Experian CaaS is proven to reduce underwriting time by up to 20% and reduce false positives by 5%

Covid-19 is rapidly changing the personal financial circumstances of millions of consumers. Making it difficult for organisations to quickly assess vulnerability and identify customers that need support now and throughout the crisis. The continuous monitoring of affordability is critical not only for identifying stress, and therefore pre-delinquency, but also for protecting vulnerable consumers.

 

Being able to perform affordability checks ‘in-life’ will bring the value of foresight. Applying this same level of care and attention to new lending will enable you to better understand consumers’ affordability status and offer the right products, at the right time.

 

As lenders look ahead, we believe a deeper understanding of individual customers’ financial stability, capacity and behaviours through trend analysis and early warning signals will be imperative to managing risk.


Power of Open Banking

Experian’s affordability solutions can bring you the technology and insight made possible by Open Banking. Having in-depth insights from Open Banking data will give you the ability to better know your customers better allowing lenders to making fair and appropriate decisions.

 

We have seen that consumers are willing consent to sharing their data, especially if there is a clear benefit from doing so, for example need to share data at that point in time. They want to access that service there and then – that is their motivation to share.


Deeper understanding of affordability

Catergorisation as a service (CaaS) can help you to give organisations a deeper understanding into how much customers can afford to borrow and what they are able to repay by providing detailed insight on a customer’s financial behaviour in real-time. This will allow you to improve how you communicate to them, and develop and deliver better products, more attuned to what they can afford.

 

CaaS can help you monitor changes in a customer’s finances, providing an assessment of liquidity, a warning of loss of earnings and potential delinquency, as well as provide solutions and support to your customers through difficult times.


Transforming transactional data into insight

We can help achieve this by analysing bank statement data through our categorisation engine; CaaS, which applies two approaches for analysing transactions. Firstly, it features keyword matching – looking for brands and regularly used descriptions (Starbucks, train travel, city councils etc). Secondly, it identifies regular patterns of payment (on the 30th of each month the customer receives £3,500, inferring a regular salary).

 

All of this gives you much deeper insights into income stability and balance – telling you how long a customer’s money needs to last between pay days, showing how often they have less than £100, and highlighting early signs of vulnerability, like gambling, payday loans, or high and consistent card payments.


Better outcomes for consumers and businesses

For lending organisations, CaaS’s categorisation and reporting will reduce underwriting time by up to 20%, significantly improve the accuracy of decisions and ultimately, will ensure your customers receive the correct products and services, in the quickest possible time based on their true affordability.

 

Salary and income validation was tested against human assessors by a high street bank, and found that our CaaS’s algorithm was correct more often and more reliably than humans. This allowed them to save time in the process, leading to better outcomes for consumers and businesses.

 

By having an accurate understanding of what a customer can afford means you can promote the right credit products to the right customers at the right time. A study by major credit card company showed they were able to drop their false positive identification of high-risk customers by 5%, and therefore lend to a significant number of customers they would otherwise have declined.