Challenge
The bank used rules-based models to decide which products to offer each customer. Those rules could not respond to individual customer behaviour in real time, which limited how far the bank could personalise its offers.
// Work 09
Launching a country-first AI recommendation engine in mobile banking
// Introduction
A retail bank wanted to personalise its offers to customers and needed decisioning that could respond to each customer's behaviour. The Team implemented the country's first AI-enabled mobile banking product.
What we did
The Team implemented a machine learning recommendation engine that drew on live customer data, including credit assessment, and deployed it directly in the bank's consumer mobile app. The engine was piloted first and then moved into full production.
Outcome
The bank launched the country's first AI banking capability of this kind. Customer engagement, conversion and personalisation improved at scale.
*Some case studies describe work delivered before forming Beacon58.