Year: 2025
Type: article
Study design: Observational Study
Abstract: This research paper investigates the challenges and opportunities for social insurance in India and how it can provide financial protection for a rapidly-growing working population, especially in the informal sector. Despite a buoyant insurance market, social insurance schemes in India appear fragmented, underutilized, and poorly integrated. The research used a mixed-method design and drew from survey data from 100 stratified respondents and secondary data from various government and international agencies to evaluate the performance of the schemes, student knowledge of schemes and system readiness at a local institutional level. From the data, it is clear there is a vast divide between knowledge (75% awareness) of social insurance schemes, and enrolment (51%). In addition, the study notes a number of issues such as digital divide, complacency of the population, lack of trust in government institutions, bureaucratic inefficiencies, and low scheme cohesiveness. The findings also include the performance of the CAMEL and IPDMS frameworks for public and private insurers - identifying strengths and weaknesses, and moderate regression hypothesis testing confirming the effect of digital access, income, and education on participation. In conclusion, the study argues for an integrated, inclusive, and tech-enabled social insurance model should address people at risk and improve: coverage; ease of enrollment; and overall sustainability, achieved through the partnerships of public and private insurers. Policy reform should focus on disadvantaged populations such as gig workers, women, and rural dwellers. The final conclusions offer some strategic recommendations for governments to consider to make India's social insurance scheme more resilient, equitable, and appropriate for the future.
DOI: 10.55041/ijsrem50987
Author: Krishna Gupta
Institution: Galgotias University
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4411615163