A comparative analysis of conventional and modern methods of credit risk assessment in financial institutions: implications for micro, small and medium enterprises (MSMEs)
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Date
2023-12Publisher
Brac UniversityAuthor
Hossain, NabihaMetadata
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This report is a culmination of what I have garnered from my undergraduate classes and from the experience of my three-month internship period. Familiarizing myself with the corporate sector and gaining practical experience helped understand the academic knowledge in practice and prepare this report overviewing the three chapters discussing my experience, the organization and the research topic.
Beginning with the first chapter, the information of the student, myself, at the allocated organization during the internship period. Additional details such as work place tasks, contribution to the organization all are addressed. From the three-month internship period, it was possible to build a bridge from the academic world to the corporate sector. Majoring in finance, and being in a financial organization such as IPDC Finance made it possible to see the reality of finance industry and the operations in-person and in detail.
Moving to the second chapter, the organization part, covers all sectors of operations conducted by the organization, IPDC Finance. Management practices, marketing practices, financial performances & accounting practices, as well as the industry and company analysis. In the end of the chapter, certain recommendations are further provided based on the research done on the organization.
Finally, in the third chapter, that is the research on “A Comparative Analysis of Conventional and Modern Methods of Credit Risk Assessment”. The topic dives into detailed analysis of the conventional methods being used. The report includes an example of memo, that is used by IPDC when assessing credit and is an important document when considering loan approvals. Further, the report analyzes the benefits of the modern methods, that are potential alternative tools to assess credit risk. This includes usage of Artificial Intelligence and Machine Learning in credit risk management, that will erase human error, biasness and such. This will be highly beneficial for the micro, small, and medium enterprises (MSMEs) which are often subject to not receiving the required funding due its nature and scale.
The report comes to a conclusion to see the visible scopes and opportunities available if the modern methods are implemented by the financial institutions for its credit risk assessment