored automatically deems them uncreditworthy. And even for low-to-moderate income consumers who are unscored, a presumption would facilitate access to existing homeownership subsidy programs designed to overcome their income gaps.

In doing so, unscored consumers could access both homeownership’s built-in savings and wealth accumulation. Over the last decade, homeowners across income levels accumulated $98,000 to $150,000 in wealth through their home’s appreciated value.³²⁴ In the most expensive metropolitan areas, low-income homeowners were among those seeing the greatest gains.³²⁵ Such private savings for unscored consumers could meaningfully enhance their financial stability. Similarly, expanding access to small business ownership would generate income, create jobs, and stimulate macroeconomic growth, potentially alleviating pressures on the social safety net.³²⁶ Even for credit used for consumption, which many observers view as a potentially risky and unproductive use of credit,³²⁷ a presumption of creditworthiness would have efficiency benefits. Unscored consumers would be able to access mainstream credit, rather than resort to high-cost, high-risk fringe credit products that worsen financial outcomes over time.

Third, a presumption of creditworthiness would better align consumers with loan terms that do not unduly exacerbate their default risks. Studies have shown that credit terms like high interest rates and balloon repayments, rather than past credit behavior, drive consumer default risks.³²⁸ In other words, high-risk terms beget high-risk defaults. Many consumers may not have poor credit scores had they not been subject to high-risk introductory credit terms that set them up to fail. A presumption of creditworthiness would ensure that all consumers’ entry into the market would be marked by favorable terms that mitigate their default risks. In turn, any future nonpayment or other default would, rather than reflect the predictable pitfalls of unfavorable terms, more accurately signal the consumer’s creditworthiness. Over time, this would allow lenders to allocate and price credit more efficiently based on actual, rather than contrived, creditworthiness.

For lenders, a presumption of creditworthiness would help maximize profits and encourage prioritizing consumers who are likely to repay. A key insight that has emerged from recent innovations is that a significant portion of unscored consumers are creditworthy. Recall, recent studies suggest that nearly half of first-time market entrants are at least “fair” credit risks,³²⁹and some may even be “very good” credit risks. ³³⁰ In other words, approximately 16 million unscored consumers may be untapped profit potential for lenders relying on traditional credit scores.³³¹ Moreover, FICO data suggests that these consumers are likely to increase their credit scores over time, thus promising long-term returns for many lenders who form the first-time credit relationship with these consumers.³³² By opening the market to all unscored consumers under a presumption of creditworthiness, these consumers would gain credit access without needing to rely on costly alternative data. Over time, the market would self-correct as those who build poor credit activity would be crowded out by consumers who effectively maintain their status and new market entrants, who are presumed creditworthy.

2. The Equity Case

Beyond serving efficiency, the credit scoring system should operate to maximize the number of consumers able to achieve and aspire to what it means to be a “full citizen” in the United States. Such a goal acknowledges how essential credit is to American life. Scholars have long documented the many ways that U.S. financial policy creates a “credit economy,” in which credit-based consumption is inextricably tied to well-being and belonging.³³³ American consumers not only depend on credit to meet their basic needs—food, shelter, and healthcare—but also to finance a sense of full citizenship through purchases of homes, secondary education, and other goods and services used within their communities.³³⁴ Consequently, scholars have advocated regulating credit markets through human rights and dignity frameworks to ensure consumers have adequate access to credit to meet these needs.³³⁵ While these frameworks are often invoked to advocate for broader credit access or more generous debt relief, they are rarely invoked to interrogate the credit scoring system that gatekeeps the entire market.

Being unscored makes consumers’ marginalized status in American society more acute. In the United States, having a high credit score is often viewed as an earned badge of respectability and responsibility.³³⁶ The credit score thus serves more than an economic purpose; it performs a social purpose to signal deserving citizenship and stratify social status. This social purpose explains why employers, with whom a credit relationship is non-existent (if not reversed), look at credit reports—employers assume credit scores track social responsibility.³³⁷ Even dating websites are incorporating credit scores to weed out undesirable singles.³³⁸ Consequently, unscored consumers navigate American society effectively bearing a scarlet letter that justifies subordinating them in both market and interpersonal contexts, thereby inhibiting their ability to realize a dignified status in society.

A presumption of creditworthiness, thus, offers two benefits: (1) a credit score that signals belonging and deserved access to the full range of citizenship and (2) a credit score that finances such access at the lowest cost.

