Promoting Financial Inclusion through AI-Based Risk Assessment in Microfinance Institutions

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@article{1709201,
      author = {Sonu Pradheen Kotapati, Gopi Chand Edara, Bhavana Kuchalapati, Venkata Revanth Kollipara, Brahmini Kotapati},
      title = {Promoting Financial Inclusion through AI-Based Risk Assessment in Microfinance Institutions},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {7},
      number = {2},
      pages = {806-812},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1709201.pdf},
      abstract = {The study looks at applying AI-based methods to assess risk in microfinance institutions (MFIs) to help include underprivileged communities in developing countries in the financial sector. The focus of the study is to deal with the difficulty of providing credit to those who do not have a standard financial background by considering alternative details like utility payments and online actions. This research uses a mix of approaches, by analyzing default rates from loans and looking in-depth at how AI tools such as CreditVidya and Lenddo, work in places with few resources. The study?s findings indicate that AI can cut loan defaults by more than 20%, making it safer and possible for MFIs to lend to borrowers they hadn?t previously considered. The study demonstrates that AI helps ensure that credit rating is fair and clear which promotes trust between lenders and borrowers. The blend of AI in this field both increases borrower success and helps improve the economy for underprivileged areas. As head of the team, I outlined the research approach, looked at the data and pulled together lessons from several case studies to give a clear summary of AI in microfinance. With this work, more is known about how AI can support financial inclusion in a sustainable and ethical way, supporting MFIs that hope to use AI.},
      month = {August},
  }