The credit analyst staffing conundrum

Community banks, especially in more rural areas, face a significant staffing challenge. Credit analysts can be hard to come by. The more sparsely populated the area, the more difficult the hunt can be..Banks don’t have the option to opt out of the hunt for great analysts, either. Credit analysts play a critical role for the bank. Lending is a primary driver of bank revenue and loans to small and medium businesses, more specifically, are often the biggest loans community banks are making. This means having credit analysts devoted to commercial lending is key.While it can be challenging to find credit analysts, technology can help fill the gap and help smaller banks succeed, even in the face of talent shortages.Staffing challengesIt’s a tale as old as time for many community banks. They hire a credit analyst, many times with the hopes of them moving up in the bank one day. They spend time getting them trained, which can be a long process, especially if the bank is small and there are only one or two credit analysts total. Training a new person takes up their already busy schedule, which can mean less productivity while they are getting the new analyst up to speed. Once the new analyst is trained and has any certifications, it’s often not long before they move on. They become an attractive hire for bigger banks, as they are already trained and they can use their experience to find a position with better pay or more opportunities. This leaves the bank right back at square one.Remote work has, in many ways, opened up the talent pool for some of these banks, allowing them to find talent outside of their small communities. On the other hand, it has also opened up the job pool for credit analysts looking to move up. So the community bank’s challenges persist.AI can helpThe phrase “AI can help” probably has a lot of bankers rolling their eyes. For years, there have been concerns across industries about how AI can take jobs from human workers. While AI cannot — and should not — replace credit analysts altogether, it can significantly expand their capacity.In commercial lending, AI can eliminate many of the manual tasks that drain a credit analyst’s time. Most analysts spend hours, even days, reading documents and finding the data they need. AI can extract necessary financial information and complete time-consuming data entry in a matter of minutes or hours, rather than days.AI can then use that information to spread the financials and make a credit decision. This is a process that usually takes an analyst days to complete. However, with AI, analysts can arrive at a credit decision in a matter of hours. Most banks spend days working on a loan application only to reach a rejection for that borrower. AI helps make the decisions faster so banks can find more borrowers to approve.Another place where analysts spend a lot of their time is generating credit memos or other financial documents the bank may need. This is another area where AI can step in and automatically generate documents. This, again, gives existing analysts more time to do work that needs a human touch.This is critical for the banks that cannot find enough humans to do the work, but still need the job done. For smaller banks, their one or two credit analysts go from being overworked to being high-performers. Their time is freed up to do more meaningful work on the borrower relationship, rather than data entry. Banks cannot afford to overlook how this can promote retention, as well.Freedom Bank’s experienceFreedom Bank was using two different platforms for credit analysis. Excel and a separate underwriting platform. Using two different systems proved to be inefficient and even caused inconsistencies for the bank, so leadership began searching for a better way.In its search, the bank found Vine and began using the platform in February, which it has already seen results from.Vine’s AI-powered document reading has helped the Freedom Bank team be more efficient by removing the need for tedious data entry. Each lender now has a consistent output, which has streamlined the bank’s credit approval process.“The flexibility of the platform has been a huge plus for us,” said Cameron Johnson, vice president at Freedom Bank. “The other underwriting platform that the bank was using was very rigid and had a pretty steep learning curve, which left us very dependent on our credit analysts to perform reviews. Vine has allowed our lenders to jump into credits and perform analysis without additional support, which allows us to be more efficient.”Even with the power of AI, Freedom Bank is not losing the human element of its business. Johnson also noted that the checks and balances within the platform provide the team with peace of mind when reviewing the outputs. AI is not replacing the analysts entirely, but removes the repetitive manual work while still allowing the team to check the quality of AI’s work. With the time saved, Freedom Bank’s lenders can focus on the customer relationships that make the bank successful.By implementing AI, banks can alleviate many of the staffing challenges they face, when it comes to credit analysts. While smaller banks may not be able to easily expand their teams, they can use AI to expand their team’s capacity.David Eads is CEO and cofounder of Vine, a commercial lending accelerator for banks and credit unions.