Case Study: Anonymous Lender
Increasing profitable marketplace lending with Affordability Engine
A major UK personal lender wanted to improve affordability assessments in their high-volume, broker-led marketplace journey. Their reliance on generic ONS data for expenditure modelling and incomplete CATO-based income verification was causing excessive affordability-based declines and manual referrals.
The lender tested how Infact's Affordability Engine – a frictionless, responsive, performant API built to cater for marketplace volumes – would impact their lending performance relative to their incumbent solution.
The data showed a transformed pre-approval process, achieving a potential 4.23% increase in lending.
Client: A major UK personal lender
Objective: To achieve at least a 1% uplift in the affordability and income verification pass rates
Background: The lender’s existing pre-approval process was multi-stage. At each stage, they anticipated drop-off as their hard-fail rules, then credit checks declined applicants.
The set up
The lender did not have confidence in the ONS-data used in their expenditure models and their existing model was causing more affordability-based declines than they felt was reasonable based on economic research.
This was a frustration as it meant the lender was declining applicants who had good creditworthiness and excluding people based on poor availability of affordability data to drive a responsible lending strategy.
In addition to this, they had a large percentage of applicants they could not verify income for using their CATO-based models, resulting in larger manual referrals.
What did Infact do?
Infact's Affordability Engine was tested against the incumbent solution to assess the potential impact on the lender's pre-approval decisioning process, and the net reduction in affordability-based declines by:
- Replacing the in-house ONS-based expenditure model with expenditure components.
- Supplementing their existing CATO strategy with Infact’s income components, giving 100% coverage of applicants.
- Creating a swap set inference to assess the positive swap-in vs. negative swap-out impact.
The solution proposed offered frictionless delivery of personalised income and expenditure metrics on 100% of applicants, giving the lender more nuanced affordability data and a higher degree of configurability and control over their model inputs.
The lender also benefits from continuous model refinement ensuring output accurately reflects the current economic environment, while offering full explainability that improves transparency for customers, auditors, and regulators. Additionally, the solution reduces the cost per acquisition of new customers by driving down OPEX costs.
Measured impact
After the retro, analysis showed that the following uplift could be expected by implementing Infact’s Affordability Engine:
Qualitative impact
In addition to the quantitative impact of the solution, the implementation of the Affordability Engine also offered the potential for:
Reducing the lender’s reliance on an increasingly unreliable data source.
Greater confidence in responsible lending decisions thanks to transparent, explainable expenditure insights, based on affordability information that is real-time, accurate and relevant – making Affordability Engine very agile.
Improving access to competitive rates for non-average customers previously disadvantaged by public data.
Faster decisions with reduced friction in the customer journey from application to approval.
Questions about how Infact can fit into your business?
Our team of experts can help you find the right solution. Fill out the form and we’ll get in touch shortly.
Infact Systems is committed to protecting and respecting your privacy, and we’ll only use your personal information to administer your account and to provide the products and services you requested from us. From time to time, we would like to contact you about our products and services, as well as other content that may be of interest to you. If you consent to us contacting you for this purpose, please tick below to say how you would like us to contact you:
For more information on how to unsubscribe, our privacy practices, and how we are committed to protecting and respecting your privacy, please review our Privacy Policy. By clicking submit below, you consent to allow Infact Systems to store and process the personal information submitted above to provide you the content requested.