In the US, credit invisibles are finally on their way to financial inclusion. JPMorgan Chase, Wells Fargo, U.S. Bank, and seven other banks expect to launch a pilot program in 2022 that assesses creditworthiness based on alternative data sources. By looking at their banking histories―such as checking and savings account balances, returned checks, and overdraft usage―the 10 banks included in the pilot program are able to grant credit to those who need it.

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With the program, 45 million Americans without a credit record can now access more financial products and services. This new credit scoring model is instrumental to banks and other financial institutions looking to expand or improve their offerings.

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With the rise of alternative scoring, it is now possible to carry out a more complete and updated analysis of clients and potential clients through behaviour prediction. Alternative sources other than rent, open banking, and utility bill data include telco, psychometric, and behavioural data. These novel sources can all help predict movements and identify patterns of applicants’ willingness to pay, especially when combined. In this way, banks and financial institutions can reduce the risk of credit default, strengthening algorithms that previously were solely based on traditional and transactional data.

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Alternative data will play a key role in generating credit scores and growing the financial technology, or fintech, sector as more and more people seek credit for large-scale investments.

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What it means to credit invisibles

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Historically, applying for credit has been difficult to achieve, even more so for the underbanked - people with little or no opportunities to build their credit scores. These people typically consist of young adults who are just starting out and are trying to avoid banking fees or have yet to build their credit history simply because they prefer forms of payment other than credit cards. Others include immigrants who arrive without credit or can’t transfer their credit reports from their previous home country and people of colour who are disadvantaged by racial inequality in accessing financial services.

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These individuals cannot purchase productive assets such as a car or a house or build their wealth with their resources. Thus, access to credit plays an instrumental role in strengthening their financial power. However, the downside of the traditional credit scoring system is that it provides little to no opportunities for credit invisibles to prove themselves. Research shows that a vast majority of Latin Americans and African Americans want lenders to look at additional factors in lending decisions. According to Experian's State of Alternative Credit Data report, about 80% of borrowers expressed that consumers would likely share various types of financial information with lenders if it meant increased chances of approval or improved interest rates on credit.

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Digital technology can drive global financial inclusion by addressing the specific needs of distinct communities and developing strong fintech ecosystems. Integrate alternative data sources in credit scoring and lending processes to make financial services more accessible, allowing credit invisibles to build their credit history and scores. These sources include bills for utilities, telecommunications, and rent; alternative lending payments; and demand deposit account information such as recurring payroll deposits and payments. All of these are already part of people’s regular financial commitments.

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According to Experian’s 2020 State of Alternative Credit Data report, 96% of lenders believe that non-traditional data allows them to evaluate creditworthiness better and reduce risk during economic stress. This proves how instrumental alternative data is for lending. As a result, financial institutions can increase financial inclusion with this data while uncovering new lending opportunities for themselves.

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What it means to financial institutions

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Alternative data is just as beneficial to financial institutions. According to management consulting company Oliver Wyman, using alternative data sources can help lenders increase the number of profitable loans made in line with a given risk appetite. Lenders can also reduce transaction costs, lower aggregate credit losses for any cut-off defined by a marginal loss rate, and increase competitive interest rates.

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Of course, sifting through various alternative data sources requires considerable time, as not all sources are created equal. However, lenders can streamline this process with the help of technologies such as artificial intelligence, machine learning, deep learning, data analytics, and more.

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Credolab, for instance, provides embedded scoring technology that lenders can integrate into their systems to assess borrowers' creditworthiness more effectively. As a result, lenders can issue credit or loans faster and more efficiently. Furthermore, borrowers would no longer have to undergo tedious credit application processes. Additionally, credoSDK for mobile captures privacy-consented and permissioned digital footprints. Credolab’s proprietary scoring algorithm processes the metadata captured to calculate behavioural scores, flag potential fraud, and enhance marketing segmentations. Therefore, it can help lenders to identify fraudulent customers and the so-called “non-starters” early in the decision process and save them time and effort from approving the wrong people.

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In compliance with federal and data privacy laws, we use non-intrusive, privacy-consented and anonymous metadata to help businesses make better risk, fraud, and marketing decisions.

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More credit-worthy people will have access to the money they need to make important investments by improving the lending process. And when more credit or loans are issued to borrowers, economies will perform better. The role of alternative data goes beyond helping credit invisibles finally become visible. Financial institutions should take this as a sign to reimagine their processes and open up more opportunities for people to be financially included.

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