After a long period of pulling back, lenders are finally beginning to find value in financing small- and medium-sized businesses (SMBs).
But after years of finding SMBs too unprofitable to finance, lenders have to play catch-up to develop better underwriting processes for greater accuracy and efficiency.
“Increasingly, many lenders have been starting to focus on [SMBs] and lending to [SMBs],” said Gabriele Sabato, who holds a doctorate in finance and is CEO and co-founder of SMB loan underwriting firm Wiserfunding, in a recent interview with PYMNTS. “But at the same time, they have all lacked a credible tool to conduct an assessment of these [SMBs] in an independent way.”
SMB loan underwriting is complex, and with greater opportunity to wield alternative data to mitigate risk, lenders can also face the challenge of understanding how to collect information, how much weight to give it, and how to analyze that data in the context of broader economic trends.
This presents a gap in the market and an opportunity for FinTechs to fill it with automated underwriting technologies, like an automated small business credit score. As Sabato explained, the financial services market’s shift toward open banking and more sophisticated data analytics capabilities will continue to support lenders’ SMB finance operations — particularly in the months ahead as SMBs’ access to capital will prove critical to their survival.
From Bank Accounts To LinkedIn Profiles
SMBs are notoriously difficult to underwrite. Particularly when it comes to younger companies, a lack of credit history has lenders with limited traditional data upon which to base their lending decisions. This is why, increasingly, financiers have turned to mixing alternative data into their underwriting processes, with information from LinkedIn profiles and news reports now taken into account.
Gathering this information manually takes hours, however, said Sabato. Further, as financial institutions (FIs) develop their own methods for understanding which data points to weigh more heavily than others in accordance with their own risk appetites, their ability to internally develop risk assessment models can add a significant burden on resources.
“In a moment like this, investing in and building your own models, finding the data to bring to your models, finding expertise and skills to build and maintain your models — it’s all hard and expensive,” he said, adding that adoption of software-as-a-service (SaaS) risk assessment technologies is a cost-effective way lenders can strengthen their SMB underwriting processes.
Wiserfunding offers its SME Z-Score solution to automatically aggregate data across both traditional and alternative data sources in a way to offer standardization for lenders, either as a standalone underwriting tool or as a supplemental solution to validate their own underwriting processes. Collaborating with other lending-as-a-service technology players, as Wiserfunding has just done with Trade Ledger, also offers the opportunity to service lenders with a holistic, integrated offering to manage SMB lending operations, from underwriting to funds disbursement.
Expanding The Data Scope
As Sabato explained, open banking initiatives will help the SMB lending arena go even further to more accurately assess SMBs’ creditworthiness, with opportunities to connect into bank account data and third-party platforms like Xero and QuickBooks to accelerate underwriting.
“For the U.S., the next big thing that is coming is open banking,” he said, pointing to the ability to integrate directly into SMBs’ current accounts in real time. “We’re be able to source directly from current accounts and have an [SMB] risk score calculated on a daily basis — that’s really amazing.”
Artificial intelligence (AI) and natural language processing tools will also broaden the scope of the ability to aggregate and analyze alternative data. Sabato pointed to the ability for technology to identify images of certifications displayed on business websites as one example of innovation in the ability to capture unstructured data to strengthen underwriting.
These risk mitigation technologies are evolving at a crucial time for the SMB lending community, with coronavirus disruption threatening the survival of an untold number of SMBs.
The ability to not only aggregate data for analysis, but place that analysis in the context of current macroeconomic trends, is critical. In today’s volatile climate, Sabato said it will likely take underwriting models like Wiserfunding’s a few months to be able to adjust to the current state of the market. It’s why the company is hesitant to add a judgement feature to the SME Z-Score, instead encouraging lenders to examine the score objectively against their own risk appetites and needs.
Now, more than ever, lenders must support the SMB community, with underwriting a critical piece of strengthened SMB lending operations.
“If [SMBs] are better serviced, then they can grow faster, and that means everyone will benefit — especially after a period like the one we have ahead of us,” said Sabato. “[SMBs] are the only ones that can make us stand up again faster.”