Graph and AI Adoption in Property and Casualty Insurance
Sia Burra, Chief Innovation Officer, Abhay Solutions
In insurance companies, data is collected at the product- or application-level and big list of integrated third-party sources. Analytics are provided separately, and insights are isolated to silos and scattered across line of business and functional areas. Connecting data from multiple sources to get better insights is very critical for insurance companies AI and ML techniques with graph as platform helps overcome challenges of unifying data from disparate data sources and get deeper insights which helps insurance companies realize important business goals, more accurate targeting, longer retention and better profitability. Some of the key points we'll explore in this session include: Graph and AI adoption in insurance benefits; Contribution of graph and AI in analytics in insurance companies; Challenges of adoption of graph in insurance space and how to mitigate them How unification of disparate data through graph and AI helps property and casualty insurance; How graph learning helps predictive analytics and prescriptive analytics (e.g. in countering fraud beyond fraud detection)
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