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Data Analytics Proves Key in Uncovering Insurance Fraud
A recent investigation has highlighted the crucial role that data analytics plays in combating financial crimes in the insurance industry.
Advanced Data Analysis Techniques Uncover Hidden Relationships
Using advanced link charts and graphs, investigators were able to uncover a complex web of connections between policy applicants, agents, and beneficiaries, shedding light on previously hidden relationships (Figure 7).
Link Chart: A Powerful Tool for Investigators
The link chart, created using Sentinel Visualizer’s Link Analysis tool, shows how data analytic tools can help investigators identify patterns and connections that may have been overlooked in traditional manual investigations.
According to Manhim Yu, “Data analytic tools can largely improve the effectiveness and efficiency of financial crime investigations, eliminating blind spots and weaknesses that prevail in traditional manual investigation.”
Benefits of Data Analytics in Insurance Fraud Investigations
The use of data mining and risk-scoring techniques can significantly reduce false positives, trimming down time and investment costs while increasing accuracy and investigation quality. Additionally, predictive modeling and machine learning algorithms can be applied to historical data to predict potential fraud in future claims.
Why Invest in Data Analytics?
While some insurance companies may still be hesitant to adopt data analytic tools, the rapid development of technology-driven business environments and heightened regulatory scrutiny make it clear that investment in tech-based solutions is not only imminent but necessary. As Yu notes, “The use of data analytic tools can guarantee accuracy and completeness, resulting in a more comprehensive and holistic investigation of fraud and money-laundering activities.”
Conclusion
With data analytics playing such a critical role in insurance fraud investigations, it’s no wonder that investigators are turning to these tools to streamline their work and stay ahead of fraudulent activity.
Figure 7: Link Chart of Policy Applicants, Agents, and Beneficiaries
(Source: Sentinel Visualizer)
References
- Association of Certified Fraud Examiners (ACFE). (2016). Report to the Nations on Occupational Fraud and Abuse. Retrieved from https://s3-us-west-2.amazonaws.com/acfepublic/2016-report-to-the-nations.pdf
- Association of Certified Fraud Examiners (ACFE). (2018). Report to the Nations: 2018 Global Study on Occupational Fraud and Abuse. Retrieved from https://s3-us-west-2.amazonaws.com/acfepublic/2018-report-to-the-nations.pdf
- Association of Certified Fraud Examiners (ACFE). (2019). Insurance Fraud Handbook. Retrieved from https://www.acfe.com/uploadedfiles/acfe_website/content/documents/insurance-fraud-handbook.pdf
- Coalition Against Insurance Fraud. (n.d.). By the Numbers: Fraud Statistics. Retrieved from https://www.insurancefraud.org/statistics.htm
- Coalition Against Insurance Fraud. (2019, March). The State of Insurance Fraud Technology. Retrieved from http://www.insurancefraud.org/downloads/Fraud_tech_study_2019.pdf