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Without the right data, your bank could be turning away qualified borrowers

  • Using alternative data provides a more holistic view of a consumer's creditworthiness.
  • Financial services expert Gary Harvey explains how FIs can achieve this using the right data sets.
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Without the right data, your bank could be turning away qualified borrowers

With interest rates rising, there is growing pressure in the lending space to provide a seamless, positive customer experience that helps lenders earn and retain customers. Today, borrowers expect fast, low-friction lending options to be available to them, and with the market changing quickly, bankers need to be in a position to expand their lens of creditworthiness to capture more applicants.

Too often, bankers make lending decisions based on a limited view of an applicant’s financial circumstances, or ability to repay a loan, potentially leading them to decline borrowers whose more comprehensive financial picture may confirm they could be qualified, long-term customers.

The need for a more holistic view

Reviewing a loan applicant’s traditional credit report is an excellent place to start when determining creditworthiness. But bankers can achieve a more holistic view by layering credit report data with income and employment data. Accessing this expanded, cloud-based information and incorporating historic payroll insights into risk models can help financial institutions make more confident decisions and potentially lend to more applicants. In fact, including income and employment data can help nearly four million more consumers move to prime or super-prime classifications by helping to create a more complete and attractive financial picture that encourages lending.[1]

For years, bankers have relied on consumer-supplied data, including W-2 forms, stated income, and paper pay stubs. Still, they often could not guarantee that the information was authentic and not altered in any way by the applicant, or outdated even before it got to them.

Today that is changing, as information such as rental, telecom, and utility payment history is more readily and instantly available in the library of data that can help banks better evaluate a borrower’s true creditworthiness. This so-called “alternative” data better allows financial institutions to assess a customer’s propensity to repay through a wider lens, providing a more comprehensive view of their financial history as part of the bank’s decisioning process. Through access to deeper data sets, bankers that recognize prospective borrowers as more than just their credit score can develop a methodology to responsibly say ‘yes’ to qualified borrowers within currently underserved demographic groups. Using this alternative data throughout the loan decisioning process may help more members of the broader community take the next step in their credit journey.

By automating the process of accessing alternative data, bankers can also mitigate the risk that the data has been modified or changed by the applicant, or is outdated even before it gets to them. Credentialed verifiers with a permissible purpose can access secure income and employment data via third parties that are supplied directly from the source: the employers and payroll providers. Operationally, bankers gain efficiencies as this technology can help them evaluate many variables, thereby positioning bankers to more quickly make accurate and consistent lending decisions. Perhaps more importantly, automated and integrated data can help reduce the rate and number of false declines, which can negatively impact profitability and brand value.

Consider the entire loan life cycle

When evaluating growth opportunities in a changing market, bankers need a view of applicants throughout each stage of the loan life cycle, not just at application. Without this level of visibility, banks risk missing out on changes in an applicant’s financial situation over time, potentially limiting the opportunity to build a deeper relationship and grow their portfolio with that customer.

As bankers continue to invest in digital transformation, they must ensure that those investments extend beyond their customer-facing applications to transform the entire experience for the positive. By leveraging technology and data analytics to improve and streamline loan decisioning, banks can set themselves apart from the competition with their efficiency and potentially put themselves in a position to provide an optimized experience to even more customers.

Gary Harvey is an experienced entrepreneurial leader in the financial services, data management, and digital marketing verticals, providing a unique perspective on how to fuse consumer behaviors, alternative data, economic trends, and corporate priorities into insightful, monetized solutions.

The vast majority of Gary’s career has been with Equifax. Currently, Gary serves as Sales Director in the Consumer Finance vertical, specializing in the use of alternative data and verified income/employment solutions at many top financial institutions, insurers, brokerage firms, and telecoms.


[1] Based on assessments from Equifax Data & Analytics team, 2021

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