In a significant shift in the lending landscape, financial institutions are increasingly turning to alternative data sources to enhance credit assessments and combat fraud. This approach aims to provide access to credit for a broader range of potential borrowers, particularly those who have traditionally been overlooked due to limited credit histories.
Reevaluating Credit Assessment Models
As federal agencies reduce funding for statistical programs and traditional credit bureau files become less comprehensive, banks and FinTech companies are finding new avenues for insights. According to Kyle Becker, Chief Financial and Risk Officer at Concora Credit, the integration of alternative data is proving invaluable. “We use a wide variety of credit bureau data as well as alternative data in making our credit decisions,” Becker shared during the August What’s Next in Payments series. “Alternative data is super useful because it allows you to maintain or reduce risk while also providing access to credit to more people.”
The credit assessment process is undergoing a transformation. Traditional models are being tested, and new sources of intelligence—such as cash flow underwriting and real-time fraud detection—are becoming essential to the decision-making process. This evolution goes beyond merely incorporating new data streams; it requires a fundamental rethinking of credit infrastructure and its implications for all stakeholders involved.
Unlocking the Potential of Alternative Data
Historically, credit bureau files served as the cornerstone of lending decisions. However, these conventional data sources often fail to capture the full picture of many consumers, particularly those with “thin” credit files or those who do not fit established categories. Becker emphasizes the importance of alternative data in providing a more holistic understanding of applicants. For instance, cash flow underwriting allows consumers to link their primary checking accounts, offering lenders a real-time view of income and expenses, which not only assesses repayment capability but also acts as a defense against fraud.
“There’s increasingly more access to these kinds of alternative data sets,” Becker noted. “If we talk about cash flow underwriting, you’ll get to see some information about real-time ability to pay bills. And that’s very, very useful on top of credit history, especially if it’s a thinner credit history.” This strategy can create a mutually beneficial scenario where lenders mitigate risk while extending credit to more individuals.
Despite the evident advantages of using alternative data, Becker points out that not all institutions are adopting the same strategies. The challenge lies in the quality and longevity of the data used; model degradation can compromise effectiveness over time. To address this, Concora Credit employs data science to continuously monitor its predictive models, ensuring they remain robust and relevant.
“The key is not just having access but knowing how to integrate and validate the data,” Becker explained. “Having digital expertise, strong data science capabilities, and scale has allowed us to leverage these alternative data sets effectively.” Concora Credit evaluates around a dozen new data sources each year, aiming to refine its processes continually.
Bringing new alternative data sources into operational use is a complex endeavor. Certain datasets are more beneficial at different points in the customer lifecycle, and institutions must weigh these factors against cost structures that can scale effectively. While underwriting and fraud prevention represent immediate opportunities, Becker believes the real potential of alternative data stretches across the entire customer journey.
“I’m a big believer that data science can help you everywhere,” he said. “For example, improving customer service is essential. People don’t wake up wanting to call their financial institution. The more you can use data science to understand why somebody’s calling and provide the right solution immediately, the happier they’ll be.”
At the core of Becker’s vision lies a layered approach to credit. Traditional bureau data serves as the foundation, while alternative data enhances this framework through insights gained from cash flow, digital behavior, and fraud analysis. “We often find one or two new data sources per year to add, layering them into our underwriting and fraud defenses, which continuously improves our offerings,” Becker stated. “This compounding effect allows us to provide more access to credit for individuals who typically would not qualify.”
While Becker acknowledges the enduring importance of traditional credit bureau data, he asserts that alternative data will play an increasingly pivotal role in the future of lending. The ongoing evolution of data usage within financial services reflects a broader trend toward inclusivity and risk management, setting the stage for a more equitable credit landscape.