Capital One's Data-Driven Approach to Making Fast but Sound Business Decisions

Historically, deriving insight from data has been a human driven activity. However, given the growing complexities of businesses and the wide-ranging data they generate, the time has come to automate this process. This shift from manual, reactive data analysis to proactive, technology driven data science will be nothing short of revolutionary.

With that in mind we invited Mike Kim, Co-Founder & CTO of Outlier, a tool that automates data collection and analysis, to share how insurance companies in particular can leverage Outlier to analyze and curate data in ways human analysts simply can’t. In addition, Mike was joined by Jim Wood, Business Manager, Capital One to share real world examples of how his team has leveraged Outlier to more effectively identify and tackle incidents of fraud.

Historically, data analysis has been considered a reactive, service-oriented discipline. However, with the advent of machine learning powered analytics tool, data analytics is rapidly evolving into a key strategic partner, within the insurance industry in particular.

As Jim Wood, Business Manager, Capital One explains, Outlier not only helps his team identify fraud incidents in real time, it also helps them track the effectiveness of their response. In addition and just as importantly, these tools have enabled his team to think more innovatively and strategically. “All of the sudden, thanks to Outlier, we’re starting to ask much more insightful, out of the box questions and are now tying together things that we never realized had commonality before.”

But how does Outlier do this? In a nutshell, Outlier takes every single dimension of data, across every facet, model all of it, and ask every single question possible to uncover new and unexpected correlations. Using artificial intelligence, Outlier takes data visualization one step further by highlighting which insights are most relevant to you.