First, all consumers would enjoy the benefit of the doubt to prevent social judgment and subordination based primarily on a lack of credit use tied to resources, culture, age, or need rather than irresponsibility. U.S. consumers would no longer need informal advantages—such as piggybacking off credit-savvy parents as authorized users, attending colleges or universities for student credit card benefits, or living in a neighborhood where the demographics are largely high-score consumers. Similarly, immigrants who lack a U.S. credit history, whether naturalized citizens or residents, would no longer be reduced to second-class members of society.³³⁹ In other words, privileged access points to build a credit score would no longer define the dividing line between so-called good, responsible consumers and bad, irresponsible consumers. Unlike current market efforts that undermine privacy rights or obscure heightened risks of discrimination, a presumption of creditworthiness does not require unscored consumers to sacrifice one human dignity to earn another.³⁴⁰

Second, a presumption of creditworthiness would create an equitable on-ramp to the credit markets on fairer terms for all consumers. No longer would select consumers be first relegated to high-risk credit terms or the high-cost fringe market that are designed for default. The extractive debt servicing fees associated with such credit products could be reallocated to cover living expenses and alleviate financial strain. In turn, the current tension between credit that supports well-being and debt that exacerbates subordination, documented by some scholars, could be mitigated. ³⁴¹

3. Potential Drawbacks & Responses

Notwithstanding the foregoing efficiency and equity gains, a presumption of creditworthiness is not without costs. It may raise concerns about potential spikes in defaults and lender losses, over-indebtedness, or credit market contractions. However, as discussed below, the broad-reaching benefits likely outweigh these potential costs.

a. Default Risks

A presumption of creditworthiness would inevitably extend favorable first-time credit to some unscored consumers who might otherwise be deemed uncreditworthy. Thus, a first-order question becomes: Who should bear the cost of heightened risk? Indiscriminate access may expose lenders to increased defaults, with potential costs passed on to the broader market.

Yet this fear of default risks should not be overstated. When unscored consumers enter the credit market, there is no strong evidence that they will default, and in fact, the odds that they will repay their debt are in their favor.³⁴² Moreover, any costs may be mitigated by the efficiencies created in reducing the percentage of borrowers who build poor credit histories, improving outcomes over time. Any balance of costs could be significantly offset by the long-term efficiencies, job creation, and wealth generation that a presumption of creditworthiness promises.³⁴³

Notwithstanding, there are several ways to think about the costs of potential increases in default. First, lenders may view them as a long-term investment in future consumers, much like offering low-margin introductory financial products to recent college grads in hopes that they eventually “graduate” to more profitable credit products. That way, a presumption of creditworthiness serves the long-term value of firms or, at the very least, their reputational value. Second, they may be viewed as a necessary cost of doing business, justified by the sometimes explicit and sometimes implicit guarantees of the federal government. Under this view, akin to the priorities reflected in banking regulations like the Community Reinvestment Act,³⁴⁴ a presumption of creditworthiness is a necessary social good, one whose cost must be borne by lenders, particularly depositary banking institutions, to maintain the privileges of their social contract. Alternatively, the social good may be understood such that the costs are borne by the government, from a public policy perspective, insofar as doing so would achieve bipartisan goals to expand access to credit and enable consumers to build credit scores while fostering greater financial stability.

b. Overindebtedness

Though a presumption of creditworthiness would broaden access to credit, which can be a social good, it would inevitably also broaden access to indebtedness, which can be a social harm. Recent scholarship has rightfully lamented the outsized role credit plays in the U.S. economy. From a public policy perspective, credit is routinely advanced as a substitute solution for a livable wage or the public provision of basic necessities.³⁴⁵ As a result, consumers find themselves increasingly dependent on credit, which puts a premium on already high costs of living.³⁴⁶ Such dependence often leads to a mountain of debt that avalanches into a valley of financial devastation.³⁴⁷ Thus, proposals to expand access to credit are often met with a consumer protection critique: What about the risks of over-indebtedness?

