AI Driven Household Financial Health Index

Author(s)	Ms. SRI ABIRAMI K, Mr. RENGARAJAN V, Mr. KARTHIKEYAN V
Country	India
Abstract	Financial wellness in a household is currently one of the focal aspects of socio-economic policy-making. However, traditional evaluation processes mostly utilize uni-variate measurements such as income, debt-to-income ratios, and credit scores. In this paper, the Financial Health Composite Index (FHCI), a scientifically sound and empirically validated measurement tool based on the dimensions of financial stability, financial risk, and behavioral expenditure discipline will be discussed. Based on the analysis of data obtained from the Survey of Consumer Finances dataset of 2022 using multiple machine learning algorithms like Gradient Boosting, Random Forest, Logistic Regression, Neural Networks, and Ensemble Learning techniques, the paper will classify household financial health into three categories—Good, Medium, and Poor, with Gradient Boosting having the best accuracy rate at 76.36%.
Keywords	Financial Health Composite Index · Gradient Boosting · Survey of Consumer Finances · Household Financial Segmentation · Machine Learning Classification · Financial Stability · Risk Vulnerability · Behavioral Finance
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-05-23
DOI	https://doi.org/10.36948/ijfmr.2026.v08i03.79407

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