InsurByte

The two-day conference will provide our members with the opportunity to learn about the latest trends in claims and risk management, and network with regional and global insurance executives. This conference is a unique opportunity for everyone - from the adjuster to the claims executive - to make new connections, stay on top of market trends and grow their network.

Healthcare has become one of the most debated topics in the world – made more relevant by the pandemic. With customers demanding more from their healthcare providers, while struggling with rising medical costs and inflation, what role can insurers play in helping provide affordable healthcare? The Asia Conference on Healthcare and Health Insurance gathered experts in the industry to explore some of these issues.

Insurance Asset Risk is pleased to announce the dates for the Insurance Asset Risk Asia conference, taking place virtually on 27th – 28th February 2023. This unique virtual briefing will give attendees the opportunity to come together and discuss the topics shaping the Asian insurance industry today. Over two days, through panel discussions, keynote addresses and presentations, experts will be tackling the key issues impacting Asian insurers' investment strategies today and in the future. Areas of focus will include best practices for ESG integration and net zero transition, asset allocation and investment strategies in the current climate of volatility, inflation and high interest rates, and IFRS 17/9 and RBC as we enter 2023.

Discover the latest fraud detection strategies and technologies at IFM Insurance Fraud Management 2023. Shift’s fraud subject matter experts will be onsite to share their extensive knowledge with you. Visit Shift’s booth #117 in the IFM Exhibit Hall! Learn about Shift Claims Fraud Detection and how you can: Uncover more fraud with 34% additional impact from external data integration Grow SIU acceptance rates by 3X Quickly investigate 4X faster with clear context Access our industry expertise including 200+ data scientists