Purpose: The purpose of this study is to develop a better method of assessing the creditworthiness of informal MSMEs in India. Using such hybrid design of fuzzy AHP and fuzzy TOPSIS, the intention of the project is to provide better access to financial products for these types of businesses which struggle because they do not have documentation, credit history and other common forms of supporting data.

Design, Methodology, and Approach: The study proposes a hybrid methodology, which is the combination of fuzzy Analytic Hierarchy Process (AHP) and TOPSIS, to evaluate and rank creditworthiness of MSMEs. A survey of 34 MSMEs led the research team to identify 11 influential factors in credit assessment. Expert insights through fuzzy pairwise comparisons were used to prioritize these factors, including GST filing, digital presence, and transaction behaviors. As a means of coping with the imprecision regarding the alternative evaluations, triangular fuzzy numbers were applied, and TOPSIS was applied to rank the alternatives according to the criteria-weighted values.

Findings: The most important variables in predicting creditworthiness included GST filing, the demographics of the business, and loan repayment behavior. Also, information gleaned from app usage, online sales, and social networks could supplement and inform other forms of evaluation. Among their findings are validations that use of these digital signals and measures of personality can be as effective as or exceed traditional forms of assessment. Customer feedback and relationships with vendors were also seen as important in determining the risk of MSMEs.

Limitations of the Research: The existing study relied on samples from particular sectors, and on the veracity of self-reported, non-traditional data. The need for broad application and effectiveness requires additional validation across larger and more diverse cohort of MSMEs.