Over the years I have written many blogs about insurance fraud including those on anti-money laundering, data quality in fraud, anti-fraud technology, life insurance fraud and even ghost broking. It’s clear that insurance fraud comes in many shapes and sizes and as losses continue to grow, detecting and preventing fraud is consistently ranked among the top three priorities for insurance executives.
Unfortunately it is impossible to predict trends in fraudulent activities, it’s obvious that there is no one bulletproof fraud detection technique. However, insurers that adhere to the following 10 steps offer the best chance for detecting both opportunistic and organized fraud.
- Step 1: Gearing up for data management
- Step 2: Visualizing data
- Step 3: Harnessing business rules
- Step 4: Searching databases
- Step 5: Detecting anomalies
- Step 6: Delving deeper with predictive modelling
- Step 7: Realizing the value of text analytics
- Step 8: Identifying organized fraud through social network link analysis
- Step 9: Managing and triaging alerts
- Step 10: Knowing your deployment options
One organization that followed these ten steps was Czech Insurer insurer, Česká pojišťovna. Using the SAS Fraud Framework for Insurance solution they were able to uncover fraud to the tune of more than 20 Million Czech Crowns ($850k) annually. Read more about the Česká pojišťovna case study.
Data and analytics can help with the detection of fraudulent activity and patterns, but claims adjusters and special investigation units (SIUs) will always be required to turn analytical insight into useful results.
To learn more about the ten steps to detecting and preventing insurance fraud, download the white paper “Simplifying insurance fraud analytics”.