The complicated fraud-detection process required an offshore team to continuously monitor data feeds on multiple screens to determine whether customer transactions flagged by their algorithms were fraudulent or genuine. This manual process led to erroneous judgements, resulting in many unnecessarily blocked cards and huge frustration for customers.
In 20% of cases, the offshore team phoned the customer directly to request additional information, which resulted in a number of challenges. These included necessary but expensive security steps, language barriers, and, in some cases, lost customers.
We spent time with the company’s fraud-prevention Subject Matter Experts (SMEs) to create a Rainbird model that identifies fraud by replicating their best-practice methods, without relying on humans. This reduced the time spent on each case, and improved accuracy and consistent decision-making.
To do this, Rainbird took the logic from over 50 fraud cases, along with the expertise of three of the business’ best-performing SMEs. The output was a Rainbird-powered fraud engine that represented the company’s best-practice procedures, which was capable of handling multiple concurrent transactions simultaneously and consistently.
We also created a new model for prioritising cases that needed expert involvement. Rainbird automatically calculates every transaction with a percentage likelihood of being genuine or fraud.
The client is now able to prioritise a smaller number of high-risk cases, paving the way to move the fraud-detection process on-shore so that the most high-risk cases can be assessed by their most experienced team members. The result of our work was an 85% automation of all cases and a 60% reduction in back-office processing costs.
The new process avoids the less accurate and inconsistent judgements that were being made by their offshore team. As well as increasing detection rates, Rainbird was able to reduce the number of false positives and the cost and inconvenience of outbound phone calls to customers.
Calls to customers are now backed by Rainbird’s in-built Evidence Tree, which can explain why Rainbird has concluded a fraud risk and better inform the customer conversation leading to consistent, better-quality calls, and demonstrably better customer outcomes.