Access to credit should not be synonymous with access to unaffordable credit. Over-indebtedness does not arise merely from having credit but from having credit in an amount, at a cost, or on a repayment schedule that is unmanageable with a borrower’s other expenses. A presumption of creditworthiness, therefore, does not equate to a presumption of affordability. Evaluating income, assets, employment, and cash flow data remains a relatively objective method for establishing a manageable principal and repayment schedule. To be sure, such an evaluation means that some unscored consumers, like some scored consumers, will be denied credit due to insufficient or unstable income and assets. But for others, credit, whether in the form of a small-dollar loan or a home mortgage, can be a valuable tool through which even low-income consumers may benefit under right-sized terms.

c. Market Exit

Finally, there is a risk that the uncertain default costs associated with a presumption of creditworthiness might lead some lenders to exit the marketplace altogether. ³⁴⁸ If the default risks tied to the presumption are too high for lenders to manage profitably, fewer credit options may be available to consumers. This, in turn, could lead to even more extreme marginalization, not just of unscored consumers, but of those with low scores as well. Such critiques often paint a dystopian picture in which consumers are left at the mercy of mob-like loan sharks that break limbs as a penalty for non-payment.³⁴⁹ As such, proposals that impose costs on lenders must grapple with the “what if” scenario of lender exit.

As a point of comparison, this same critique was levied against the Military Lending Act (MLA), which caps the allowable interest rate for loans made to military members.³⁵⁰ Yet in the years following MLA’s passage, the predicted credit contraction did not result.³⁵¹ To the contrary, military personnel continue to enjoy access to a robust credit market without being subject to exorbitant rates.³⁵² The credit market adjusted. To be sure, absorbing the costs of 4.5 million military personnel and their dependents may be more manageable than doing so for the over 32 million unscored consumers.³⁵³ Still, by some estimates, the true cost burden of the unscored lies in the approximately 16 million individuals who may be high-risk borrowers.³⁵⁴ Their associated costs would be offset by the profit potential of lending to the other half of unscored consumers and could be absorbed by the market more broadly.³⁵⁵ And such absorption is feasible, as exemplified by the market’s capacity to absorb the high costs incurred by consumers who use rewards credit cards.³⁵⁶ But even more, the speculative concern of market exit may be reasonably addressed through government subsidies or other incentives designed to encourage lenders to adopt a creditworthiness presumption.

IV. Path to a Presumption

Though the benefits of a presumption may be clear, the path toward one in an economy that so doggedly believes in the merit of a credit score is complex. This Part first describes the law governing credit scoring, which currently does not offer solutions for unscored consumers. It then suggests three paths forward. It surfaces a rarely relied upon provision of the Equal Credit Opportunity Act (ECOA) to propose a lending program tailored to unscored consumers. It then explores an amendment to the ECOA that would ban creditors from discriminating on the basis of a consumer’s unscored status. Finally, it proposes a similar set of laws to be enacted in non-credit contexts that bar adverse decisions based on a consumer’s unscored status.

A. Legal Blind Spot

The primary regulations governing the credit scoring system are the Fair Credit Reporting Act (FCRA)³⁵⁷ and the Equal Credit Opportunity Act (ECOA).³⁵⁸ Enacted in response to widespread concerns about the potential harms of misinformation in credit scoring, the FCRA imposes specific duties on credit reporting agencies, reporting lenders, and other users to ensure the accuracy and transparency of information in credit reports.³⁵⁹ Specifically, the FCRA requires credit reporting agencies to implement procedures to reasonably ensure the accuracy of information included in credit reports and to safeguard reports from unauthorized use.³⁶⁰ If credit is denied based on a credit report (or score), the creditor must disclose its reason to the consumer,³⁶¹ and credit rating agencies must disclose the report details that underlie such adverse action upon the consumer’s request.³⁶² Additionally, consumers may dispute and have false data removed from their credit reports. To a limited extent, the FCRA also restricts the type of information that may be included in a credit report by barring the inclusion of non-financial medical information.³⁶³ If a credit reporting agency willfully fails to comply with the FCRA, it may be liable for limited statutory damages, punitive damages, and attorney fees.³⁶⁴

For its part, the ECOA prohibits denying credit on the basis of select protected class identities, including race, gender, age, or receipt of a public assistance.³⁶⁵ A creditor violates the ECOA upon a showing of either disparate treatment or disparate impact.³⁶⁶ The former involves discriminating against a particular consumer based on a protected identity,³⁶⁷ while the latter concerns facially neutral policies that disproportionately exclude members of a protected class without a legitimate business justification.³⁶⁸ Notwithstanding, the ECOA provides a limited exception intended as a reparative effort: Under certain conditions, lenders may establish “special purpose credit programs” to extend credit to marginalized groups who might not otherwise qualify for credit under traditional creditworthiness metrics.³⁶⁹

