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Machine Learning Is Giving Small Businesses a Fairer Shot at Financing

4 min read • Jan 31, 2019 • Lendio

Porters Bar & Grill in Boston has been a favorite among concert-goers and sports fans for nearly two decades. But the business nearly shuttered in 2017 as the effect of waning cash flow during the slow season took its toll. Traditional lenders—even the bank Porters uses—took months to review loan applications and eventually declined them.

By their nature, small businesses have small capital needs and often don’t have the cushion to carry them through a months’-long traditional loan process. It’s surprising then that in an economy comprised of 99.9 percent small businesses, we still have a banking system that isn’t set up to meet these entrepreneurs’ needs. But thanks to improvements in technology and new ways of using data, more entrepreneurs are getting the funds they need, when they need them.

So far, the financial industry has only scratched the surface of what it can accomplish by harnessing data and using it in new and insightful ways, yet machine learning (ML) is already changing the game for small businesses like Porters. By automating as much of the process as possible and integrating technology at every touchpoint, online lenders can match businesses with the right financing for their needs in a matter of days, not months. For Porters, getting approved for financing through an online marketplace meant keeping the doors open until business picked up again—and continuing its nearly 20-year tradition as a popular watering hole for Boston event goers.

In today’s economy, artificial intelligence (AI) and ML touch all of us—from algorithms that answer your questions through internet searches to the content served up in your Facebook feed. And financial technology is no exception. Fintechs employ chatbots to augment customer interactions, they deploy AI aimed at identifying suspicious behavior and improving security, and they use machine learning to track spending and create budgets in consumer applications.

Lendio is one such fintech leading the charge in automation. The nation’s largest marketplace for small business loans, Lendio uses the big data available in today’s online ecosystem to give businesses like Porters a better chance at getting the funds they need, when they need them. The average size of a loan hovers around $35,000—a paltry sum when compared to a typical bank, where the average loan is closer to half a million dollars. Ten years ago, a business needing this size loan would have few options—perhaps a local bank or family friend. Now with ML at play, a lending marketplace can instantly match business owners with the lenders equipped to fit their needs. Instead of spending days or weeks filling out multiple applications, a business owner can spend 15 minutes completing one online application and then work with a dedicated funding manager to review loan options.

The Lendio platform uses 40 unique data points to determine which loan products are the best fit for a given applicant. By taking advantage of the information available, including credit score, monthly revenue, and time in business, Lendio has improved borrower acceptance rates by 20 percent.

Still, loan applications can be complex, and mistakes or omissions of key information often lengthen the application period. By automating the process for obtaining bank statements using optical character recognition, Lendio has reduced the amount of time elapsed between a business owners’ completed application and submission to the lender by four days, while also reducing the total time to funding by five days. In total, Lendio has shortened the average application period from more than three weeks to mere days. That’s a lifetime in the eyes of an entrepreneur and a far cry from the months it could take with a traditional bank.

Even so, the best data is no substitute for a solid relationship. Tech can only drive you so far, and customer service can’t take a back seat. Many companies are merging the best of tech and customer experience by finding ways to open brick-and-mortar locations that are bolstered by ML and AI. For instance, retailers have long used data to optimize sales strategies, and the industry is now using it to personalize the in-store experience. Particularly in the world of financial services, many customers feel more at ease with an in-person consultation. Lendio’s franchise locations allow small business owners to experience the best of both worlds—the familiarity of working face-to-face and the chance to access an array of loan products suited to their business.

Supporting the financial needs of entrepreneurs means small businesses like Porters remain sustainable. As both ML and AI advance, fintechs in the small business space and beyond will be able to serve a wider swath of customers, as well as provide a personalized experience that’s tailored to every customer’s unique needs.


Levi Lewis, VP of Product Strategy, Lendio

Levi Lewis has managed innovative product teams at multiple billion-dollar ecommerce companies. Dedicating his career to researching the science of decision-making, he has created several industry-first applications to help customers quickly and easily find products from major retailers. As VP of Product Strategy at Lendio, Lewis is committed to reducing the time and effort small business owners must invest to get and compare multiple loan offers and find the optimal fit for their needs.