Sunday, December 22, 2024

Data and Technology Help FinTechs Balance Inclusive and Responsible Lending

Access to credit – it’s needed to purchase a home, a car, go to school or start a business.  Yet, traditional ways of evaluating the creditworthiness of consumers for these transactions have some limitations. While traditional credit scores remain a reliable way for lenders to predict repayment risk, pairing the scores with other forms of data can provide a more comprehensive picture of a consumer’s ability and willingness to pay back a debt.

With credit balances trending up in every non-mortgage lending category since the pandemic, the demand for credit remains high. Unfortunately, based on anonymized Equifax data, delinquency rates are also trending up by as much as 26% from April of 2022, but still down from March of 2020. As wage gains struggle to keep pace with inflation, consumer spending power is diminished, leaving some with limited capacity to cover emergencies or even regular expenses. Just when borrowers need access to credit, the uncertainty about consumer financial health trends and recent high profile bank failures have some lenders pulling back and tightening their credit policies.

FinTechs have enjoyed explosive growth over the last decade by offering financial services that are faster, simpler, and more widely available. Access to credit is a fundamental value proposition for FinTechs – and their “secret sauce” includes alternative forms of consumer data that provide an expanded view of a borrower’s financial situation. The more complete perspective of consumer financial wherewithal allows lenders to extend more credit without taking on additional risk.

Few lenders are in a position to accept more risk, especially during periods of economic uncertainty. Private FinTech funding that reached a peak in 2021 has slowed according to

Crunchbase News April 2023 – The FinTech Funding Crunch in 4 Charts  leading to more scrutiny about profitability. The rapid rise in interest rates has not only throttled venture capital funding, but also threatens some of the FinTech business models that depended upon near-zero rates. The current macroeconomic environment has more FinTechs searching for a balance between inclusive and responsible lending – seeking a balanced path to profitability while expanding lending options.

Examples of alternative data that can help reveal profitable lending opportunities include employment and income information, payment records, and bank transactions. Payment data for telecom, utilities, and rental accounts provide valuable insights about a consumer’s history with regular payments, while employment and income data is a good leading indicator of a consumer’s financial capacity. A complete view of a consumer’s ability and willingness to pay, provides lenders with the insights they need to expand lending and help consumers when they need it most.

Technology advances are also making alternative data more accessible to qualified lenders. Equifax leverages cloud technologies to bring together innovation and investment to deliver better insights and outcomes for consumers. Lenders and service providers can obtain a traditional consumer credit score, as well as a one that layers additional data sources – helping consumers to get approved for more opportunities or to obtain the best possible rates. For FinTechs that prefer to develop custom decisioning models, advanced data analytic platforms facilitate alternative data ingestion, keying, and linking to a consumer or small business entity. Access to Fair Credit Reporting Act (FCRA) compliant information with the tools needed to associate the various types of data is the foundation for creating a more complete view of potential customers.

Building models and risk decisioning with alternative data can get complicated and expensive. To make data more usable, providers like Equifax, develop data attributes that can extract valuable insights from raw data to help predict future outcomes.  With access to thousands of data attributes across multiple data assets, model builders can test a variety of options to discover the most predictive combinations, or select preconfigured packages for simplicity. Other best practices, such as building waterfalls into decisioning trees or accessing multiple data elements via a single API, can also help boost results and create a better return on data investments. The same practices can also streamline processes and help reduce expenses.

Ultimately, the objective for FinTech lenders is to say yes more – responsibly, and with reduced risk. Underserved communities can represent opportunities for lenders that have the capability to assess risks more discreetly.  Adding alternative data can help identify unbanked or underbanked individuals that fall within a target risk profile. Technology innovations that result in broader access to alternative data are expanding opportunities for lenders and helping consumers reach their personal goals.

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