All the information that is needed to find and stop bad actors from entering our financial system already exists and is available to you today; it’s just buried in terabits of messy, unstructured data all over the internet. For those performing investigations and evaluating risk, this needle in a stack of needles problem is huge and growing: Unstructured data already dominates the web (growing exponentially year over year), and the traditional technology these departments use cannot keep up. Recent developments in natural language processing technology (NLP), the field of AI that focuses on human language, have, for the first time, made it possible for automated systems to find and deliver identity-relevant intelligence hidden in unstructured textual data. These innovations unlock a new world of actionable insight, providing much-needed ammunition in the fight against fraud, money-laundering, financial crime and terrorism.
Key Takeaways:
1. Unstructured data leaves room for criminals to fly under the radar because traditional tech can't keep up
2. New developments in AI and natural language processing (NLP) have begun to make it possible for automated technology to sort through unstructured data
3. In order to crack down on financial fraud and money laundering, financial institutions should use AI as a tool for finding and fighting bad guys
