Banking Analytics

The financial world thrives on predictions. Understanding and incorporating macroeconomic scenarios and probability weights are pivotal when it comes to calculating Expected Credit Loss (ECL). This blog explores the relationship between macroeconomic factors and credit risk assessment. Let’s shed some light on the process of assigning probability weights to various economic scenarios. By delving into

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

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

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

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