The Australia property insurance is a very competitive and volatile. Recent years have witnessed many natural disasters which have increased the claims for insurance companies. It is challenging to access accurate information on the risk exposure and the detailed building characteristics. As a part of the solutions, we have developed a property intelligence product leveraging 250+ risk attributes covering 10M+ properties in Australia. This will help property insurers in underwriting, pricing, and portfolio risk management. Attendees to this session will get insights on:
• How an analytical property data mart was created by harmonizing structured and unstructured data
• How State of art ML models were built to estimate the insured value of the building, predict the market penetration, estimate post event losses etc.
• Business benefits realized through this solution.
Case Study
Suguna Jayaraj
SVP, Head of P&C Analytics
Suguna is a passionate data science leader with a 14+ years of experience in insurance and banking industry. She heads the P&C Analytics for Swiss re solutions and runs the product team of data scientists, data engineers, actuaries, geospatial scientists etc. in Bangalore. The team develops solutions and products by leveraging new age data sources as well as integrating ML based techniques to enable the clients take better risk decisions. She was honored as ’40 under 40 Data Scientists’ by Analytics India Magazine in 2021. Her paper on “ML based Geo-score to improve auto insurance pricing” went to be Top 10 Machine Learning papers in India and is published in Internationally reviewed Lattice Magazine Q2 2021. She holds an M.Tech from IIT Delhi and is a B.E(Civil) gold medalist from Gujarat University.
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Tuesday, 20 September, 2022 / 03:30 PM - 04:00 PM IST