I am the Chief Data Scientist (and co-founder) at Rippleshot. What does that fancy title mean? I spend my days investigating patterns in card fraud and card behavior. I am constantly looking for tools to develop to identify fraud events and help financial institutions write decision rules to stop them.
The card fraud industry is fascinating because of the massive amount of available intimate data. We live in a time with access to monumental samples of consumer behavior data. I am consistently surprised about what type of insights I can uncover regarding how people and businesses operate and, most important of all, the rare types of criminal behavior I can identify.
I have accomplished many things in my 10+ years at Rippleshot, but two projects will always stick out for me. First are the original detection algorithms I wrote when we started the company that acted as the foundation for future accomplishments. More recently, our Rules Optimizer product, which lets fraud analysts upload their data and leverage machine learning to create optimal decision rules for stopping fraud.
Moving forward, I want to explore building a web of consumer and merchant behavior in the financial equivalent of the web of life. Relationships between people are described by financial data, just like they are in social media. This is potentially the source of many profound insights into humans as a whole.