TL;DR
Bath Building Society has partnered with London-based fintech Sikoia to automate mortgage document handling, income verification, and affordability checks. The AI-powered platform validates documents at upload, extracts income data from payslips, and produces risk indicators in seconds rather than hours.
What the partnership covers
The deal forms part of Bath Building Society’s wider technology transformation and its move to cloud-based lending infrastructure provided by One Mortgage System (OMS).
Sikoia’s platform automates several steps in the mortgage application process that have traditionally required manual handling:
- Application validation: Documents are checked at upload for completeness, integrity, and policy compliance, with instant feedback to reduce rework
- Income and employment verification: Income and employment data is extracted and standardised from payslips and supporting documents, producing a clear income profile with automated risk indicators
Bath is currently using Sikoia via its Ready-To-Go Dashboard for immediate operational improvements, while a deeper integration through OMS’s cloud platform supports a more streamlined application-to-completion journey.
Why it matters for UK lending
Craig Brown, Bath Building Society’s Head of Mortgages, said the automation would have “a real impact on how quickly and consistently we can progress applications.” By reducing manual checks and summarising key information for underwriters, the society expects faster decisions and clearer feedback for brokers.
The partnership reflects a broader trend among smaller UK lenders adopting AI verification tools to compete with larger banks that have more extensive in-house technology teams.
Looking forward
As AI-powered verification becomes standard across UK mortgage lending, the competitive gap between early adopters and those still relying on manual processes will widen. Smaller building societies that invest in these capabilities now may be better positioned to attract broker business through faster turnaround times.