In the wake of COVID-19, traditional lenders are being more conservative about the measure of risk in their investment portfolio. Small businesses innately address more risk than large organizations, making banks reluctant to loan to them.
Since most small businesses have limited or no credit history for a traditional score, they usually don’t qualify for a loan. While the specific reasons differ from lender to lenders and country to country, the one common thing is credit.
In the present scenario, three data trends may influence the small business lending landscape and provide lenders with meaningful information to help lend money responsibly across the world.
Leveraging Customer-Permissioned Financial Data to See Deep Critical Insights into business health:
Many traditional banks still use old-school methods of credit scoring and rely on historical data sets such as business history, revenue, and credit score to determine creditworthiness. This can make it challenging for entrepreneurs who have just started their new venture or businesses that have limited or poor credit history or are struggling with cash flow issues, to gain access to credit.
Besides traditional data, lenders are looking for additional information to help improve credit decision-making. In 2021, more and more lenders will use consumer-permissioned data to gain a better view of the overall financial health of a small business. This means borrowers provide access to the data from their various financial sources such as accounting, banking, financial, cash flow predictive software, and other accounts.
For example, some fintech companies like Codat, Validis, and ForwardAI provide real-time financial data APIs to lenders to access and use borrowers- permission data to facilitate small business lending.
Utilizing Alternative Data for Credit Risk Analysis
Alternative data has been transforming the lending industry for a while and its uses will continue to rise in the future. Lenders can collect and analyze alternative data on creditworthiness based on information readily available in the digitized form such as online rankings, utilities, and mobile phone data, social media and internet data, and more.
While traditional data such as credit score, business history, cash flow, profit and loss, sales, and bank accounts have its advantages, alternative data can help lenders to better understand their borrowers’ financial needs as well as determine their creditworthiness. Today, lenders will likely continue to try to find ways to utilize alternative data in their credit decisions, particularly those focused on undeserving small businesses. Depending on the above data points, lenders can get a better idea about the ability of a borrower to repay the loan amount.
Using ML and AI to Unlock the Predictive Power of Data
Before modern credit scoring, lenders relied on extensive documentation and manual processes to determine if an applicant is eligible for the loan. It was a complicated process and open to human error, and the information gathered was not complete and accurate. After the digitization in small business lending, scoring traditional FICO scores became easier, and more complex patterns could be evaluated, which boosted predictive power. AI and ML-based systems were able to evaluate more complex data easily and quickly and with fewer errors.
Today, in addition to historical data, more and more forward-looking data is being gathered, analyzed, and transported by FinTech companies with the help of AI and ML. Lenders can access and use this data through APIs to determine creditworthiness and reduce risks. With forward-looking data, lenders can accurately predict the financial future of a business - their income, expense, and spending behavior to make data-informed lending decisions.
While the small business lending industry continues to shift globally, improving credit scoring methods, providing easy and fast funding, and better determining borrowers’ creditworthiness can help you stay ahead of the competition and take your financial institution ahead. Increased consumer credit score awareness combined with the greater availability of the most robust and real-time financial and predictive data to improve credit decisions, may help lenders, better manage the road ahead.
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