Nayansee Rai

Customer Experience and Journey Optimization.

• Conducted five usability studies with over 80 participants to refine health package purchase journeys (compare features, language toggle, assisted calling support) directly improved conversion rates and decision confidence.
• Leveraged 15+ heatmaps, 500+ session recordings, and user events to propose interventions for lab booking journeys (voucher application, location updates, lab/test selection), resulting in a 25% increase in cart transactions.
• Designed and executed a task-based study with over 24 doctors, introducing templated medicine, dosage, and frequency selection, which reduced prescription filling time by 50%.
• Rolled out high-impact features that delivered a 67% increase in daily prescription volumes and a 48% growth in doctor acquisition.
• Devised and launched GTM for an Incentive Program targeting Relationship Managers, which drove an 83% increase in platform usage during the pilot phase.
• Launched personalized homepages and user profiles, achieving 85% adoption within the first month, and contributing to 105% MTU growth in the B2C journey.
• Partnered with Exotel to streamline integrations and improve system activity by 30%.

AI & Automation Initiatives

• Introduced 'Health Saathi' – a generative AI bot with over 10,000 daily active users, boosting self-service from 30% to 65%. Automated resolution of over 10,000 monthly queries (claims, bookings, policy updates) at 85% First-Time Resolution (FTR) has reduced first-level call volume by 35%.
• Launched Smart IVR powered by speech synthesis, driving monthly transactions up from 12,000 to 20,000 (a 66% increase), with a 70% call-to-book success rate.
• Automated 19,000+ monthly claim-related emails (registrations, status follow-ups) via generative responses, achieving a 70% auto-closure rate at over 90% accuracy.
• Deployed contextual 'Raise a Query' triggers, lowering journey drop-offs by 17% for reimbursements and cashless claims.

Fraud, Risk & Claims Workflows

• Managed a team of 10+ investigators and collaborated with 5+ data scientists, scaling suspicious claim identification from 2% to 8%, and raising investigation coverage from 40% to 100%. Each investigator successfully closed 50 to 60 manual cases per day.
• Developed an AI-powered fraud detection framework (ChatGPT APIs), achieving over 85% anomaly detection accuracy, and cutting manual workload by 60%.
• Built real-time fraud dashboards with AI insights, reduced case resolution TAT from 2 days to 1 hour, boosting fraud resolution rates by 95%.
• Designed a machine learning–based risk scoring system for customers and providers, which saved ₹40–50 lakh per month in payouts.
• Conducted post-facto analysis to identify missed fraudulent claims, which enabled ₹10–20 lakh per month in recoveries.
• Owned and launched OCR-based claim status prediction, increased the first approval rate by 25%, and reduced escalations by 40%.
• Partnered on policy wordings, SOPs, and T&Cs for corporate offerings; conducted demos of abuse workflows for 50+ enterprise clients (e.g., Credit Suisse, Nvidia) in collaboration with Risk, Underwriting, Account Management, and Legal teams.
• Identified high-demand/no-network areas, enabling the onboarding of 100+ providers across regions.