Author name: Tanuka

credit default risk

How Restructures, Write-Offs and Delinquencies Impact Credit Default Risk

Credit default risk is a critical consideration for lenders and investors in the financial world. It refers to the likelihood that a borrower will fail to meet their debt obligations. This ultimately leads to default. Several factors contribute to credit default risk, including economic conditions, borrower characteristics, and the performance of loan portfolios. Evaluation of […]

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Expected Credit Loss

Expected Credit Loss: Basel III vs IFRS 9 – A Comparative Analysis

Expected Credit Loss refers to the estimated amount of loss a bank can expect to incur on a financial asset over its lifetime. In the landscape of financial risk management, understanding and implementing effective credit loss models is crucial for financial institutions worldwide. The two prominent frameworks, Basel III and IFRS 9, play pivotal roles

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Data Wrangling

Data Wrangling : Understanding, Why its Important

Data wrangling has become the primary process to remain competitive for organizations. Data is the backbone of the digital age, and with growing volume leading to data explosion, the need for effective data handling becomes paramount. Among the essential processes in the realm of data science is Data Wrangling. This article delves into the intricacies

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Fraud detection in banking

Fraud Detection in Banking Industry using Data Analytics

Fraud detection in banking industry is becoming crucial day by day. In this digital age, where every transaction leaves a digital trail, the banking industry faces a constant battleground: fraud. From credit card skimming to sophisticated cyberattacks, fraudsters are becoming increasingly cunning, leaving banks scrambling for solutions. But amidst this digital arms race, a powerful

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Significance of EAD in Calculating ECL in the Banking Industry

In the dynamic world of banking, risk management plays a crucial role in ensuring financial stability. One crucial aspect of this is the calculation of Expected Credit Loss (ECL). This process involves various components, and among them, Exposure at Default (EAD) holds a key position. In this article, we will delve into the importance of

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Data Analytics in Finance and Banking Sector

The finance and banking sector is one of the most data-rich industries in the world, generating vast amounts of data on a daily basis. The traditional banking institutions have been collecting customer data for decades, but with the emergence of fintech companies, the competition has become more intense, and banks are increasingly turning to data

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