The National Association of Insurance Commissioners (NAIC) and Association of Certified Fraud Examiners (ACFE) have identified over $40B in losses related to Fraud with ~10% of those claims in Property & Casualty, Automotive, and Business Insurance.
Further complicating the process is all 50 states in the US have different regulatory bodies, each with different rules and regulations. Some states have enacted legislation to combat the different types of insurance fraud schemes such as agent and broker schemes, underwriting irregularities, vehicle insurance schemes, property schemes, doctor and personal injury schemes, upcharging health treatment, inflating damage values, salvage fraud, and many others. Special Investigations teams are looking at ML methods and new technology to help reduce the queue of claims and increase the accuracy of fraud detection. Join our panel of speakers in a hands-on session that demonstrates how to employ ML, Graph technology, Human-in-the-loop, and visualization techniques to ensure your organization complies with Special Investigations units in 2021.
The focus of this webinar is to identify areas in which Machine Learning, Visualization, and Graph technology can increase the accuracy of claims fraud identification by over 11%, and to show how including the ‘Human in the Loop’ can get you ahead of your state’s fraud prevention legislation. This event is designed in a 'Speed Dating' format, focusing on key topics for under 15 minutes in order to maximize the insights.
Key Learning Topics:
- Key Challenges for Special Investigations: State & federal rules are complex and difficult to manage for audit & compliance; our technology approach with ML & Graph can help you gain accuracy & insights in real time
- Technology Innovations: new technologies like master data matching, graph analytics, and ML are assisting in the reduction of false positives and increasing accuracy
- Empower the Investigator: 2021 capabilities in visualization technology and human processes are increasing throughput, providing valuable human intelligence, and creating quicker and more efficient outcomes for different roles like claims fraud management, investigators, and data and analytics teams
- Rise of ML & AI with ‘Explainable’ ML: Present practical methods of fraud detection and prevention, complex dependencies, and case management with ‘humans-in-the-loop’ to incorporate fraud investigator domain expertise into the detection technology for increasing accuracy of fraud prevention