How data-driven decisions can transform consumer lending

Within the consumer lending industry, analytics is everything. For a business such as Admiral Money, whose core activities are unsecured personal loans and car finance, competitive advantage hinges on the capacity to make rapid decisions based on large data sets.

The company’s Head of Analytics and Data, Kelvin Lee, explains: “Because our business largely comes through pricing comparison websites, we need to be able to make a decision on how likely somebody is to default, or settle their loan early, and how likely they are to take up another product. All these different factors feed into a number of predictions about a customer, which effectively tell us whether that customer is going to be profitable at different price points. And that dictates whether we choose to lend to that customer and at what price. It’s absolutely fundamental to our business. We live and die on these predictions.”

All this takes serious computational power and, until recently, Admiral didn’t have it. Launched in 2017 as part of the wider Admiral Group, Admiral Money was operating on legacy technology in the form of on-premise hardware that, in addition to being costly to maintain, presented all the usual challenges: frequent outages, high prices, slow processing speeds and concerns around data protection. The old model was hindering growth.

“We got to a point where we literally couldn't add much more data into the mix,” says Lee. “We were close to the point where we would have to either pull away vital data that you use for decision-making, or stop writing business.” The solution was to turn to the cloud in the form of Amazon Web Services (AWS), which has been pioneering cloud technology and innovating with Intel on behalf of its customers for more than 16 years.

Migrating critical business workloads and business intelligence is daunting, so partnering with the right experts was essential. Inawisdom, an AWS Premier Services Partner that specialises in AI, machine learning and data analytics, offered an understanding of how Admiral wanted to empower in-house end users. “We were very clear that we were looking to build our own data capability, and that the transition from it being built to us running it had to be seamless. Knowing that Inawisdom have such a strong relationship with AWS gave us confidence that the solution being proposed was the right one.”

Together, Admiral Money and Inawisdom agreed that the solution was to create a new analytics platform that would deploy Inawisdom’s data pipeline to accelerate the migration. In just 12 weeks, Inawisdom designed and built a data warehouse model using AWS Cloud with Intel technologies that enabled Admiral Money’s analysts to produce visualisations and correlate data in ways that had previously been impossible. More than two terabytes of historic data was processed into the new system in three months, and a machine learning sandbox was created for the rapid testing of new use cases and data sets, so Admiral Money could explore innovative ways of leveraging their data.

The results have been transformative. Admiral Money’s staff can now make accurate data-led decisions on everything from quote to sale to customer engagement. Security fears have been allayed, with data management protection effectively embedded into the platform. And it’s been brilliant for recruitment. “We have a platform which we can use to attract even more talent,” says Lee. “People want to know that you’re in the cloud and that your technology stack is in a good place so that they’ll have access to the latest and greatest tools.”

The processing power of AWS means that designing new models no longer takes months. “We can do that in days and hours now,” says Lee. “We are effectively deploying new models in minutes, which is the benefit of a cloud solution and the benefit of some really good design work that was done at the outset.” Crucially, the company is now primed to continue growing, he concludes. “What we’ve got now is an entirely scalable technology that we previously didn’t have. We started with just over £400mn in March 2020 when we embarked on our data journey, and now have over £800mn in balances. We’ve doubled the size of the business.”