Chapter 1: Data Alchemy in Insurance: A Catalyst for Improving Financial Inclusion Levels and Insurance Penetration

Introduction: Data play a very significant role in solving the problem faced at micro and macro levels. Financial inclusion and insurance penetration have been a major problem of developing economies. These two economic indicators can be strengthened with the emergence of data alchemy.

Purpose: The present research study is conducted with the objective of measuring the impact of technological infrastructure, data alchemist techniques, and regulatory environment on insurance penetration and financial inclusion.

Methodology: To meet the research objectives, data were collected through a random sampling technique from the insurance agents in Mumbai, which can be considered the heart of insurance in India. On the data collected, the partial least squares (PLS) algorithm was applied using smart PLS software. PLS is a statistical method used for predictive modeling and analysis of complex data with multiple variables.

Findings: The final results revealed a significant relationship between data alchemy techniques and financial inclusion. Also, a significant impact on the financial inclusion level of the regulatory environment is also recorded. However, in a developing country like India, currently data alchemy techniques are not significantly impacting insurance penetration.