Case Study
How an Indian insurance company automated payout settlements and improved customer experiences with Microsoft Dynamics 365 CRM
OUR CLIENT
This life insurance company, founded in India nearly 20 years ago, is a collaboration between a leading publicly owned Indian bank and an international financial institution. With more than 100 branch offices and nearly 10,000 employees, this joint venture combines the local bank’s extensive network and premium customer base with global insurance and risk management expertise.
THE CHALLENGE
Manual insurance payout settlement processes caused bottlenecks, errors, and re-work
The life insurance company struggled with manual processes for payout settlements—when the company pays a policyholder for specific events during the policy term, such as maturity of the policy, money-back payments, claims, surrender of the policy, and partial withdrawals. Each payout transaction involves registration, documentation, verification, payout processing, settlement, reconciliation, and relevant customer communications. With hundreds or thousands of payout settlements every day, processing teams were bogged down by errors, re-work, and bottlenecks, causing frustration for both employees and customers.
In particular, the company had a fragmented view of policyholders, causing confusion and delays. Customer service supervisors had to manually sort and assign approximately 5,000+ emails per day, a tedious, time-consuming task. Meanwhile, processing teams had to manually create cases for payout settlements, track emails, and send customer communications while toggling between multiple systems and screens.
Company leaders wanted to deploy and integrate a customer relationship management (CRM) system with its core business applications to automate processes, ensure service level agreements (SLA) were met, and accelerate payout settlements.
THE TRANSFORMATION
Automating sales and customer service tasks with Microsoft Dynamics CRM
UST implemented Microsoft Dynamics 365 CRM, a cloud-based software suite that helps manage sales, marketing, and customer service processes with AI-powered insights. We integrated the solution with the company’s insurance policy administration system, Ingenium, and its business management systems for claims, documents, grievances, and regulatory compliance, to ensure seamless workflow automations. The CRM implementation delivered:
- A 360-degree view of policyholders—to better understand customers, anticipate needs, personalize interactions, and coordinate experiences across touchpoints
- Automated email routing—using bots to sort emails based on pre-defined logic
- Consolidated document management—since all customer documents are automatically organized and stored in a central repository that business users can access as they manage payout settlement requests
- Automated workflows—to create and assign settlement cases, track service requests, send communications to policyholders, and pay settlement transactions
- Intuitive dashboards—providing real-time information with key data insights, like net asset value and surrender value, as well as SLA notifications to prioritize tasks
THE IMPACT
Operational efficiencies and better customer and employee experiences
The successful implementation engagement led to these business benefits for the insurance company:
- Increased productivity—Business process automations eliminated manual tasks.
- Better adherence to SLAs—Processes have been streamlined and employees can see dashboard notifications to help prioritize tasks and settlement cases.
- Accelerated payout processing—Fewer bottlenecks, errors, points of re-work, and manual tasks helped the company achieve faster processing.
- Improved decision-making—The 360-degree customer view, easier access to customer documents, and data-driven insights have enabled company leaders to make more informed decisions.
- Higher customer retention rates—Customers appreciate speedier payouts, fewer errors, and more informed, personalized attention, and the company can seamlessly handle large volumes of business scenarios thanks to the parallel processing and a robust rules engine for clearer decision metrics.
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