Chief Manager - Renewals

Job Description

Job TitleChief Manager - Business Planning AnalyticsLocationGurgaon 90CDepartmentOperations - RenewalsFunctionOperationsReporting toAVP –RenewalsBand4B

Key Responsibilities:

Lead the end-to-end business planning process for renewals collections, and surrender management verticals.

Define annual and quarterly plans in alignment with business goals, regulatory requirements, and market dynamics.

Perform gap analysis and define corrective actions based on forecast vs actual performance

Build and maintain advanced dashboards and reports (MIS) tracking key performance indicators (KPIs) of Call centre like persistency ratio, surrender rates, lapse ratio, renewal collections, and onboarding exceptions.

Analyze customer behavior patterns, risk profiles, and policy trends using predictive analytics models to enhance targeting strategies.

Provide actionable insights to influence strategy and decision-making across collection and retention functions

Perform root-cause analysis of surrender cases and design data-driven interventions to reduce voluntary surrenders.

Identify and flag vulnerable or high-risk policy cohorts for early engagement.

Monitor persistency trends and design focused retention campaigns leveraging propensity models.

Analyze collections performance at a granular level (product-wise, channel-wise, cohort-wise).

Recommend strategies to improve agent and customer engagement based on analytics output.

Support digital initiatives like Autopay win-back models, Humanoid BOT targeting, and customer segmentation models.

Monitor onboarding workflows for anomalies and deviations, including KYC compliance, policy issuance timelines, and system-generated vs manual exceptions.

Establish control frameworks to reduce onboarding errors and drive process improvements.

Collaborate with Operations and Risk teams to mitigate early-stage leakage

Measure of Success:

Improvement in Persistency Ratio

Reduction in Surrender Rates (Voluntary Involuntary)

Onboarding Exception Ratio

Accuracy Timeliness of MIS Reports

Predictive Model Accuracy Effectiveness

Impact of Data-driven Interventions (collections uplift, early warning score models)

Reduction in manual effort through automation digital tools