Automated decisions you can trust
Getting automated decisions you can trust is a big challenge. If automated decisions are always subject to review, then cost savings aren’t being realised. Loans will take longer to turn around. Consequently, members become dissatisfied. Furthermore, automation needs to ensure applicants get a fair hearing.
The latest version of our decision engine delivers a greater proportion of auto accepts than ever before
That’s because we’ve looked at £100m of credit union loan applications. Final accept, refer or decline decisions were compared to automated recommendations. Applicants’ credit profiles were assessed against the risk appetite of 20 lenders.
As a result, we are now better able to understand the thresholds for negative indicators, including missed payments, defaults and County Court Judgments. The value of CCJs and defaults is important. So is when they were issued. And nor are all defaults the same.
Furthermore, there are good missed payments. (Where an applicant has recovered, financially and cleared arrears). And bad missed payments. (Where arrears are accumulating and heading towards a default). It is important to distinguish between the two.
A common approach to common challenges
There is remarkable consistency between responsible lenders. Approaches to assessing credit risk are broadly similar.
Importantly, a common approach suggests common problems.
Financial exclusion manifests itself in particular ways on a credit record. Responsible lenders, set up to tackle financial exclusion, have adopted lending policies to meet this ongoing reality.
For example, a low credit score might be due to demographic factors. Renting rather than owning your home. Not re-registering for the electoral roll. Moving around a lot. All these make it harder to get credit. When it’s hard to borrow, millions turn to high-cost short term credit.
High interest means unaffordable payments. Instalments are missed. Knock on effects include not making a payment on water, gas and electricity. Collection departments in subprime lenders often shout the loudest. It’s no wonder that people get behind on utility bills. Of course, this sends a credit score even lower. And the cycle repeats itself.
Responsible lenders understand the financial struggle facing low-income households. Because of this, a fairer approach to lending is provided. It has to be. Without responsible lenders, many people’s situations would spiral out of control. Consequently, this leads to increased costs for borrowers and wider society (e.g. poor health outcomes).
Decision engine 2.0: big benefits
NestEgg’s decision engine caters for all risk types. It is flexible enough to fairly assess loan applications from the financially excluded.
We’ve learnt from our clients and their borrowers and are excited to be launching decision engine 2.0. It’s a big upgrade. Four new clients went live this next week. Benefits include:
- Granular rules enabling you to set value and recency limits for when defaults or CCJs are referred or declined. There are lots of options for credit score cut offs, treatment of insolvencies and other missed payments.
- Four lending risk levels are available, based on the value of a loan application.
- Choose strategies according to product e.g. revolving credit, homeowner and consolidation loans
- Change rules really easily.
- Best in class affordability assessments that work well for those on lower incomes and the better off.
- Open Banking data to complement bureau information.
- Built in e-signatures.
- Open API for back office and web front end integrations.
Grow your loan book
With 25 years’ experience in money advice and credit union lending operations, NestEgg has the experience to help you fine tune your lending strategy.
Our software makes it really easy for people to get accepted for affordable credit so you can grow your loan book. Critically as the launch of decision engine 2.0 shows, we are constantly upgrading and improving.