According to Wikipedia, Open banking is a financial services term as part of financial technology that refers to: The use of open APIs that enable third-party developers to build applications and services around the financial institution. Greater financial transparency options for account holders ranging from open data to private data.
There is no doubt that Open Banking offers a rich insight into potential customers’ financial position that conventional credit reference data cannot. Its ability to deliver accurate insights into income and expenses allows for a deeper understanding of an applicant’s disposable income. Open Banking service providers like AccountScore, Credit Kudos and Openworks are delivering increasingly actionable insights through improving categorisation and analysis. Beyond affordability this insight helps identify potential vulnerability, the most obvious being gambling behaviour.
It is not surprising therefore that there is escalating interest by lenders in this emerging data source. With credit files incomplete because of the FCA’s COVID requirement [FCA Link? There are multiple references] to stop reporting, and a continually growing focus by the regulator on all forms of vulnerability, the benefits to lending decisions are clear.
Realising these benefits without damaging commercial consequences is difficult; Because of its impact on journey conversion, how to use the data effectively in decisioning strategies, and the effort to implement an ongoing need for change.
A key goal of any lender is to ensure that they get as many ‘good’ applicants through the onboarding journey. The more that are lost along the way reduces marketing efficiency, loan volumes and revenue. Conversion is king, but Open Banking has a strongly negative effect. While some customer cohorts may engage with Open Banking, a large population are rejectors, having not yet accepted this new world. Lenders must therefore only use Open Banking journeys for applicants where it is absolutely necessary, and where journey engagement is predicted as high. Other applicants need different journeys, or they will be lost.
Using Open Banking data in onboarding journeys requires a very different approach to using credit reference data, because unlike credit histories there is no retro data to use to build strategies. As a result, decision science teams have to build their strategies in real time, in live. It requires advanced split testing, thorough outcome tracking, and fast model refinement.
And finally, both journey optimisation and decisioning optimisation will drive lenders to have to continually and iteratively change their onboarding systems, which will require significant ongoing technical resource to implement.
For these reasons, the old way of onboarding, with fixed forms and predefined onboarding journeys are simply inadequate in an Open Banking world. An Open Banking world demands agile, adaptive, and dynamic onboarding journeys. Journeys that deploy Open Banking intelligently, targeted where it adds value but not where it impacts performance. Journeys that can be tested easily, analysed and refined quickly. Onboarding that is configured, not coded.