Finova appoints Director of Data to power AI mortgage strategy
Finova, the cloud-based mortgage and lending software provider that the company says powers one in five UK mortgages, has appointed Tom Tredwell as Director of Data. Tredwell joins from Shawbrook Bank and will report to Chief Technology Officer David Espley. The hire is framed as a direct response to demand from brokers and lenders for faster, actionable market intelligence, as well as a bid to accelerate Finova's AI capabilities across the mortgage journey.
The appointment is, at its core, a personnel story. But it arrives at a revealing inflection point for UK financial infrastructure: the moment at which mortgage software platforms are repositioning themselves as data businesses, with AI acting as the commercial mechanism for unlocking that transition.
Data as the new lending infrastructure
Finova manages nearly £50 billion in loans and savings under management and serves more than 60 banks, building societies and specialist lenders, alongside a network of over 2,400 brokers. That scale means the platform sits on an unusually rich, cross-institution data asset. Tredwell's remit centres on developing a strategy to leverage that anonymised dataset responsibly, providing broker and lender clients with faster insight into business performance, product positioning and competitor benchmarking.
CEO Gareth Richardson described the hire in terms of governance as much as growth: "Tom brings a rare combination of deep mortgage industry expertise and extensive experience across data and technology and will play a pivotal role in building the scalable, well-governed data foundations we need to develop better products, improve efficiency and deliver greater value for our clients and their customers."
The emphasis on governance is not incidental. Finova explicitly references the UK government's Smart Data initiative, citing government estimates that Smart Data applied to homebuying could generate £14.1 billion in net social value and contribute £2.06 billion annually to UK GDP by 2043. Those projections, sourced from GOV.UK's Smart Data 2035 strategy, frame the hire as an alignment play as much as an operational one.
The convergence angle: fintech infrastructure meets the AI compute question
The broader read-across for cross-sector strategists is the degree to which mortgage software infrastructure is becoming a proxy for the AI-readiness of UK financial services. Finova's Bain Capital Tech Opportunities-backed consolidation (which brought in MSO, formerly part of Iress, in 2024) creates a unified platform with the data density that AI models require to produce meaningful outputs at scale. Without clean, well-governed, interoperable data foundations, AI investment in financial services produces marginal efficiency gains rather than structural transformation.
This mirrors a pattern visible across other regulated industries. In healthcare, the NHS's push toward shared care records is being driven by the same logic: the bottleneck to AI-driven outcomes is not compute or model quality, it is data infrastructure. In mortgage lending, where a single transaction touches credit risk, regulatory compliance, property valuation and consumer behaviour simultaneously, the data-governance challenge is comparably complex.
For investors and technology strategists tracking the UK proptech and fintech convergence, the Finova move signals that data leadership is becoming a board-level priority at infrastructure platforms, not just at the AI-native challengers. Capital that has flowed into open-banking and embedded-finance plays over the past three years will increasingly find itself evaluating the data maturity of the underlying software layer. Finova, with its scale across lenders and brokers, is positioning that layer as a competitive moat rather than a utility.