Agentic AI targets the friction automation can’t fix

Agentic AI targets the friction automation can't fix

Buying a home should feel momentous, yet for millions of borrowers it mostly feels like waiting.

nCino, which recently delved into how agentic AI can support mortgage lending, highlighted IDC’s global 2026 study of mortgage lenders, which found that nearly half of banks still take two to four weeks simply to process an application, while 30% take more than four weeks to close. Only around one in three loans completes in under a fortnight.

That delay is costly on both sides, nCino argues. Borrowers experience it as uncertainty, while lenders absorb it through loan officer hours lost to status calls and document chasing. A decade of workflow automation has failed to close the gap, because automation was designed to accelerate individual steps rather than reason across the lifecycle of a loan.

Workflow automation still earns its keep on structured, repeatable work, such as routing tasks, triggering alerts and generating disclosures. Its limit, nCino notes, is one of judgement rather than effort. IDC found the top three global friction points are outdated credit risk models (31%), document collection and verification (27%), and complex compliance and KYC requirements (27%). These are process problems, not speed problems.

Agentic AI, by contrast, is goal-driven rather than rule-bound. Where automation routes a document to a queue, agentic AI reads it, classifies it, extracts the relevant data, checks it against the existing file and flags what is missing. nCino calls this the agentic homeownership journey, spanning conversational tools such as its Mortgage Advisor, document intelligence and pre-screening that catches issues before they reach an underwriter’s desk.

Lenders are convinced. IDC found decision-makers now rank AI agents for mortgage operations as their number one transformation priority, with 35% naming it first globally, rising to 44% in the UK, and a target of 68% process automation within five years.

The payoff differs by region, nCino highlights. In the US, 49% of lenders already use AI for document extraction against 39% globally, with roughly half of underwriting still manual. The UK and Ireland run on broker channels where transparency matters as much as speed, prompting a push towards end-to-end digital journeys. Australia and New Zealand already close loans faster than anyone, so the next gains come from layering intelligence onto an experience that already works.

nCino concludes that the winners will fix the workflow first, then place intelligence where it compounds: at intake, in verification, during underwriting and wherever a borrower is left wondering what happens next. The advantage comes from placement, not volume.

For more insights, read the full story here. 

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