Plend - 173tech

Customer Behaviour

How Plend cut defaults with smarter lending data

Objective

Build scalable infrastructure to integrate open-banking and credit bureau data.

Obstacle

Tight budgets and the need to show a clear, immediate impact.

Outcome

Lower default rates, millions in fairer loans granted, and a future-proof data foundation.

Background

Research by PwC shows that around 20 million UK adults are held back by inaccurate or incomplete credit data, excluding many from fair financial products or forcing them to pay higher interest rates.

Plend set out to change this. Their mission was to move beyond traditional credit scoring by combining open banking data with credit bureau data, giving a fairer, more accurate picture of a person’s financial health. But integrating such large and diverse datasets required robust infrastructure, and that’s where 173tech came in.

Challenges

Data Volumes: Processing open banking data involves handling significant volumes of detailed information, such as transaction histories, spending patterns, and account balances. The sheer size of these datasets translates into increased costs for both extraction and storage. For Plend, ensuring scalability and efficiency in managing these data volumes was critical to keeping operational costs under control.

Which Data Is Valuable: Not all data is equal. With hundreds of variables; from repayment history to income flows to spending habits, the challenge was identifying which signals truly predicted loan performance and creditworthiness.

Solution

Scaleable Infrastructure: We designed and implemented a scalable data stack from scratch, ensuring it could handle large volumes of data without driving up costs. This infrastructure was built with flexibility in mind, allowing Plend to adapt to future needs without overhauling their systems.

Data Modelling: Once the data stack was in place, we modelled the open banking and credit bureau datasets, creating a unified framework that integrated seamlessly into Plend’s existing analytical infrastructure. This setup enabled Plend to extract actionable insights, empowering them to make fairer, data-driven decisions on loan approvals.

Impact

Long-Lasting: Our work directly contributed to Plend funding over £8 million in fairer loans during their first year of operations, marking a significant step forward in their mission to make lending more inclusive and equitable. By building a robust data infrastructure and integrating open banking data with traditional credit bureau information, we enabled Plend to make more accurate lending decisions.

Default Rate: This approach not only helped reduce their default rate but also allowed them to proactively identify pre-arrear customers (individuals showing early signs of financial difficulty). With these insights, Plend could take preventive measures to support borrowers before they fell behind on repayments, fostering trust.

Inhousing: With the technical heavy lifting complete, Plend could confidently hire and scale an in-house data team, focused on day to day strategy rather than building infrastructure.