Thought Leadership
Credit risk management in the post-pandemic era
The year that was, and key trends in 2021
Credit risk management continues to be critically important across financial institutions. In the last year, the top concerns faced by credit risk professionals has dramatically changed, owing to the economic downturn, COVID-19 pandemic and worldwide disruption. 2020 essentially turned the concept of credit risk management on its head. With perspectives changed forever, what’s to become of credit risk management in 2021?
Staying sure-footed in the new normal
Credit monitoring and preventive intervention with real-time Early Warning Systems
The large-scale disruption brought on by the new normal calls for financial institutions to exercise more caution when it comes to managing their lending activities. Technology-aided solutions, like the real-time Early Warning System developed by BCT Digital, are changing the game – by detecting systemic flaws and vulnerabilities, and upholding the sanctity of the credit management process. On a macro scale, these systems will be instrumental for FIs to build the systemic stability and competitive advantage needed to thrive in the new normal.
Making big leaps in Banking with Big Data
The banking risk management scenario is steadily evolving. The system of compiling data from information silos and feeding them into manual spreadsheets is now fading into the past.
rt360 and the Risk-Adjusted Return on Capital (RAROC) calculator
The struggle that banks face in combating credit risks is multi-dimensional. Foremost among them is determining the right capital allocation and pricing for different sources of their revenue.
AI-based Models and Model Risk
AI-based models are more susceptible to certain risks than their conventional counterparts, unless they are put through proper governance and oversight mechanisms. We will look at some of the model risks AI models may be susceptible (over its conventional counterparts).
Machine Learning and Credit Fraud Detection
Machine-Learning-based algorithms lend themselves as useful tools for analysing the possibilities of credit fraud. This is typically done by running the algorithms on various transactional data and analysing for hidden patterns.
Measures to maintain liquidity and asset quality through good governance
Many NBFCs are structured in a manner that leaves room for inherent asset-liability mismatch. If we take the example of infrastructure HFCs, usually the assets are long-term, while the funding is short term.
Managing credit risk in a volatile financial market with Early Warning Systems
Collaborating, brainstorming, improvising and iterating without boundaries. It’s every innovator’s dream. For the Indian banking industry, this dream has finally arrived – heralding an era of extraordinary change and progress
Innovation Sandbox and Indian Banks – A close look at one of RBI’s most visionary initiatives of our time
Collaborating, brainstorming, improvising and iterating without boundaries. It’s every innovator’s dream. For the Indian banking industry, this dream has finally arrived – heralding an era of extraordinary change and progress
Practitioners’ Insights On Credit Monitoring
In an industry-first survey on Credit Monitoring Practices of Indian Banks, Bahwan CyberTek highlights the need to take a holistic approach to credit monitoring with organizational ownership combined with an urgent need for automation as well as data integration. Bahwan CyberTek, a leading global provider of innovative software products and solutions, has launched a report based on India’s first ever survey on ‘Credit Monitoring Practices of Indian Banks’; the report titled ‘Practitioners’ Insights on Credit Monitoring’.
Read More
