One bad keystroke, one bad algorithm, or one bad trader and financial systems can face dire consequences on a global scale. Unscrupulous traders exploit loopholes in existing monitoring systems to manipulate markets to the tune of millions or even billions, until it’s too late to contain the damage.
A major international investment bank knew they needed to mitigate the risk of losing billions of dollars to rogue trading. Business as usual meant wading through petabytes of data to try to find anomalies, or combing through those same mountains of data months or years after an incident to figure out who was at fault and how it happened.
This bank needed a way to proactively detect, understand, and mitigate potential threats and understand holistic risk exposure, but they weren’t sure it could be done. The datasets were large and disperse, and the aberrant behavior was easily disguised.
These are the kind of “impossible” problems we love to tackle at Palantir. We first engaged with this institution in 2013. Since then, we’ve deployed a novel approach to predicting risk that, importantly, surfaces only the likeliest indicators of fraud, saving countless hours and safeguarding the privacy of the company’s employees. Our software gives them the ability to actually prevent billions in losses — rather than picking up the pieces after another bad trade slips through the cracks.
Today, major financial institutions are using Palantir to combat illegal activities while protecting the privacy of millions of employees and customers. Our predictive framework uses years’ worth of structured and unstructured data to put alerts in context. It provides transparency into suspicious and high-risk activities, and gives analysts the tools to track emerging trends and patterns of behavior.
We are driven to find solutions that improve the way the world works. By developing software that lets our customers be proactive, not reactive, we see the potential to transform a core industry and redefine how financial institutions measure risk.