Recent legal actions underscore the continued importance of these laws in policing improper creditworthiness assessments by rating agencies and lenders. In 2021, TransUnion was found to have violated the FCRA after it added alerts to over 8,000 consumer credit files falsely flagging those consumers as probable terrorists, drug dealers, or other national security threats.³⁷⁰ Additionally, from January 2022 to February 2023, the Department of Justice settled five lawsuits against lenders accused of violating the ECOA for failing to lend to racial minorities, failing to establish branches in minority neighborhoods, or inexplicably charging racial minorities and women higher discretionary fees.³⁷¹

Notably, however, neither the FCRA nor the ECOA offers consumers protection when they lack a credit report or score. There is no duty imposed on credit rating agencies to generate reports or scores, nor any obligation on creditors to report tradelines. Moreover, being an unscored consumer is not a protected class identity, and there is no precedent that auto-denying credit based on a lack of score constitutes disparate impact under the ECOA. In fact, in some ECOA cases, credit scores are used to evidence (or refute) an adverse credit decision’s legitimacy.³⁷² As a result, unscored consumers have little legal recourse for the inefficiencies and inequities embedded in the credit scoring system.

B. Introductory SPCP

Despite its current failures, this existing legal framework is equipped to serve unscored consumers. The special purpose credit program (SPCP) is one legal mechanism that could be reimagined to facilitate a presumption of creditworthiness.

1. Special Purpose Credit Programs

For more than forty-five years,³⁷³ lenders have been federally authorized to issue credit under SPCPs based on otherwise prohibited considerations such as gender, race, or nationality. As a form of “affirmative action” in credit policy, SPCPs are designed to facilitate credit access for historically marginalized communities, notwithstanding the ECOA’s prohibition against considering protected class identities.³⁷⁴ To do so, the SPCP must either be: (1) explicitly authorized by federal or state law,³⁷⁵ (2) offered by a nonprofit organization to its customers or to an economically disadvantaged class of consumers,³⁷⁶ or (3) offered by a for-profit lender that implements a written plan meeting certain additional requirements. ³⁷⁷ Thus, a state, federal agency, or credit union may implement an SPCP without condition, while for-profit lenders like Chase or Bank of America must establish a qualifying written plan.

Such a written plan must satisfy four requirements. First, it must identify the underrepresented class of consumers the SPCP aims to benefit.³⁷⁸ This class can be defined by a shared financial need or common characteristic, such as race, gender, rural residency, or low-income residency.³⁷⁹ Second, the plan must detail why the SPCP is necessary.³⁸⁰ Lenders may satisfy this requirement by sharing their own or third-party data illustrating that the targeted consumer class systematically fails to obtain credit in the market and would otherwise be unable to obtain favorable credit under the lender’s existing underwriting standards. The lender may demonstrate this by tracking, for example, the basis on which consumers receive adverse decisions from the lender.³⁸¹ Notably, however, lenders may not collect demographic data prior to establishing the SPCP and must instead rely on demographic estimates to demonstrate need.

Third, the written plan must establish standards and procedures designed to increase the likelihood that consumers who would typically be denied credit are approved, and that those typically offered onerous terms are instead granted more favorable ones.³⁸² For example, the written plan may describe modifications to the lenders’ underwriting standards, requirements of a new credit product tailored to the targeted population, or adjustments to loan modification programs. The SPCP, once established, may condition credit access on otherwise prohibited demographic data only to the extent necessary to ensure consistency with the program’s defined class.³⁸³ However, lenders may not discriminate within the identified class—for example, an SPCP aimed at women may not offer disparate terms along racial lines.³⁸⁴ Fourth, the written plan must specify the SPCP’s duration.³⁸⁵ This may be a fixed termination date, a milestone for termination, or a date by which the lender will reevaluate to determine if the SPCP remains necessary.

Despite their promise and longstanding federal endorsement, SPCPs remain rarely implemented, especially by for-profit lenders. Some attribute this reluctance to legal uncertainty. One concern is that such programs run afoul of the Fair Housing Act (FHA),³⁸⁶ which prohibits discrimination in mortgage lending but, unlike the ECOA, does not have an SPCP carveout.³⁸⁷ Other lenders may fear inadvertently running afoul of the ECOA’s SPCP carveout,³⁸⁸ thereby exposing themselves to harsh penalties under federal and state anti-discrimination laws. In other words, to lenders, the risk of a technical failure in implementation would not be worth the benefit. In 2021 and 2022, federal regulators attempted to assuage these concerns through various interagency memos³⁸⁹ and advisory opinions³⁹⁰ that endorsed SPCPs and provided implementation guidance. While some lenders signaled more serious consideration, SPCPs remain woefully scarce.

