Avg. Withdrawal Rate (Annual)
12.5%
Most Common Reason
Housing
Avg. Age at Withdrawal
38 Years
Members Analyzed
1.2 M
Reasons for Premature Withdrawal
Distribution of stated reasons for EPF withdrawals.
Aggregate Fixture Retention Curve
Deterministic educational curves over synthetic aggregate cohorts; not individual predictions.
Survival Analysis: This model estimates the time until an event (e.g., withdrawal) occurs. It helps understand how long different member segments tend to stay invested.
Withdrawal Behavior Clusters
Illustrative aggregate cohorts defined in the fixture; not model-discovered segments.
Clustering: This technique groups members with similar characteristics and withdrawal behaviors, allowing for targeted interventions.
Key Factors Correlated with Withdrawals
EPFO: Data-Driven Policy & Stability
- Identify vulnerable member segments needing support.
- Inform targeted financial literacy and advisory programs.
- Refine withdrawal policies to balance member needs and long-term savings.
- Improve overall member retention and scheme sustainability.
- Enhance long-term financial stability of the EPF corpus.
Research: Advancing Savings Behavior Insights
- Apply survival analysis and clustering to unique social security datasets.
- Generate novel insights into retirement savings behavior and premature withdrawal drivers.
- Potential for high-impact publications in economics, finance, and public policy journals.
- Explore socio-economic determinants of financial decision-making.
- Contribute to academic understanding of pension systems in developing economies.