Nivo, the AI Agent for lenders and brokers, has published a new market insights report revealing how wasted admin, duplicated effort and repeated broker-lender back-and-forth are costing specialist lending teams hours on every case.
The research, which is based on in-depth conversations with more than 70 lenders and brokers across the UK specialist lending market, alongside deployment data from Nivo’s own AI platform, identifies rework, not complexity, as the dominant driver of operational inefficiency in origination.
The report finds that many specialist lending teams are losing time to work that has already been done once, including chasing missing documents, correcting incomplete information, checking submissions, clarifying requirements and managing repeated broker-lender communication.
According to Nivo’s research, most firms in the sample are achieving right-first-time submission rates of 50% or below, meaning a significant proportion of daily case administration is spent fixing, chasing or repeating work rather than progressing new cases.
Nivo’s findings also show that a typical secured loan case can generate 15 to 20 message rounds, involve more than five people, and require upwards of five hours of administration on the broker-to-lender leg alone. Between 20% and 50% of cases are also stalling or failing to complete, with process friction identified as a more common driver than deal quality.
The report also draws on Nivo's deployment data, which shows reductions of six to eight hours of administration per case when AI agents are applied at the intake and document collection stages, where much of this wasted effort typically begins.
Matthew Elliott, Co-Founder and Chief Commercial Officer at Nivo, said:
“The biggest thing stopping brokers and lenders completing more deals is the admin work gathering, checking, and chasing information and documents. Our AI agents are a perfect fit for this work, taking it on 24/7 so teams can move more cases forward faster at lower cost.”
The Rework Problem is available to download now at: https://whitepaper.nivohub.ai/