This recent interest may prove short-lived—or at least significantly challenged—after a Supreme Court decision significantly curtailed affirmative action practices in college admissions.³⁹¹ Moreover, the Trump administration has aggressively pursued efforts to apply the Court’s reasoning to a broader array of federal agencies³⁹² and private sector activities³⁹³ designed to support marginalized groups. Nevertheless, because SPCPs are not required to be race-based, there is reason to believe they could withstand judicial scrutiny, even under the current Court and administration.

2. A Uniform Model Solution

A uniform model written plan for an introductory credit SPCP,³⁹⁴ approved by both the CFPB and the Department of Housing and Urban Development (HUD), may facilitate a presumption of creditworthiness. Unscored consumers form a clear, identifiable class of consumers who, as described in this Article, generally lack access to credit under most lenders’ typical underwriting practices. Moreover, unscored consumers are disproportionately low income and members of racial or ethnic minority groups,³⁹⁵ and thus, they have long, well-documented histories of the very discrimination in financial markets that the ECOA and other anti-discrimination laws were explicitly designed to address. Indeed, for many consumers, being unscored is a mere residual effect of such prohibited discrimination. Thus, targeting unscored consumers for reparative credit access through an SPCP is consistent with the carveout’s legislative purpose and satisfies the first requirement for a written plan.

To meet the second requirement, evidencing a documented need for the SPCP, lenders could combine the general market analysis provided in this Article with internal analyses of adverse decisions based on a consumer’s unscored status. However, relying solely on recorded adverse actions likely undercounts affected consumers, as some unscored consumers do not apply for credit out of a reasonable belief that they will be denied.³⁹⁶ Accordingly, lenders should also document the percentage of their applicants who are unscored. This way, lenders can show if unscored consumers are underrepresented in the applicant pool and track whether an increasing percentage of unscored consumers enter the market over time.

To satisfy this third requirement, the model written plan should outline clear standards and procedures that prioritize a consumer’s cash flow and assets. As a threshold matter, applicants for the introductory credit SPCP must be unscored consumers. Although a case could be made for a complementary SPCP aimed at rehabilitating low credit scores, the introductory credit SPCP this Article contemplates is not intended as a reset for consumers with existing credit scores. By focusing exclusively on the unscored, lenders target a small, fixed group of consumers and can alleviate fears of inadvertently violating anti-discrimination laws tied to protected class identities.

Another linchpin standard to this proposal is that unscored consumers must be required to demonstrate an ability to repay the loan provided under the SPCP. Lenders can assess this through proof of employment, income statements, deposit accounts, other asset holdings, or a cash flow analysis. This standard allows lenders to calibrate loan principal amounts and assess default risk primarily based on ability, rather than a willingness to repay. This therefore departs from the existing convention that holds ability and willingness as distinctly and equally important. By presuming first-time borrowers’ willingness, unscored consumers are freed from the conundrum of proving what they have never had the chance to demonstrate. Notably, this standard adopts the key virtue of alternative underwriting and enhanced scoring models—the incorporation of real-time financial data³⁹⁷—while limiting the privacy risks associated with disclosing more information to centralized credit rating agencies. Moreover, it avoids the heightened risks of bias likely to result from interpreting nonfinancial alternative data³⁹⁸ or reverting to the individualized character assessments of yesteryear.³⁹⁹ To ensure most unscored consumers are effectively served, the introductory credit SPCP should offer a mix of credit products, including small-dollar revolving credit accounts, auto loans, and home mortgages.

The standards and procedures should also model credit-market features that presume creditworthiness, including relational underwriting and blacklists.⁴⁰⁰ For instance, SPCP approval could be conditioned on opening a deposit account or using the lender’s financial advising services. Consumers could be denied credit only if they do not have the ability to repay or, if applicable, have a history of missed payments on recurring obligations like rent. Importantly, the mere existence of rent payments is not necessary for the loan; only negative payment history may be treated as indicative of an unwillingness to repay debts.

