Biz2Credit, an online lending marketplace and direct funding source for SMBs, views AI as a force multiplier for underwriting, pricing and portfolio management.
AI is especially effective for analyzing cash-flow data, which is crucial for SMB lending amid growing demand for alternative financing such as revenue-based models, Biz2Credit Chief Executive Rohit Arora says in the latest episode of the “FinAi Podcast.”
“In the case of revenue-based financing, the big difference is that it is based on your cash flow and a lot of small businesses are seasonal by nature,” he said.
"The idea there is that you are actually giving them access to credit where you can recalibrate those repayments. … By using AI, you can do better pricing on it.”
Most customers use open banking to connect their data directly to Biz2Credit’s AI-powered platform, which includes tools for underwriting, risk assessment and loan servicing, Arora said.
Biz2Credit has provided $8 billion to more than 200,000 businesses since its inception in 2007, with loans ranging from about $25,000 to $2 million, according to the company.
SMB funding volume in the United States increased 9.3% year over year in the second quarter, according to the company's Aug. 3 SMB financing report comprising internal and economic data.
Faster, smarter and more customized lending also is important given the economic challenges facing SMBs today, Arora said, highlighting recent pressures from higher interest rates and inflation.
“What happens in SMB lending, unlike mortgage lending in this country, is that SMB lending is benchmarked to the Fed rates and they're typically floating rates,” he said.
“So even if you have an existing small business loan or a line of credit, every time the Fed will increase the rate, the rate will go up.”
AI can help alleviate such challenges by providing deeper insights into businesses’ financial data, streamlining customer interactions and mitigating credit risk, he said.
Listen as Arora discusses the growing opportunities to deploy AI for SMB lending.
