Artificial Intelligence (AI) has become a revolutionary force in credit evaluation and SME (small and medium enterprises) financing in the quickly changing financial ecosystem. The underlying creditworthiness of SMEs is frequently overlooked by conventional credit evaluation techniques, which mostly rely on financial statements and collateral. This study contrasts traditional credit evaluation methods with AI-driven financial tools to see how they affect SME credit choices. For the study, a descriptive and quantitative research design was chosen. A structured questionnaire disseminated via Google Forms was used to gather primary data from 56 respondents. Awareness of AI tools, perceived effectiveness in evaluating credit risk, decision accuracy, transparency, processing speed, and confidence in AI-based lending systems were all evaluated by the questionnaire. Reliability testing, graphical depiction, mean score interpretation, and percentage analysis were used to assess the gathered data. The results show that AI-driven financial tools greatly improve decision consistency, shorten loan processing times, and increase the accuracy of credit risk assessments. However, due to worries about algorithm transparency, data privacy, and technology infrastructure, adoption rates are still moderate. Though it presently serves as a decision-support tool rather than a whole substitute for conventional techniques, AI-based credit evaluation is generally having a favorable impact on SME funding.
Pratika Yadav (Thu,) studied this question.