Further, the loan terms, including interest rates and payment schedules, should be consistent with terms typically offered to consumers with a “good” to “very good” credit score.⁴⁰¹ Such favorable terms recognize loan terms’ role in borrower defaults and limits such exogenous risks. Notwithstanding, these terms may be introductory, adjusting based on the credit score that develops for the consumer after a minimum twelve months. Doing so recognizes that the length of credit activity is a significant factor in signaling creditworthiness. This ensures an onramp to the mainstream credit market while allowing conventional terms to emerge that accurately reflect—rather than create—a consumer’s risks.

Finally, the duration of the introductory credit SPCP should be indefinite. There will always be new entrants to the credit market or individuals who have been out of the credit market for an extended period. Evidence of the SPCP’s success—that is, eliminating market barriers for unscored consumers—will merely affirm the SPCP’s ongoing necessity. Consequently, CFPB and HUD approval will be crucial.

C. ECOA Expansion

A presumption of creditworthiness may also be advanced by amending the ECOA to prohibit credit determinations solely based on unscored status. The ECOA has, as a policy matter, long prohibited creditors from considering certain factors, without regard to whether such factors may be correlated with heightened default risks. For example, the ECOA was initially implemented to protect against gender-based credit discrimination and prohibit lenders from considering an applicant’s likelihood of bearing or rearing children.⁴⁰² Yet, even today, the persistent gender income and wealth gap are partially attributable to declines in workforce participation and income disproportionately experienced after motherhood.⁴⁰³ Such income shortfalls can make debt repayment difficult, and thus, may create a credible concern for default risks. Notwithstanding, policymakers prohibit blanket discrimination against women as a class and motherhood as a choice in favor of more individualized financial assessments.⁴⁰⁴

Similarly, the ECOA protects unmarried couples that jointly apply for credit pursuant to its discrimination prohibition based on marital status.⁴⁰⁵ Prior to the ECOA, lenders believed marriage created “special legal ties” that granted lenders more legal remedies in the event of a default than they would enjoy against unmarried couples.⁴⁰⁶ Contemporary observers noted that debt servicing and enforcement costs may be objectively higher for unmarried joint applicants.⁴⁰⁷ Today, the risk of dissolution for unmarried couples is higher than for married couples.⁴⁰⁸ Such heightened costs and risks that income and assets will not be combined for long arguably create a credible concern of default risks. Still, the ECOA prohibits blanket discrimination against unmarried couples who jointly file credit applications. Similar analyses could be made with respect to the ECOA’s other protected class identities or the FCRA’s prohibition on the use of health information in credit reporting.⁴⁰⁹ Congress and the courts have elected to limit the bounds of purportedly rational credit decisionmaking to enable greater access to credit on an individualized basis. And there remains bipartisan support for legislative interventions to further improve credit scoring.⁴¹⁰

Unscored consumers should enjoy similar protections under the ECOA and the FCRA. Specifically, the ECOA should be amended to prohibit creditor practices that discriminate against consumers without a traditional credit score or a credit report sufficient to generate such a credit score. Though denying credit or charging a premium for being unscored provides lenders a low-cost screening mechanism, it is over-inclusive and inequitable in ways similar to credit determinations based on gender, marital status, or being a public assistance recipient. When a consumer is unscored, creditors should be compelled to rely on individualized financial factors like income, assets, and cash flow data until twelve months after the first credit score is generated.

D. Creditworthy Presumption Laws

Finally, to fully realize a presumption of creditworthiness, policymakers must address the ever-expanding reliance on credit scores and reports in noncredit markets. There have been scattered efforts at the state and municipal levels to limit using credit history in employment, insurance, and rental housing decisions. Ten states⁴¹¹ and some municipalities,⁴¹² including California⁴¹³ and New York City, have restricted employers’ use of credit reports in hiring decisions. Yet, despite a decades-long effort, such a ban has been unsuccessful at the federal level.⁴¹⁴ In the insurance context, progress has been even more limited. Only a handful of states have restricted the use of credit scores or history in insurance underwriting, and several merely prohibit basing adverse outcomes solely on credit history.⁴¹⁵ Notably, only two states prohibit using a consumer’s unscored status as the basis for an insurance decision.⁴¹⁶ The rental housing market has seen similarly modest reform. A seemingly infinitesimal number of municipalities have broadly prohibited using credit history in housing determinations.⁴¹⁷ The limited uptake of these efforts leaves most unscored consumers vulnerable to growing employment barriers and higher living costs.

