Integrating open banking in your credit decision engine
February 24, 2023
Functioning credit is an important element of a well-functioning economy. When consumers and businesses can borrow money, economic transactions can take place efficiently and the economy can grow. On the consumer side, credit let households smooth their biggest expense, and lower the financial pressures on them. Hence maintaining a good living standards.
The problem in the UK is that lenders heavily relies on outdated data source such as ONS statics and Credit Rating Agencies (CRA) files. CRA data is right on average but fails on an individual point of view. Mainly to depict the changing financial state of an individual. It can also be impacted by considered bad financial practices, which most of the time the consumer is not even aware of.
Similarly, ONS statistics are failing to take into account new trends such as rising cost of utilities, various sources of income or understand a multi banking activity. These two discrepancies ultimately end by restricting access to credit.
In this short article we have decide to share some of the benefits of an open banking based credit decision engine has to offer. And how you can start to make a difference using some of Render' products.
Many lenders struggle to transition to more advanced credit models mainly due to a heavy technological heritage. This lack of technical capabilities constrains them to stick with simple analytical engines and data sources. Hence further limiting their ability to innovate.
These challenges are real and shouldn’t be downplayed. For those who went ahead and started using new credit decision engine with open banking like our sister company Abound, the results have been remarkable. Being at the core of this transition, here are three key benefits Render has noticed:
* Increase revenue per pound lend. Thanks to a better customer experience, taking away the complexity of applying to a loan, Abound was able to increase its acceptance rate, lower the cost of acquisition and serve each customer adequately. And improve the pricing to fit each risk profiles.
* Decrease credit loss rates, Abound is seeing a 70%reduction in credit default rates even still at that time of the year. Where the macroeconomic context keeps on being uncertain.
* Increase efficiency by having less paper work and faster decisioning process. Thanks to a combination of more highly automated data extraction and efficient case prioritisation, underwriters are taking on average 10min per referral case.
How to start integrating open banking in your credit decision engine
Based on its deep expertise Render is providing the right tools for lenders to implement a new credit-decisioning model in less than six months. From start to finish, Render can help you:
* Analyse your credit model performance with and without open banking setting up a retro exercise. With its strong technical expertise the Render team can advise on how to extract the right data for modelling (formatting, completeness testing, and performing missing value and record treatment)without creating any breach in regards to security or compliance policies.
* Setup the adaptable APIs to integrate our products seamlessly. Hence creating a smooth transition towards open banking based credit decisions.
* Develop new credit features mixing open banking and CRA data tailored to your lending activity.
As macroeconomies keep on evolving, lenders will have to increase their digitalisation. Moving towards more sophisticated and automated credit-decisioning models that can incorporate a wide variety of traditional data such as open banking. These changes will help lenders match consumers digital expectations. While keeping their competitiveness and resilience towards the challenging economic times.