How alternative credit data works alongside credit scores

For decades, credit scores have been the gold standard for lenders. This data, typically from the three main credit reporting agencies (Transunion, Equifax, and Experian), is delivered in a convenient format—the traditional credit score–which most commonly ranges from 300 (poor) to 850 (very good).

However, credit scores are just one part of the picture. They do not consider other financial factors that impact the ability to repay loans, such as income or spending habits. As a result, some consumers have less access to credit. On the other hand, some seemingly creditworthy borrowers might be riskier than their scores indicate, leading lenders to offer loan terms that don’t consider the true risk of the borrower. 

Incorporating alternative credit data, such as income data and buy now pay later (BNPL) payments, alongside traditional credit scores, can provide a more holistic picture of a borrower’s finances. This approach can expand credit access to nearly 49 million US adults with thin or no credit history. For lenders, this can lead to more customers and reduced risk–even among prime or subprime borrowers. 

In this article, we’ll explore what alternative credit data is, how it differs from traditional credit scores, and how financial organizations can use these datasets to complement one another. 

What is alternative credit data?

Alternative credit data is financial information not typically reported to the three main credit reporting agencies that lenders can use when making lending decisions. This data is gathered with customer permission and can be analyzed to better understand their ability to repay a loan and set loan terms. 

Alternative data includes cash flow from rent payments, gig economy income, utility bill payments, BNPL payments, and more. Lenders can use this data in two ways:

• As attributes and insights to feed into their existing risk models, allowing for custom analysis and segmentation. 

• An alternative data score that provides a single, standardized metric to quickly assess borrower risk.

In both cases, alternative credit data can supplement traditional credit data to increase loan approval rates while keeping risk in check or spot hidden risk that traditional scores might miss.

Alternative credit data helps highlight:

• Income sources and stability: Regular paychecks from the same employer indicate reliability, while varied income streams (such as gig work, seasonal jobs, or freelance contracts) show additional earning capacity. The length of employment and frequency of payments also provide insight into overall stability.

• Spending patterns and financial behavior: Lenders can review recurring expenses, debt obligations, transaction data, and any signs of financial strain, such as late payments or repeated overdrafts.

• Savings and liquidity: A borrower’s ability to save, maintain emergency funds, and hold cash reserves reflects financial discipline and resilience. Adequate cash flow suggests they can cover investments, debt obligations, and distributions without relying on external financing.

• Debt-service coverage ratio (DSCR): This ratio measures how well a borrower’s operating income can cover debt obligations, helping lenders gauge repayment capacity.

Benefits of using alternative credit data and scores

Alternative data types can help lenders build a more complete borrower profile and complement traditional credit reports. Even FICO says alternative data can provide unique insights that complement conventional credit scores.

Adding alternative credit data to the mix offers useful benefits such as:

• Expanded access to credit: Alternative data helps people with thin or no credit history qualify for loans at fair rates and start building credit. 

• Improved decisioning in underwriting: Traditional credit scores are often updated monthly and can lag behind a borrower’s real financial state. Cash flow and account data provide a real-time view of income, spending, and liquidity for more precise decisions.

• Better borrower experiences: Open banking providers make it easy to access alternative data securely. Borrowers can link their financial accounts in seconds—no paperwork or manual uploads required—streamlining the application process.

Why are lenders turning to alternative credit data?

Many lenders are already turning to alternative credit data to make more informed lending decisions, including banks, hedge funds, and venture capital investors.

However, consumer lending organizations have the most to gain by capturing a fuller picture of borrowers’ ability to repay. They’re leaning on alternative data more now due to several factors: 

Better visibility into creditworthiness

Alternative data scores incorporate cash flow signals such as income consistency, bill and rent payments, and spending patterns. Instead of relying solely on lagging indicators from a credit report, lenders gain a more up-to-date, holistic view of an applicant’s financial health. This richer perspective helps lenders better differentiate between high- and low-risk borrowers.

More inclusive lending decisions

For “credit invisibles,” an alternative score built on reliable financial signals—like on-time rent or utility payments—can open the door to affordable credit. Even for borrowers with established credit scores, blending traditional and alternative data can result in fairer outcomes and more precise risk assessment.

A simpler path to adoption 

Historically, lenders interested in alternative data needed to manually integrate hundreds of attributes—such as transaction details, income flows, and liquidity ratios—into their underwriting models. That process can be costly and time-consuming. Cash flow underwriting removes that barrier by packaging cash flow insights into a standardized score or set of insights, making it easier for lenders to use without rebuilding models from scratch. Instead of reinventing their credit strategy, lenders use cash flow data alongside FICO or VantageScore and start making more informed decisions right away. 

This raises an important question—how can alternative scores complement, rather than replace, traditional credit data?

How alternative credit data works

Alternative data isn’t designed to replace traditional credit scores—it’s meant to enhance them. Credit reports remain the foundation for most lending decisions, but they can leave important details out. By combining the two, lenders can strengthen their underwriting and offer borrowers more competitive options. Here’s how they work: 

1. Data collection

With a borrower’s permission, lenders gather financial data that isn’t typically included in a credit report—such as cash flow. Instead of relying on manual uploads like bank statements or pay stubs, lenders can use an open banking data provider, which allows applicants to securely connect their bank and payroll accounts in seconds.

2. Consumer permissioning

Borrowers remain in control of what data is shared. They choose which accounts to connect, ensuring that only the relevant financial data is passed to the lender. This consumer-permissioned approach builds trust and removes friction for users. 

