How Digit is uing AI-led claims engine to speed up insurance settlements

India's insurance sector is entering a new phase of digital transformation, with claims processing emerging as a key battleground for customer experience, operational efficiency and competitive differentiation. As insurers ramp up investments in artificial intelligence (AI), automation and cloud-native platforms, Digit Insurance says its technology-led claims architecture is helping it significantly outperform industry turnaround benchmarks and move closer to real-time settlements.

According to Vishal Shah, Head of Data Science at Digit Insurance, the company has built its claims infrastructure around an event-driven, real-time architecture designed to eliminate delays traditionally associated with insurance workflows.

"When a claim is raised, customers are measuring us by how quickly we respond and how human that response feels. Our focus has been on eliminating friction, minimising ambiguity and enabling consistently faster resolutions at scale," Shah told TechCircle.

The insurer's performance metrics underscore the impact of that strategy. Nearly six out of ten health insurance cashless hospitalisation approvals are completed within 20 minutes on average, while 71% of motor insurance repair approvals are processed within 12 hours. Most post-policy service requests, including policy corrections and updates, are completed instantly or within two hours.

The company's approach differs from traditional insurance systems that often depend on sequential processing and multiple manual handoffs. At Digit, critical functions are automated at the point of claim intake, with documents digitally read, classified and validated as they enter the system. This allows standard claims to move through processing pipelines with little or no human intervention.

A major contributor to faster health claims approvals has been the company's ability to compress traditional decision-making layers. Instead of processing tasks one after another, multiple functions run simultaneously. Document identification, data extraction, policy verification and risk assessment occur in parallel, reducing waiting times significantly.

Digit also uses AI- and machine-learning-driven confidence models to determine how claims are processed. Claims assigned high confidence scores are automatically approved and advanced through the workflow, while complex or ambiguous cases are routed to human reviewers.

"Automation works best when combined with the right human oversight," Shah said. "The objective is not to replace human judgment but to ensure that specialists spend their time on the claims that genuinely require deeper scrutiny."

This human-in-the-loop approach is becoming increasingly important as insurers seek to balance automation with governance, compliance and risk management. While a growing share of claims processing can be automated, high-value claims, complex medical cases and transactions flagged by risk indicators continue to require human intervention.

The insurer's cloud-native technology stack has also enabled it to scale processing capacity during periods of high demand. However, Shah acknowledged that some challenges remain beyond the reach of technology alone.

In motor and health insurance, poor-quality vehicle images, non-standard hospital documentation and ambiguous medical records can lower automation confidence levels and necessitate manual review. Certain claims, by their nature, also require detailed assessment regardless of system sophistication.

"Some bottlenecks are structural rather than technological," Shah said. "Dynamic load management and intelligent prioritisation help us ensure these exceptions do not impact overall service levels."

Digit is also expanding the use of AI-led image analytics and natural language processing across onboarding and claims workflows. Automated decisions are assigned confidence scores, while lower-confidence cases are escalated for review. Manual corrections are then fed back into machine learning models, creating a continuous feedback loop that improves accuracy over time.

Travel insurance offers one of the clearest examples of automation's growing role. During FY26, 75% of domestic non-medical travel claims were processed through automated systems, with nearly 79% of those claims initiated within 15 minutes. According to Shah, access to pre-validated booking records, travel timelines and policy data from a unified data environment enables such rapid processing.

The benefits extend beyond operational efficiency. Faster settlements are contributing to improved customer satisfaction and stronger renewal behaviour, while automation is helping reduce manual workloads and improve the early detection of claims leakage.

Looking ahead, Digit expects the industry to move steadily toward touchless claims processing for low-complexity scenarios. Advances in AI models, broader access to verified data and improvements in straight-through processing are expected to increase the share of fully automated claims over the coming years.

While human oversight will remain critical for complex cases, Shah believes real-time settlement is quickly shifting from an industry aspiration to a customer expectation.