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In this episode we talk with Bavo DC Campo, a data scientist and statistician, who shares his expertise on the intersection of actuarial science, fraud detection, and social network analytics.
Together we will learn how to use graphs to fight against insurance fraud by uncovering hidden connections between fraudulent claims and bad actors.
Key insights include how social network analytics can detect fraud rings by mapping relationships between policyholders, claims, and service providers, and how the BiRank algorithm, inspired by Google’s PageRank, helps rank suspicious claims based on network structure.
Bavo will also present his iFraud simulator that can be used to model fraudulent networks for detection training purposes.
Do you have a question about fraud detection? Bavo says he will gladly help. Feel free to contact him.
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Want to listen ad-free? Try our Graphs Course? Join Data Skeptic+ for $5 / month of $50 / year
https://plus.dataskeptic.com
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472472 ratings
In this episode we talk with Bavo DC Campo, a data scientist and statistician, who shares his expertise on the intersection of actuarial science, fraud detection, and social network analytics.
Together we will learn how to use graphs to fight against insurance fraud by uncovering hidden connections between fraudulent claims and bad actors.
Key insights include how social network analytics can detect fraud rings by mapping relationships between policyholders, claims, and service providers, and how the BiRank algorithm, inspired by Google’s PageRank, helps rank suspicious claims based on network structure.
Bavo will also present his iFraud simulator that can be used to model fraudulent networks for detection training purposes.
Do you have a question about fraud detection? Bavo says he will gladly help. Feel free to contact him.
-------------------------------
Want to listen ad-free? Try our Graphs Course? Join Data Skeptic+ for $5 / month of $50 / year
https://plus.dataskeptic.com
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