Normalized claim
Time: 40% increase
Claims settled 40% faster.
Last evidence check: Jun 1, 2026
Indian Insurers Revolutionize Claims Processing and Customer Engagement
Use case typeClaims automationUpdated Jun 13, 2026
Indian insurance companies have transformed their operations by leveraging Microsoft Power Platform to automate and digitize claims processing. Previously, these insurers struggled with inefficient manual processes, high operational costs, and the growing need for regulatory compliance and improved customer satisfaction. By implementing a combination of Power Automate, Power Apps, Power BI, and Power Virtual Agents, they digitized workflows, built AI-powered chatbots for real-time customer support, and enabled agent-centric mobile solutions. The low-code/no-code capabilities accelerated deployment and adaptation across multiple internal processes, including claims approvals, fraud detection, onboarding, and compliance reporting. Automation led to faster settlements, reduced fraud, higher customer satisfaction, and lower costs, solidifying digital transformation in India’s insurance sector.
- Organization
- Indian Insurance Company
- Industry
- Insurance
- Location
- India
- Published
- February 2025
Reported outcomes
Time: +40%
Time & speed
Risk & safety: −30%Customer experience: +20%Customer experience: −15%
Catalog median for time & speed deployments: +59% across 138 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Quantified impact: 30% decrease
Fraud rates cut by 30% in 6 months.
Last evidence check: Jun 1, 2026
Normalized claim
Quantified impact: 20% increase
Customer satisfaction increased by 20%.
Last evidence check: Jun 1, 2026
Normalized claim
Productivity: 25%
Agent productivity up by 25%.
Last evidence check: Jun 1, 2026
Normalized claim
Quantified impact: 15% decrease
Churn reduced by 15%, regulatory reporting workload cut by 30%.
Last evidence check: Jun 1, 2026
Normalized claim
Quantified impact: 30% decrease
Churn reduced by 15%, regulatory reporting workload cut by 30%.
Last evidence check: Jun 1, 2026
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Indian Insurance Company
- Provider
- Microsoft
- Maturity
- Production
- Linked source
- mobiosolutions.com
Previously, these insurers struggled with inefficient manual processes, high operational costs, and the growing need for regulatory compliance and improved customer satisfaction
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 4
- 1Automated Claims Processing with Power Platform
- 2AI-powered Customer Service Chatbots for Insurance
- 3Real-time Compliance Reporting for Insurers
- Implemented Microsoft Power Platform (Power Automate, Power Apps, Power BI, Power Virtual Agents).
- Automated claims submissions, approvals, and compliance processes using low-code tools.
- Deployed AI chatbots to handle customer inquiries and policy questions 24/7.
- Used Power BI for real-time risk and compliance analytics.
- Enabled fraud detection using AI and ML workflows integrated with existing systems.
- Claims settled 40% faster.
- Fraud rates cut by 30% in 6 months.
- Customer satisfaction increased by 20%.
- Churn reduced by 15%, regulatory reporting workload cut by 30%.
- Operational costs lowered significantly.
Sources & evidence1
Evidence: Medium60/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Quantified outcome available
- Technical implementation details available
- Recent evidence check available
- Last evidence check: Jun 1, 2026.
Live sourceStill referenced
The case's original source is still reachable.
- Cited source last checked Jun 1, 2026 — ok (0/1 broken).
Measures whether this deployment's public evidence persists — not whether the system is still in production.
Published: Feb 10, 2025Publisher: mobiosolutions.com
AI-generated summary. Verify important details with the linked sources before relying on this case.
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