credit-risk

Commercial banks can strengthen credit decision-making by connecting credit monitoring, risk measurement, stress testing and problem-loan recovery within a single end-to-end workflow, according to an April 28, 2026 case study from S&P Global Market Intelligence. The analysis argues that fragmented Read More ... The post S&P Global Outlines Four-Pillar Model for Modernising Credit Risk Management …

South Africa credit risk is improving. Consensus data from leading local and global banks reveals 2026 sector credit trends. The post South Africa Credit Risk: Resilience and Recovery appeared first on Credit Benchmark .

Absa Bank has modernised its credit risk management infrastructure using SAS Viya on Amazon Web Services (AWS), significantly reducing reporting time while strengthening model governance and regulatory compliance. The initiative was announced by SAS on 5 August 2026. (PR Newswire) Read More ... The post Absa Bank Modernises Credit Risk Reporting with SAS first appeared on Risk Management Associat…

Bank of England research signals a shift to private credit — see why forward-looking counterparty data now matters more than ratings. The post Why Forward-Looking Credit Data Matters for Monitoring Non-Bank Financial Risk appeared first on Credit Benchmark .

Global credit default swap (CDS) market activity reached a record $41.8 trillion in 2025, surpassing... Read more CDS Market Dynamics: Five Years of Activity and a Record 2025

Every monsoon, cyclone season, and heatwave now carries a credit implication. A borrower who was “standard” in March can be under severe financial stress by August, not because their business model failed, but because a flood took out their inventory, Read More ... The post Disaster Related Credit Risk: How Banks Should Redesign Borrower Assessment first appeared on Risk Management Association of…

Private credit is now one of the biggest pools of capital in finance. By the end of this decade, it’s predicted to hit $5 trillion, with the corporate segment alone expected to roughly double over the next five years. And, driven by a pursuit of high yields, flexible terms, and quicker execution, the number of […] The post Private Credit Risk Management: 6 Challenges and How Risk Teams Tackle The…

Fitch Ratings has cautioned that the rising use of artificial intelligence (AI) in credit risk management could potentially disrupt employment and reduce tax revenues in developed economies. AI-driven automation in banking and financial services is increasingly replacing traditional credit assessment Read More ... The post AI-Powered Credit Risk May Threaten Jobs and Tax Revenues, Fitch Warns fir…

Download PDF Actionable insights from the collective credit intelligence of the world’s leading financial institutions. Introduction: A Consensus View of European Credit Risk Understanding credit risk in Europe increasingly requires a different lens – one that goes beyond traditional indicators to incorporate more forward-looking signals. The perspectives of lenders and investors with direct expo…

As global economic conditions become more complex, credit risk management is emerging as a critical priority for banks and financial institutions. Rising interest rates, geopolitical tensions, inflationary pressures, and changing borrower profiles are increasing the challenges associated with assessing and Read More ... The post Stronger Credit Risk Practices Essential Amid Rising Economic Uncert…

According to research from Deloitte, financial institutions are rethinking their credit risk technology platforms to meet evolving regulatory demands, analytical complexity and the pace of innovation. Legacy systems are increasingly seen as cost‑intensive and less capable of supporting advanced risk Read More ... The post Credit risk measurement technology trends — Deloitte analysis first appeare…

Credit card fraud has become a significant threat to individuals, financial institutions, businesses, and governments, causing substantial annual economic losses through increasingly sophisticated fraudulent activities. This research aims to enhance credit card fraud detection by leveraging machine learning algorithms and ensemble learning techniques to improve detection accuracy and model robust…