Suncorp speeds up insurance claims: AI agents to cut time and boost accuracy

Australian insurance giant Suncorp is set to launch five AI agents that will handle various “sub-processes” in insurance claim settlement as early as this month. This move is expected to significantly speed up operations and enhance accuracy, especially in complex tasks like coverage verification and incident classification.

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Why Suncorp Needs AI Agents

Insurance claims settlement is a complex and multi-stage process. It involves receiving applications, classifying them, verifying coverage, assessing damages, interacting with contractors, and finally, making payouts. Each of these stages can be a source of delays and errors, negatively impacting customer satisfaction and operational costs.

Suncorp, which has long utilized data and AI technologies, aims to automate this process, making it more “agentic” — where individual tasks are performed by specialized AI agents.

How AI Agents Will Work at Suncorp

The company is implementing five AI agents that will take over a portion of routine tasks. Two of them will operate at the First Notice of Loss (FNOL) stage, when a customer reports an incident. Their tasks include:

• Information collection and validation. One of these agents is expected to be voice-based, taking claims over the phone.
• Classification and routing. Agents will determine the type of claim and direct it to the appropriate department or to the next agent for further processing.

The next stage is “coverage check,” where a system of agents will determine if the claim falls under the insurance policy terms. AI agents will also be used for:

• Vendor dispatch. For example, sending a repair crew to the incident site.
• Settlement calculation. Automatic determination of the compensation amount.

The entire claims settlement process is orchestrated using BPMN workflows, where each task can be performed by one or more AI agents.

Reliability and Control: How Suncorp Manages AI Risks

Kranthi Nekkalapu, Executive for AI at Suncorp, emphasized the importance of monitoring and risk management when implementing AI agents. The company has developed a centralized observability platform based on Databricks, which collects data from all agents and workflows in real-time. This allows for:

• Performance tracking. Leadership can see the big picture, business users can view details of specific decisions, and engineers can debug the system.
• Security assurance. The platform monitors agent performance, identifying anomalies or potential attacks.
• Accuracy guarantee. Suncorp has developed a library of 100 different controls for various AI applications, enabling 99% accuracy in complex tasks such as determining the cause of loss for insurance coverage.

Human involvement is maintained: complex cases that an agent cannot handle are escalated to a human, and all claims rejected by an agent undergo mandatory human review.

Source: itnews.com.au

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