Azure Machine Learning makes it easier to spot false loan applications and protect consumers
Elly Yates-Roberts |
Callcredit, one of the UK’s biggest credit reference agencies, is using Azure Machine Learning to identify criminals assuming a different identity when trying to access credit reports and borrow money.
The services have successfully stopped fraudulent access to Callcredit’s credit reporting and scoring service Noddle, and prevented consumers having loans taken out in their name.
Noddle is a free-for-life credit report and score service that searches the market to find credit cards and loans available to a person based on their credit rating. Callcredit is using Azure Machine Learning which uses existing data to verify the identities of those signing up to Noddle.
“We were using a third-party, specialist machine-learning fraud-detection platform to help us spot fraudulent sign-ups to Noddle,” said Mark Davison, Callcredit’s chief data officer. “We had to decide whether to bring this in-house; so, we created a model internally, on Azure Machine Learning, which outperformed the third-party product. We’ve now retired the third-party service and are running our own machine learning-based fraud detection, spotting how fraudsters are trying to sign up to Noddle and preventing them getting access to those credit reports.”
“It helps lenders make more accurate decisions, more quickly. The loan applications a lender will turn down and the ones they will approve are easy to spot,” said Davison. “The grey area in the middle, which are the ones they have to manually refer, are much trickier. As a result, the end consumer goes through a far more onerous process where an underwriter has to review the case. That’s not a great experience for the consumer or the lender.”