Application of AI in Credit Analysis for SME Financing

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Vidya CM, Geetha Rajaram


Financial providers typically evaluate business statements of finances, cash flow statements, personal financial statements, and business plans as part of their traditional credit research process for any entity. This paper demonstrates how financial technology, or Fintech, may speed up determining an entity's creditworthiness, especially for SMEs. A main source of difficulty for small and medium-sized businesses seeking financing to launch or expand their operations is a deficiency of concrete data and a solid track record.  The issue of information asymmetry affects SMEs. The SMEs might not be able to supply the same information because of a lack of financials, but the financial providers need additional details to complete the credit proposal. In the present situation, financial technology pitches in the form of big data, in the absence of concrete data. Every second, an enormous amount of data is gathered from multiple sources, social media platforms, online and offline transactions, and other sources. The new era of credit analysis is centered on behaviour among customers. Everything from preferences for purchased products to likes and dislikes expressed on social media platforms is captured through "Big Data." Everything is available in minutes, allowing one to determine whether or not a person deserves credit quickly. All of these are investigated using intricate mathematical calculations to examine information sequences within a vast amount of data. This study investigates how Fintech can shorten the time needed for credit examination.

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Vidya CM, Geetha Rajaram. (2024). Application of AI in Credit Analysis for SME Financing. European Economic Letters (EEL), 14(1), 634–645. Retrieved from