Agentic AI - technology that autonomously achieves user-set goals - isn't just an advancement; it's a necessary evolution for firms looking to stay competitive amidst constantly shifting industry standards. Unlike traditional AI, which requires human intervention, agentic AI adapts independently, processing real-time data to drive optimal outcomes with minimal oversight. This game-changing tech is set to redefine the financial and insurance sectors, boosting operational efficiency, reducing costs, and enabling hyper-personalised customer experiences.
Agentic AI in Finance: From Static Solutions to Dynamic Transformation
Over the past decade, traditional AI has enabled efficiency improvements across almost every financial product stack. Once deployed, however, traditional AI remains static and reliant on periodic human intervention, significantly limiting its transformative effect on the financial industry. Agentic AI offers a new route, evolving independently and autonomously responding to live data. Where generative AI offers insights, agentic AI goes further, actively making smarter, quicker decisions.
This independence enables agentic AI to assist customers with complex requests automatically. For example, if a customer requests to "open a new credit card," agentic AI can analyse a wide range of customer data to identify the bank's optimal credit card for the customer's financial profile, prefill account applications, and file biometric verification, vastly simplifying a previously tedious process.
Agentic AI can reduce the burden on banks' administrative teams. For example, conventional AI in credit scoring requires regular updates to remain accurate. In contrast, agentic AI continuously evaluates risk profiles, responding instantly to new data, market changes, or shifts in customer profiles. This responsiveness enables, for the first time, real-time accuracy in credit scoring. The same applies to customer service, where agentic AI can handle complex queries faster, reducing wait times and allowing human agents to focus on high-impact tasks.
Banks' tech stacks are ripe for transformation with agentic AI. Cyber threats and fraudulent activity vectors plague traditional institutions and digital banks alike, and traditional AI often struggles to keep up, relying on static rules that require frequent updates. Agentic AI, however, continuously learns from real-time data, detecting unusual patterns and independently taking actions to mitigate threats, building a dynamic and proactive line of defence for banks.
Insurance Disruption: Dynamic Underwriting and Customer-Centric Policies with Agentic AI
Traditional AI is already widely adopted in the insurance sector, flagging issues for review and enabling improvements in the accuracy of risk models and data collection processes. Unlike traditional AI, agentic AI independently verifies claim data, detecting and correcting anomalies and alerting human operators only when necessary. It's a proactive approach to underwriting, adjusting policies in real time to match evolving risk patterns.
Agentic AI enables insurers to reassess policyholders' risk profiles continuously, automatically adjusting coverage to reflect real-time conditions. This adaptive approach allows insurers to offer hyper-personalised, competitively priced policies that deliver better customer outcomes, replacing rigid, one-time agreements with flexible policies.
Leading the Future: A Paradigm Shift in AI
Agentic AI isn't just an improvement; it's a fundamental shift from passive AI to proactive, goal-driven intelligence. As a trusted partner - not just a tool - it enables faster, more innovative, and more customer-centric solutions. For finance and insurance leaders ready to lead the future, agentic AI is essential. Those who fail to prioritise it risk being left behind.
