Can Big Data Make Small Business Lending Profitable?

Technology has made everything from filling out tax forms to buying groceries quicker and easier. You can invest for your retirement online. You can buy health insurance online. You can find out if you qualify for a mortgage online.

 

Can technology do for small business lending what it’s done for the rest of the financial world? Can big data help regional and community banks make small business lending profitable? Increasingly – and perhaps surprisingly – the answer is yes.


 

Historically, origination costs for small business loans have been too high, relative to the revenue generated, to make them a profit center. Oliver Wyman estimates underwriting a smaller commercial loan costs a marginal $1600 – $3200 per loan – when those loans only generate an estimated $700 to $3500 interest per loan according to SBA.gov for loans under $50K.  Of course, small and mid-size banks exist to serve their communities as well as turn a profit – but they’re not charities either.  The good news is, big data is cracking the code of small business lending, improving efficiency and profitability. More good news: harnessing big data’s benefits is no longer exclusive to top-tier banks with huge IT departments.

Big data’s value starts with more efficient data-gathering in the loan application and approval processes. Automation can’t replace the good judgment of a loan officer, of course, but it can make the more mundane aspects of the job easier. According to one lender, Excelsior Growth Fund, 30 to 40% of a loan officer’s time is consumed reviewing loan applications that are clear no’s. An online loan application combined with big data can help that loan officer get to those no’s faster, freeing up time for higher-value work. In fact, automation can reduce both cost and time of the entire loan-making process, from analyzing the initial application to tracking loan performance.


 

“…big data is cracking the code of small business lending, improving efficiency and profitability.”


 

Lowering loan origination and servicing costs is an important step towards profitability, but the promise of big data is even bigger. Automating the lending process means capturing crucial data throughout the loan’s entire lifetime. That means making better decisions at every stage.

 

Take restaurants. It’s common knowledge in the banking world that restaurant loans are risky. But can you back up that gut instinct with data? Can you reliably tell a restaurant loan likely to fail from a loan that’s a good bet? Big data can augment traditional loan data-gathering to give lenders a more complete borrower picture. Additional data, such as rave reviews on Yelp and local media and strong social media savvy, can be very illuminating of a borrower’s creditworthiness. Thanks to technology, gathering enhanced data takes no extra effort at all.

 

Every community is different. What works in Peoria might not fly in Poughkeepsie. Gathering data on the success and failure of your actual loan portfolio will help you better understand what kinds of loans are succeeding in your area, and what kinds of loans tend to run into trouble. It’ll help you identify early warning signs in loans that could be heading south.

 

Big data can even enable topline revenue growth with risk-based pricing. Currently banks extend the same pricing to all accepted loans. Alternative lenders charge much higher prices for mostly edge-case loans. Using big data, traditional lenders can close this gap with loan pricing that reflects the borrower’s risk profile and grounds these risk decisions in data. It’s more affordable to borrowers compared to alternative lenders, and it’s more profitable to banks.

 

Even 20 years ago, collecting and analyzing this kind of data would have been impossible. These days, it’s easy. Yes, big data can make small business lending more profitable–and it can also make the process faster and easier.

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