HousingWire (Circ.: 439K) Bring Visibility to Credit Invisibles Through Alternative Financial Data

As the cost of living rises on a national scale, more and more consumers are looking for ways to live comfortable financially. While loans, in theory, may seem to be one obvious important solution, they are not as accessible to a growing number of Americans given a lack of sufficient, traditional credit history. According to recent analysis by the Consumer Financial Protection Bureau, there are 26 million "credit invisibles" who have no information on their credit reports and therefore, no credit score (translating to 10% of the total U.S. population). This group is made up of Millennials, low-income individuals, recent immigrants and mass-affluent individuals. In addition to “credit invisibles,” 19 million consumers do not have sufficient information on their credit reports in order to have a credit score generated. “Credit invisibles” are often overlooked based on perceived lack of credit worthiness; while in reality, there are various alternative financial data sources beyond credit reports that could inform a consumer’s reliability and ability to repay loans. In fact, many of these “credit invisibles” still have banking and non-credit product history that can be used to create a better risk assessment, which could lead to greater access to credit markets. Leveraging financial data sources, such as transactional level data from banking, investment and lending accounts, opens other doors to assessing risk, and tracking that ongoing risk during the life of the loan. Expanded applicant pool for pre-qualified leads Historically, lenders have identified pre-qualified leads for personal and mortgage loans by sending offers through various channels. This process can prove difficult as there is the potential for risk and lack of data by only referencing limited credit information. The issue is magnified when dealing with “credit invisibles,” who will be missed through traditional data sources. By integrating robust financial data into the lead qualification process, lenders can also generate higher quality leads and increase conversion rates for marketing programs. With a holistic view of a borrower’s financial profile, powered by granular-level transaction data, lenders can better target the right product to the right customer at the right time. An optimized underwriting process The traditional mortgage application with its statement-based verification processes are frustrating for consumers accustomed to streamlined online experiences from applications like Google Now and Amazon Pay. By using a consumer’s most recent bank, transaction, and investment data, lenders can improve the accuracy of critical credit risk measurements and streamline the underwriting process by reducing manual intervention and digitizing the process. Alternative financial data is particularly useful in the underwriting process for retail loan products, specifically collateralized loans that need clarification of down-payment funds in home mortgage and automobile financing. Specific insight regarding an applicant’s ability, stability and willingness to repay Arguably the most important component of determining risk level in loan consideration is an individual’s ability to repay. Additionally, lenders must factor in an applicant’s stability and willingness to repay the agreed upon loan. For “credit invisibles” who don’t have a credit score, lenders need to consider alternative financial information to assess their credit worthiness. The key types of data to analyze an individual’s ability to repay include: cash, investments and other assets; revolver or transactor status; home ownership and value; and cash flow metrics. The stability of a “credit invisible” is also critical for lenders to consider. Factors like how often an individual moves and validation of employment and income can speak much more clearly to an applicant’s stability than a traditional credit report does. In addition to sources such as home ownership and revolver or transactor status, applying advanced data analytics to an applicant’s payment history on non-credit items will help show how consistently obligations like rent, utilities and phone bills are paid. There is a clear opportunity for lenders to capitalize on the opportunity to identify credit invisible consumers who have no credit score, but are still credit worthy. Tapping into alternative financial data from “credit invisibles” can not only broaden an institution’s applicant pool, but also give lenders a more holistic view of their applicants, thus helping to improve risk assessment and approve more qualified customers.