3. Data analysis

The raw data can be used as is or normalized and structured into a standardized score. AI and machine learning models evaluate key signals—such as income stability, spending patterns, liquidity, and debt obligations—to produce a single metric that’s easy for lenders to interpret.

4. Combining with underwriting

Finally, the alternative is used alongside the borrower’s traditional credit score. Lenders can weigh it equally, treat it as a supplemental signal, or use it to segment applicants into different risk tiers. For example, a borrower with a borderline FICO score but a strong alternative score may qualify for a better rate, or a borrower with a high credit score might have risk indicators that qualify them for a higher rate.

Alternative credit data use cases in lending

By supplementing traditional credit data, alternative credit data is already reshaping how lenders evaluate borrowers across the financial market, including: 

Auto lending: Second look for near-prime applicants

For borrowers on the margin between approval and denial, alternative credit data scores can tip the scale. By incorporating signals like steady income or consistent savings, lenders can distinguish between high- and low-risk applicants with similar credit scores. The result is more precise approvals and better pricing for borrowers who might otherwise face unfavorable lending terms.

Buy Now, Pay Later (BNPL): Assessing new-to-credit customers

BNPL continues to attract younger consumers who often lack deep credit histories. Alternative credit data scores allow lenders to evaluate these borrowers based on real-time cash flow and payment behavior rather than just their thin or non-existent credit files. This creates opportunities to extend short-term credit responsibly while managing repayment risk.

Unsecured lending: Revealing blind spots and unlocking access

Alternative credit data often helps expand access to credit by helping thin-file customers gain access to credit. However, it can also uncover risks that traditional credit reports miss. A borrower with a strong credit score might appear low-risk on paper but could be showing early warning signs in their day-to-day finances, such as declining balances, missed rent payments, or increased reliance on short-term credit.

By analyzing real-time cash flow, income consistency, and spending patterns, lenders can identify these subtle risk signals before they result in delinquency or default. It can also help lenders identify applicants who are capable of repayment but do not have a traditional credit score. This allows lenders to fine-tune loan terms, reduce charge-offs, and make more confident underwriting decisions.

See how Affirm uses Plaid to better understand its customers’ ability to pay.

Challenges for lenders when using alternative credit data

Many fintech companies rely on alternative credit scoring models to determine whether or not to extend credit to borrowers. However, there are challenges to the widespread adoption of alternative credit data. 

These include: 

• Regulatory and compliance implications: Alternative credit data use must align with consumer protection laws such as the Equal Credit Opportunity Act (ECOA) and the Fair Credit Reporting Act (FCRA). Lenders must ensure that any score derived from alternative credit data can be explained to regulators and consumers, and that decisioning models remain free from discrimination.

• Data quality and accuracy concerns: The accuracy of alternative credit data can vary. Some data sources may have errors or lead to misinterpretation.  

• Privacy and security concerns: Using cash flow data can present privacy concerns. Financial institutions must also make a plan to ensure privacy and security. Requiring customer permissioning can solve this challenge. 

• Operational readiness and integration requirements: Adding alternative credit data to the credit decisioning process can require system upgrades, new workflows, and staff training. Lenders must be ready to integrate new data streams into existing risk models without slowing down application processing times or adding friction for borrowers.

• Consumer education: For alternative credit data to gain mainstream acceptance, consumers must understand how their data is used, what benefits it provides, and what protections are in place. Lenders need to clearly explain how data sharing works, obtain informed consent, and provide ongoing transparency to build trust with borrowers.

These challenges highlight the importance of working with the right partners when adopting alternative credit data solutions.

Getting started

Adopting alternative credit data scores doesn’t have to mean overhauling your entire credit strategy. Lenders can take a phased approach to test, validate, and scale these insights in a way that supports both business goals and compliance requirements. Here are some practical steps:

Evaluate and select a pilot use case

Start small by identifying a segment where traditional credit scores leave gaps—for example, thin-file borrowers, gig workers, or near-prime applicants. Piloting with a targeted population makes it easier to measure the impact and build confidence internally.

Establish clear evaluation criteria

Define the metrics you’ll use to assess success—such as approval rate lift, portfolio performance, or borrower satisfaction. This ensures you can compare alternative credit data outcomes against traditional approaches.

Integrate scores into existing risk models

Instead of replacing your current models, layer alternative credit data scores alongside them. Many lenders start by using these scores as a secondary signal for borderline cases, or by running them in parallel to validate predictive power.

Plan for compliance and transparency

Work with legal and compliance teams early to ensure your use of alternative credit data aligns with ECOA and FCRA requirements. Be ready to explain score inputs to both regulators and borrowers, reinforcing trust through transparency.

Leverage the right partners for data access

Partnering with Plaid makes it simple to securely access consumer-permissioned cash flow data at scale. With Plaid Link, borrowers can connect their financial accounts in seconds—a trusted flow already used by 1 in 2 U.S. bank account holders—helping lenders access the data they need without adding friction to the application process.

Alternative credit data expands financial access and equity

Younger and lower-income individuals are much less likely to have a credit score or a favorable credit report than their older or higher-income counterparts. However, that does not make them less likely to have a steady income and pay their bills on time. Using alternative credit data can help close these age and income-related gaps in financial access and equity, all while creating new business opportunities in the lending industry. 

The benefits of alternative credit data for lending are clear: Lenders get a wider pool and make better-informed decisions without compromising their risk profiles; applicants get more loan options at better rates, and individuals excluded from traditional credit scoring get their fair chance.

Learn about credit solutions, including Plaid LendScore, that can help you use alternative credit data to power smarter credit decisions. Plaid’s credit products and solutions are provided by Plaid Check, a Consumer Reporting Agency (CRA).