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3 Ways Artificial Intelligence Will Impact Commercial Lending

May 15, 2017 Philip N Burgess Jr Princeton NJ

One could make the argument that hundreds of factors will determine whether a business will fail or succeed.

In an ideal world, commercial lenders would be able to measure all those variables and weigh them against each other to determine whether a credit applicant will be able to pay the loan back on time and in full.

Unfortunately, we're a long way off from that ideal world, but artificial intelligence (AI) may get us there. Here's how:

1. Economic Forecasting

While one loan applicant may run a restaurant, another may own a land site development company. Both applicants could have good business credit reports, but each compete in distinct industries. A restaurant's success partly depends on consumer culinary trends, while site developers rely on homeowners with stable, rising incomes.

For underwriters, knowledge of such economic factors could help them determine which businesses will be lucrative over the next few years. The challenge is, even economists have an incredibly difficult time predicting what will happen in the future, given that political conditions, trade relations and hundreds of other factors may change rapidly in just a short amount of time.

AI could provide lenders with the means to track those factors. Pulling data from consumer confidence studies, industry growth outlooks and other sources, an AI program could run formulas to determine whether a particular business will succeed.

AI could analyze economic factors to inform underwriters. AI could analyze economic factors to inform underwriters.

2. Expedited Lending

Every underwriter knows that it takes some time to fully assess a business's creditworthiness and financial prospects. Computers can perform complex calculations millions of times faster than the average person, and once those computers can actually think, they'll be able to draw conclusions as to whether an applicant should or should not receive credit for his or her business.

Simon Isaacs, chief broker at eBroker.com.au, wrote a piece for Fintech Business, asserting that AI "will likely dramatically increase both the speed and depth of loan-matching capabilities." We're talking about approving a loan within an hour of a business owner walking through the door.

3. Differentiating Factors

Although four site development businesses may compete in the same market and offer similar services, each one has a key differentiator. While one site developer may offer a lower price point, another may have a stonemason with 12 years of experience.

Essentially, while all these businesses may look the same at first glance, one may be more successful than its competitors based on what distinguishes it from the rest. An AI could analyze which factors homeowners look for a in site developer and predict which company will succeed based on those traits.

If macroeconomic indicators suggest more homeowners will want to connect to public sewage lines in the near future and a general contractor offers such services, that organization is likely to receive more business than competing organizations which do not specialize in sewage connections. As a result, the company in question will be financially stable, something creditors will take note of.

"Commercial lenders need to increase data accessibility before investing in AI."

How Do We Get There?

In order to identify a business's differentiating factors, AI will need access to a lot of internal information: the services offered, personnel skill levels, age of equipment, and innumerable other details. The same principle applies when analyzing macroeconomic variables, reviewing a business's loan application form, business plans and credit reports.

Why? The main benefit of machine learning - a subset of AI - is that it gets better as it's exposed to more data. Based on the accuracy of its predictions, it can deduce where it went wrong when running previous calculations and adjust those formulas to make better predictions.

Before commercial lenders build up machine learning and AI capabilities, they need to institute measures that increase data accessibility across their operations. Departments should be able to securely and freely share information with each other. Once they've established such flexibility, commercial lenders can begin investing in AI.

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