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Getting Small Business Loans Right – The Future Needs To Resemble The Past


by Rob Frohwein, CEO of Kabbage

Let’s be honest, most small businesses’ capital needs aren’t being met by today’s lenders. In fact, the bulk of commercial lenders don’t serve small businesses at all. Not because they don’t want to, but because they aren’t structured do so effectively or efficiently, and the cost-to-margin ratio isn’t favorable for smaller loans. What’s more, many risk-assessment measures are built on one-time snapshots of a business rather than the longer-term potential needed to provide ongoing capital to small businesses from delis to dry cleaners. As a result, small businesses have been left with little to no options to access the capital they need when they need it.

So, what’s the solution? For starters, the industry needs to take a more honest look at the small business, its owner and how the business is run on a day-to-day basis, rather than solely focusing on the lagging indicators such as dated tax returns or historical transactions. The solution lies in using real-time data to get back to the personal banking that lenders and businesses enjoyed many years ago.

It Takes a Village.

Decades ago, in small towns and communities across the U.S., banking was truly a relationship-based business. Lenders and loan recipients were neighbors; they knew each other’s families going back several generations and they worked within the same local economies. Banks gauged risk using first-hand, day-to-day knowledge – they understood how their clients’ businesses worked, knew who their customers were, and had a front-row seat from which they observed the ebb and flow of their businesses. Hyper-personalized lending was born. But as banking grew and scale was required, truly hyper-personalized lending died.

There’s a lot of reasons that growth in commercial lending left small businesses behind. The average-sized small business loan – sometimes as little as a few thousand dollars – is just too expensive for most commercial banks to acquire and service. Even at local banks, loan applications are anything but personal – they’re complex, time consuming, and rely on narrowly defined underwriting criteria that don’t account for a small business’s unique characteristics. Small businesses willing to “run the gauntlet” and apply for loans often wait weeks for a response, and all too often are denied– even from the institutions that hold their checking and savings accounts. The bottom line: if you’re lucky enough to exhibit the narrowly defined prerequisites, you might hear a “yes.”  If you don’t, b-bye.

Yet, small businesses’ needs aren’t going unmet because there’s a lack of interest in serving them. In fact, plenty of non-bank lenders have entered the market hoping to capture a piece of the pie, but they don’t solve the problem because, frankly, they’re not really different. They fail to leverage available data and technology to stay in touch and remain up-to-date on customers’ business performance and health. Instead, they employ old operating models that still rely on manual processes and assess risk with traditional methods, all cloaked as “new” and “alternative” because the application is online. But, there’s nothing disruptive about an online application. Sorry.

Data Delivers the Big Picture of Small Businesses.

To create a truly personal relationship with small business and tailor products and services accordingly, lenders need the daily, up-close and personal view into their customers’ businesses and industries that local bankers used to have. Long ago, those insights came from frequent chats with customers, neighbors and friends. Today, they can be gleaned from readily available data that can provide what I like to call “fingerprint” lending.

For example, lenders can learn about a small business’ customers’ satisfaction, and even the business owner’s character (one of the five C’s of credit) with data from the e-commerce platforms they use, their social media interactions with customers, and even the weight, frequency and destination of products they ship. Other types of data can give lenders insights into a business’s unique cash flow needs and competitive landscape. By employing previously untapped data and keeping it fresh through persistent connections, lenders gain a unique, up-to-the-minute understanding of the small business’ capital needs based on where they’ve been, where they are, and where they’re headed.

Personalization Gives SMBs a Competitive Edge .

So, while it may seem counter-intuitive, data and automation are the key to personalization at scale. Consider a Boston-based restaurant called Angelica’s. By reviewing up-to-the-minute data from the restaurant’s point of sale, supply company and reservation software, a lender can chart the business’s cash flow to pinpoint and plan for seasonality. Using that information, the lender can tailor loan repayment schedules and capital injection to meet the restaurant’s cyclical needs. Since the data input and review process is automated, it can scale easily to run similar analysis for hundreds, or thousands of restaurants or other businesses.

What’s more, by running comparative analysis of data from hundreds of similar businesses — perhaps those with the same location, size or industry — lenders can help inform customers’ decision making. For example, if a lender learns how much, on average, 30 similarly-sized Boston restaurants pay for monthly linen rentals, they can share that information with Angelica’s to help optimize its linen expenditures. That type of competitive intelligence is a unique value-add for SMBs.

Benefits for Customers and Lenders.

Both bankers and small businesses can benefit from fingerprint lending. Since the application process is fast, online and highly personalized, it levels the playing field by eliminating common loan-application roadblocks: time, distance from banks, fears of being declined, and ease of access. Overall, it provides a much better customer experience. It brings the loan process from the banker’s desk to the business owner’s kitchen table, where decisions are free from bias, and are purely based on the objective business data. Think about the opportunities to eliminate bias against the individual when all that a lender can see is the objective business. Maybe “looking a person in the eye” isn’t such a great thing.

For lenders, the automated, comprehensive approach lowers operational costs and the cost to acquire customers, savings that are passed on to the small business owner that lower their total cost of capital. Perhaps most importantly, though, are the deep, real-time insights giving lenders the ready-knowledge to regain the previously-lost one-to-one relationship with small businesses. Those advantages are the foundation of true interactive relationship-based banking, and allow for meaningful, responsible and scalable relationships that allow lenders to provide offerings suited to every small businesses’ needs, every time.

We Can’t Go Back but We Can Move in Real-Time.

Clearly, we can’t turn the clock back to the days of small town USA when all lenders knew all borrowers on a personal basis and scale was the thing used to weigh produce. But we can — and must — do better by small businesses when it comes to lending. Small business owners, because of their size, resources and often relatively short credit histories, have unique needs that aren’t being met by today’s lending models. The industry’s attempts at new approaches are laudable – but fall far short because they don’t measure the attributes that work best to discern a small business’s health yesterday, today and – where it matters – tomorrow. The future needs real-time data, allowing lenders to make the right decisions based on leading indicators, not lagging indicators. Let’s give our small businesses the fair shot they deserve by using real-time data to provide fingerprint lending.


In 2008, Rob Frohwein recognized that companies like eBay offered automated access to small business transaction data via APIs. Rob realized small businesses could simply share this data to allow underwriters to make better, faster credit decisions and provide a great user experience. He co-founded Kabbage in Atlanta, Georgia, to leverage the power of real-time data automation through technology.


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