NTT DATA AI for Insurance

An enhanced service-as-software solution powered by the NTT DATA AIVista platform. Purpose-built, it combines insurance operations expertise, AI science, enterprise engineering, and managed execution so carriers can move from isolated pilots to production outcomes faster.

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Customer case study

What AI for Insurance Looks Like in Practice

When one of North America’s largest life and annuity third-party administrators (TPAs) at NTT DATA needed to modernize its policyholder services operation, NTT DATA AIVista delivered measurable results. Third-party administration refers to the outsourced management of an insurance carrier’s operations, where the TPA owns the strategy, technology, and day-to-day operations to handle all incoming policyholder requests on behalf of its insurance clients. NTT DATA runs this function for major life and annuity carriers across North America, processing nearly 4 million customer transactions per year across 70-plus transaction types, touching six systems per request.

98.5%

Accuracy

vs. 50% to 72% for leading off-the-shelf frontier models​

The Challenge
Every incoming customer request, whether an address change, beneficiary update, or form submission, passed through a fully manual pipeline spanning six systems. A 30-person indexing team manually extracted data from scanned documents and categorized each request before it could reach the 2,500-person processing staff downstream. Classification errors cascaded into compliance risks. Business rules had been codified for only three of 70-plus transaction types. And with no unified observability across systems, there was no way to measure performance, identify bottlenecks, or build a case for improvement.
25x

Fewer documents sent for
manual review

Automation potential raised from 70% to 98%

The solution
AIVista deployed specialized AI agents to replace the repeatable, mundane manual chain with a single automated pass. AIVista’s Intelligent Document Processing Agent extracts and classifies every incoming request, including multi-type documents, with confidence scores on every field. The AIVista Rules Validator Agent then connects to existing systems of record, retrieves the required context, and runs full IGO/NIGO determination in seconds. Professionals concentrate on exceptions, low-confidence cases, customer-sensitive decisions, and the improvement of operating rules. The entire pipeline runs on top of existing infrastructure, with no system replacement required.
~$7M

Estimated annual savings

For a partial TPA implementation in 2026

The results

The system achieved 98.5% accuracy compared with 50% to 72% for leading off-the-shelf frontier models, thereby raising automation potential from a frontier-model-only baseline of 70% to 98%, with 25 times fewer documents sent for manual review and an estimated $7 million in annual savings for a partial TPA implementation in 2026. This was achieved at near cost parity with commodity models. The platform also includes confidence thresholds, enforceable controls, and end-to-end traceability, which are industry prerequisites for AI-driven processing in regulated production environments.

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