4 core insurance functions primed to benefit from agentic AI
Agentic AI in insurance has potential to transform insurance. Read four use cases.
Author
Thorsten HeinRSS
Principal Product Marketing Manager
Principal Product Marketing Manager
Thorsten Hein is a Principal Product Marketing Manager in the Risk Research and Quantitative Solutions Division at SAS Institute. He specialises in global risk management operations insights in both banking and insurance, focusing on risk and finance integration, IFRS, Solvency regulations and regulatory reporting. He helps risk management stakeholders to go beyond pure regulatory compliance and drive value-based management to maximise business performance, using his wide experience to deliver both business relevance and technical coherence.
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Asset and liability management (ALM) is still a cornerstone of banking. But when market conditions shift quickly, as they increasingly do, it no longer reflects how banks actually experience and manage risk, capital and profitability. The environment has changed. Volatility is now persistent rather than episodic. Regulatory expectations continue to
Valuable customers? Insurers toe the line with agentic AI
Agentic AI has been heralded as a top tool for efficiently orchestrating customer engagement activities at insurance companies. It can: Automate repeatable, rule-based processes that affect customer experience (think claims processing and customer onboarding). Rapidly retrieve disparate data, analyze risks and recommend decisions. Help lower operational costs while keeping humans
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