Using Machine Learning In Digital Banking To Reduce Fraud
After a leading mobile-based financial services targeted at millennials looked at various fraud prevention tools, the company approached Simility to help fight fraud. Simility provided an end-to-end solution which included customized models fine-tuned for their specific use cases.
In the past, fraudsters had used that company's customer accounts to funnel money via stolen identities. But with Simility's advanced device fingerprint technology, the company could detect multiple accounts created from the same device and suspend them before a single stolen payment was processed. Any related activities by the fraudulent device were made available to the fraud analysts to catch unusual transaction patterns per device.
Take a look at this case study to learn:
- Why the company turned to Simility's fraud prevention solution with machine learning;
- How they reduced fraud by 70 percent while increasing business sevenfold;
- How they achieved a dramatic reduction in manual reviews.