As AI accelerates underwriting and expands the data available to lenders, concerns over problem loans and weaker small-business lending are reinforcing the case for human judgement.
Artificial intelligence is moving deeper into commercial lending, promising faster decisions, broader data analysis and more consistent processing. But the latest thinking across the sector also points to a limit: the more AI can do, the more lenders need to decide which tasks should remain in human hands. That tension sits at the heart of Simply Asset Finance’s argument that technology should support, rather than supplant, lending judgement.
In its blog post, the company says AI is already helping lenders build a more detailed view of a business by drawing on open banking data, cash-flow information and transaction records alongside more traditional measures such as credit history, assets and profits. That wider lens can be especially useful for small and medium-sized companies, where funding requests are often urgent and delays can derail a purchase, stall a deal or slow expansion. Simply Asset Finance says its AI assistant, Kara, is designed to handle repetitive work such as extracting data, processing proposals, routing requests and carrying out due-diligence checks, leaving staff more time to deal directly with customers.
That approach matches a broader trend identified by industry analysts. Wolters Kluwer has argued that the democratisation of AI is lowering the barriers to adoption by making the technology more accessible and affordable, while also stressing the need for workflow integration, trustworthy data and human oversight. S&P Global Market Intelligence reported in July that the first wave of AI in lending delivered about a 20% productivity gain, with further improvements expected as lenders use it more widely across underwriting, data extraction and reconciliation. KPMG, meanwhile, has said AI is becoming mainstream in commercial lending, but only when it is embedded across front-, middle- and back-office processes with clear governance and controls.
Even so, the data tells only part of the story. Simply Asset Finance argues that a borrower’s context can be crucial, because a dip in cash flow may reflect investment in new equipment rather than distress, while a loan request may be driven by a well-judged growth opportunity rather than short-term pressure. That is why face-to-face conversations and regular contact still matter, particularly when a business is taking a calculated risk or aiming to enter a new market. The company’s own phrase, “Technology with a Handshake”, is meant to capture that balance between automation and relationship-led lending.
Recent research suggests there may be a practical reason for caution. The Federal Reserve Bank of San Francisco said in September that banks using AI more intensively tend to show higher returns on assets, but also a greater share of problem loans and a decline in small business lending. The bank’s findings suggest AI can be strong at processing hard data, but less effective when lending depends on softer information about ambition, character and local knowledge. In that sense, the promise of AI in lending may not be to replace the lender’s instinct, but to sharpen it, provided the industry keeps clear boundaries around what machines can decide and what still requires a human conversation.
Disclaimer: This article is intended to inform and educate, not to recommend or endorse any financial product, investment or strategy. Please consider your own financial circumstances and seek professional advice where appropriate before making financial decisions.
