A company says it can help financial institutions spot fraud by analyzing terabytes of internal e-mails.
The average financial institution exchanges anywhere from a million to three million e-mails a year. Buried within all the missives about meetings and lunches might be a few damning indicators of a brewing fraud.
A company called Digital Reasoning hopes to help banks find this critically important information with machine-learning software that raises red flags found in messy, or “unstructured,” text data, including e-mails, tweets, and document files. The software uses statistical models to break down sentences and infer their meaning. This is important because finding warning signs may not be as simple as matching a string of text.