Credit Credit Risk Management Using Hybrid Methodologies

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2020-01-01
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Patil, Gitesh
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Dr. Anthony Townsend
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Information Systems and Business Analytics
In today’s business landscape, information systems and business analytics are pivotal elements that drive success. Information systems form the digital foundation of modern enterprises, while business analytics involves the strategic analysis of data to extract meaningful insights. Information systems have the power to create and restructure industries, empower individuals and firms, and dramatically reduce costs. Business analytics empowers organizations to make precise, data-driven decisions that optimize operations, enhance strategies, and fuel overall growth. Explore these essential fields to understand how data and technology come together, providing the knowledge needed to make informed decisions and achieve remarkable outcomes.
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Information Systems and Business Analytics
Abstract

Federal Home Loan Banks (FHLB) of the United States provide funding solutions and liquidity to the borrowing banks in and outside of the United States of America. This paper focuses on the borrower outside of the United States. The FHLBs heavily rely on popular rating agencies to measure the creditworthiness of the members. Available research suggests that the health of banks from the sovereign is dependent on the credit posture of the sovereign, and it is essential to review the sovereign entities of the borrower banks. All major FHLBs use the credit bureau for the credit assessment. This research questions the reliability of the rating agencies for Credit Risk Management. If credit-related information is not processed correctly or communicated properly within FHLBs, the more likely the bank might face unanticipated loss. It is imperative to measure and use improved credit risk management. This research identifies the potential drawbacks of the traditional credit risk management and points to the importance of hybrid solutions for reliable and residual credit risk solution. The paper also describes two of the prominent credit risk analysis techniques.

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Wed Jan 01 00:00:00 UTC 2020