Lifecycle-based analytics of auto-renewal policies, analysing customer awareness, timing risk, escalation drivers, and preventable complaint patterns.
End-to-end Power BI dashboard for Shield Insurance tracking revenue, customers, DRG/DCG growth, trends, and segmentation by city, sales mode, age group, and policy ID.
Synthetic personal-lines insurance portfolio built as a governed digital twin, with dataset freezing, validation gates, and actuarial realism.
Insurance policy and claims analytics report built with SQL Server integration, DAX lifecycle logic, and automated scheduled refresh.
3-page Power BI insurance report with executive KPIs, drill-through customer details, and feedback sentiment insights using a word cloud.
Interactive Power BI dashboard built during an internship at AtliQ Technologies for Shield Insurance, analyzing ₹989M in revenue across 26K+ customers. Covers sales channel performance, age group segmentation, and monthly trends using a star schema data model, DAX measures, and Power Query transformations.
SQL + Power BI case study detecting claim severity & leakage: reserve adequacy, vendor IQR outliers, missed subrogation/late FNOL, duplicate payments. End-to-end T-SQL (staged → core → mart) + executive dashboards.
Production-style regression project for predicting insurance claim amounts using advanced modeling techniques, feature analysis, and business-driven insights.
End-to-end motor insurance analytics project using a two-stage (hurdle) modeling approach to predict claim occurrence and claim severity. Combines business analysis, machine learning, and risk insights to support underwriting, pricing, and claims optimization in General (P&C) Insurance.
Production-style ML system for automated insurance claims decisions using a SQL gold dataset, rule + model scoring, FastAPI inference, and explainable outputs.
End-to-end BI project simulating and analyzing a car insurance portfolio with 1M+ records to derive insights on claims trends, loss ratio, and business risk using Python, SQL and Power BI.
End-to-end analytics project testing whether Australian macroeconomic indicators (ABS, RBA, APRA) can predict general insurance claim severity 2–4 quarters in advance. Includes lead-lag correlation analysis, OLS/Ridge/Lasso regression, stress-test scenarios, and an interactive Streamlit dashboard.
> Shield Insurance Analytics > A data-driven approach to analyzing revenue trends, customer segmentation, and sales mode performance in the insurance sector. This project provides structured insights to optimize engagement strategies, enhance policy targeting, and improve overall business decision-making.
Predicting insurance charges and identifying key risk divers using regression and regularization.
CAS Workers Compensation Reserving Case Study. Loss Development Factors, Catastrophe/Outlier Analysis, Ultimate Loss Estimates, Frequency-Severity.
Power BI dashboard for PRISM Insurance — tracks ₹5.98M premium, ₹600.55M coverage & ₹16.91M claims across Auto, Health, Life, Travel and Home policies
Customer behavior & revenue analysis using Power BI
xploring Determinants of Healthcare Expenditures and Outcomes Using Statistical Analysis
Insurance risk analytics for 10 Academy. Includes EDA, DVC, A/B testing, and XGBoost modeling for claim severity and pricing, with SHAP analysis.
Geospatial underwriting lab for climate, terrain, and exposure-informed insurance decisions.
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