Unscored consumers should be protected in these noncredit contexts from adverse decisions based solely on their lack of credit history. Accordingly, policymakers should enact creditworthy presumption laws, ideally at the federal level. Such laws should draw on the research supporting credit score bans in other contexts. For example, studies illustrate that poor credit history is a weak proxy for employee performance,⁴¹⁸ and employment rejections based on poor credit can exacerbate precarious financial conditions and further entrench poor credit history.⁴¹⁹ For unscored consumers, the proxy of no credit history is likely weaker and the harm, thus, more undue. Indeed, such adverse decisions, including in rental or insurance contexts, may punish consumers who exercise financial responsibility by not having credit without future income to support it.

Efforts to implement creditworthy presumption laws should withstand scrutiny better than credit score ban policies. Since they do not shield consumers who already have poor credit scores, critics who (albeit wrongfully) believe poor financial activity indicates poor behavior in other contexts may still rely on credit scores. In this way, credit presumption laws strike a fairer balance more likely to withstand political and legal scrutiny because they simply prevent penalizing consumers for the absence of a credit history.

* * *

By facilitating a presumption of creditworthiness through the foregoing proposals, policymakers would realize three key benefits. First, unscored consumers would gain meaningful access to credit, employment, low-cost services, and greater financial stability. Second, market actors—such as lenders and insurers—would benefit from an increasingly larger pool of potential consumers with “good” credit profiles. Third, all consumers would be incentivized to more prudently seek credit only when needed, no matter how late their entry into the market.

Conclusion

Credit scores are not merely a linchpin of mainstream credit markets—they are essential to full participation in a credit-based society. They unlock access to loans, housing, insurance, employment opportunities, wealth-building, and even community. Yet this system privileges some while excluding others. New market entrants must “earn” a credit score through mechanisms that create a class divide: the “haves,” who possess financial resources, education, or well-informed networks that grant them fair entry into the credit market, and the “have-nots,” who remain “unscored” and locked out of opportunity.

This Article undertakes the uncommon task of critiquing the credit scoring system’s underlying design. It implicitly contrasts the credit scoring system—which governs access to society’s essential privileges—with the criminal justice system, which protects access to its most basic rights. In the criminal context, the law has long recognized that the cost of mistakenly condemning the innocent is too great to bear. By contrast, in the credit context, no comparable principle shields unscored but creditworthy individuals from being misclassified as risky. In a credit-dependent economy, a system that errs on the side of exclusion proves itself both inefficient and inequitable, inflicting undue and enduring harms.

This Article makes three core contributions to the legal literature. First, it highlights international models that presume creditworthiness, illustrating that the U.S. approach is a policy choice—not an inevitability—and calling for a deeper comparative study to inform reform. Second, it grounds a presumption of creditworthiness in equity and efficiency, showing how the exclusion of unscored consumers—disproportionately drawn from already marginalized communities—undermines both. Finally, it surfaces an overlooked legal tool: the special purpose credit program, which offers a concrete path to reintegrate unscored consumers into mainstream credit markets and, along with other proposals, facilitates broader market inclusion. By shifting to a presumption of creditworthiness, this Article argues, lawmakers can better serve the credit scoring system’s underlying aims, unlocking full, fair, and efficient participation in the broader economy for all.

* Associate Professor of Law, Georgetown University Law Center. Many thanks to Gina-Gail Fletcher, Veronica Root-Martinez, Abhey Aneja, Dorothy Brown, William Buzbee, Julie Cohen, Christine Desan, Mechele Dickersen, Pamela Foohey, Nikolas Guggenberger, Luke Herrine, Eun Hee Hun, Filippo Lancieri, Patricia McCoy, Christopher Odinet, and Josh Teitelbaum. I would also like to thank the participants at the Money as Democratic Medium 2.0 Conference at Harvard Law, Sixth Annual Consumer Law Scholars Conference at Berkeley Law, 2024 Culp Colloquium at Harvard Law, and 2024 SEALS Annual Conference; and participants at faculty colloquia hosted by Georgetown Law, Miami Law, UNC Law, and Washington & Lee Law. Special thanks to Mia Ndalugi, Matthew Shang, Michael Miele, Jordan Artigas, Justin Dabre, and Nicolas Rosso for invaluable research assistance.