Fighting the SMB Funding Gap in Countries Worldwide
Originally published on Forbes.com.
Nick Chandi is the CEO of ForwardAI, which offers easy, versatile business data access and analysis for banks, lenders, and fintechs.
About 90% of businesses globally are small and medium-sized businesses (SMB). They account for 50% of employment worldwide and generate trillions annually. Despite significant contributions to the global economy, SMBs have an unmet financing need. Forty percent of micro, small and medium enterprises (MSMEs) found in developing countries need $5.2 trillion per year.
In most cases, a small business’s most common recourse is to go to a bank for a business loan, but how successful are SMBs in getting them? In December 2021, big banks approved 14.3% of SMB loan applications—about half their approval percentage before Covid-19 disrupted economies worldwide. Similarly, smaller banks generally approved over 50% of their loan requests pre-pandemic. Since then, their approvals have fallen to 20.1%.
While financial institutions have grown more conservative in approving loans, borrowers struggle to obtain loans because of insufficient traditional data. Lenders look at historical data like credit history and FICO scores to underwrite loans. They’re usually unwilling to bank on businesses that don’t meet their benchmarks. In fact, a 2021 survey found that 33% of borrowers feel discouraged about loan approval due to their low credit scores.
A laser-focus on traditional data also excludes huge swathes of the population. Some consumers and businesses just don’t use credit products. As many as 21% of U.S. consumers manage without a credit card and over 35% of Canadians are credit invisible. If these consumers were to apply for a loan, they would likely be rejected. Credit scoring would not give an accurate picture of their financial health. It also discourages potential borrowers from applying, particularly if they belong to minority communities. One in 4 black-owned businesses did not apply for credit, and 60% of them said it was because they believed they would be rejected.
This data shows that traditional data alone may not be enough to yield an accurate assessment about a potential borrower, or their ability to meet a payment schedule. By using automation technologies—like artificial intelligence (AI) and machine learning (ML)—and integrating broader datasets into the underwriting process, there is room to generate richer insights that appropriately reflect a business’s financial health, so lenders can make better lending decisions. Within this combination, there is great potential to successfully tackle the worldwide SMB funding gap.
AI and ML technologies have given rise to new industry tools like cloud-based loan origination systems (LOS), which have automated loan processes and workflows. They offer small-business customers an improved user experience, consolidated document management, advanced transparency and access, and speedy approvals. They also integrate with multiple accounting systems, which is paramount for SMB owners because they can transact with the lender/bank seamlessly.
For lenders, the benefits include cutting down on loan underwriting times because they automate the evaluation and screening processes, including collateral and asset analysis. They can also cross-reference applications for verification and derive accurate insights from variables, like past application histories and fraud risk, to compose comprehensive risk profiles for potential borrowers.
Lenders are also increasingly looking at nontraditional data like rent and utility payments, web data and social media to inform loan underwriting. Social media can produce useful insights from something as ordinary as review count to determine a volume trend to indicate sales growth or decline. Similarly, interaction trends can indicate the popularity of service and potential for growth.
As lenders pivot to nontraditional data, many have found a hero in accounting data. Accounting platforms hold all the key information about a business’s customers, suppliers, orders, revenue, profit and loss statements, and more. With APIs, lenders can plug directly into a small-business customer’s accounting platforms. By integrating into an SMB’s accounting system, lenders can have a look at the day-to-day, week-by-week changes across revenue, order volume, profit, loss and more to spot trends and deviations. This helps them come to a better determination about the business’s loan risk.
Having said that, these technologies rely on data from financial infrastructures that can vary in strength from country to country. Before new technologies can be embraced, there needs to be a certain threshold of digitization and standardization for alternative data to be of use to lenders. Consider that SMBs in less mature economies may not be using digital accounting systems at all. In such cases, regulators and policymakers need to play a role in encouraging the wider adoption of accounting systems and alternative data to level the playing field. As it is with most technological advances, it’s probably just a matter of time before that happens.
In mature economies, the scenario is a little different. Banks, payment networks and TPPs are employing open banking to access and share consumer financial data with each other. With borrower permission, lenders can utilize open banking technologies to connect to their borrowers’ accounting systems. They can then extract accounting data to incorporate into their underwriting process. In doing so, lenders streamline the loan process and cut costs, putting them in a better position to serve more SMB customers and edge out competitors.
In one study, cash flow problems accounted for 82% of SMB failures. For small-business customers, being approved for a loan could mean the difference between surviving payroll—or investing in inventory—and shuttering their doors. The global economy is too dependent on small businesses to watch them fail. Utilizing new technological advances and expanded datasets, lenders have more opportunities to reach SMBs and help them succeed.
Originally published on Forbes.com.
