Experian has announced that it is launching a new range of services to help lenders evolve their approach to making consumer credit decisions, so businesses can make more informed decisions and deliver fairer, more affordable outcomes for their customers. The service is called Experian Credit 3D.

Experian says knowing a consumer’s credit information at a single point in time only offers a snapshot of their financial behaviour. However, by using innovative trended and alternative data sources via Experian Credit 3D, businesses can access an unparalleled set of insights, enabling faster decisions based on a more rounded picture of affordability.

Tom Blacksell, Managing Director of B2B at Experian, said “A customer’s current credit position only ever tells part of the story. People’s financial circumstances are multidimensional and unique. By providing a range of smart insights that recognise this, we are supporting our customers as they look to keep up with a diverse and ever-changing global population.

“With Experian Credit 3D, we are making richer sources of data available to our customers to make this possible, combining trended and new alternative data sources, such as open data. But, more importantly, we are employing our vast set of capabilities and wealth of experience in advanced analytics and machine learning to help our customers through this period of exciting and rapid change.”

There’s little doubt that the market is evolving fast, driven by burgeoning consumer demand for a more fluid and accurate customer experience. According to a recent survey, 77% of businesses cited ‘gaining better insights about their customers’ as a top priority for the year ahead.

Traditional risk scores have evolved significantly over the last five years using analytics and utilising different data sources, such as rental, mobile and payday loan data. They use a view of payment history and credit use at the point of application to form a risk score, which remains a reliable and successful assessment method for many ‘mainstream’ consumer applications with stable profiles.

Augmenting traditional risk scores with a view of detailed consumer behaviours over time is particularly valuable in making decisions on applications which are currently on the margins. Alternative non-credit data, including subscriptions and utilities data, can support the approval of applications from consumers with ‘thin’ credit files.”