The shift toward AI-powered credit scoring for more accurate borrower assessment Rising importance of alternative datasets, including behavioral and non-traditional indicators Adaptive pricing methodologies that respond to real-time market changes Challenges of modelling credit risk during periods of heightened economic uncertaint
Understanding the geopolitical forces reshaping the banking landscape Resilience strategies mitigating disruptions to energy, financial, andtrade flows Country risk models incorporating political stability and market exposuredata Geographic diversification as a tool for preventing concentration risk
Expanded borrower evaluation using unconventional and digital data streams Early warning signals derived from online behavior and real-time market insight Dynamic portfolio realignment based on evolving macro conditions Regulatory expectations surrounding the responsible use of alternative datasets
Model Risk Management - balancing act between internal and regulatory best practices
Modern continuity strategies for cyber incidents and technology outages Crisis management frameworks enabling rapid multi-channel response As digital ecosystems expand, banks must balance efficiency, speed, security, and continuity. How can institutions remain resilient in a world of real-time risk? Regular stress testing and simulations to strengthen preparedness Clear communication protocols for escalation and coordination
Managing ethical, fairness, and systemic risks linked to AI adoption Governance structures designed for fast-moving digital innovation Forward-looking risk methodologies suited for frontier technologies
Responding to new laundering pathways emerging with digital platforms Transaction monitoring methodologies covering cryptocurrencies and new assets Data-driven customer scoring models to strengthen digital onboarding Industry collaboration and intelligence sharing for stronger defense
Finding the balance between compliance, risk management, assurance and resource allocation practical challenges and lessons learned from AML, GDPR, Outsourcing Guidelines, DORA and AI ACT implementations
AI-enabled reporting capabilities delivering compliance at scale Continuous compliance visibility across institutional operations Integrated GRC platforms supporting holistic risk oversight Systems designed to proactively anticipate regulatory change
Modern approaches to evaluating and overseeing strategic vendors Real-time risk tracking across critical digital supply chains Continuity strategies addressing disruptions or vendor failures Structured exit and disengagement frameworks for high-risk relationships
As digital ecosystems expand, banks must balance efficiency, speed, security, and continuity. How can institutions remain resilient in a world of real-time risk?
Governance frameworks built for advanced and automated models Machine learning for fraud detection and enhanced risk intelligence Explainability and transparency to meet evolving regulatory demands Continuous monitoring ensuring consistent model reliabilit
Leveraging AI and machine learning to enhance credit scoring, limit management, and early-warning indicators Using alternative and non-traditional data sources while ensuring explainability and fairness Balancing innovation with regulatory compliance, data governance, and ethical risk considerations
Transformation of traditional credit risk models through advanced AI and machine learning Expanding the use of alternative and behavioral data to enhance borrower profiling Dynamic risk-based pricing strategies aligned with real-time market conditions Key challenges and limitations of credit risk modelling in times of macroeconomic instability
How AI agents can support the Financial and Credit Risk teams in monitoring and managing risk
Move from "Gatekeeper" to "Guardrails": Stop treating risk management as the final hurdle before launch. Instead, embed risk controls directly into the Agile design and DevOps pipeline. This allows teams to innovate quickly while ensuring seamless, compliant deployments by default. Digitize the Framework Itself: You cannot govern a digital ecosystem with analog tools. Replace static, manual risk registers (spreadsheets and slides) with automated monitoring and data-driven Key Risk Indicators (KRIs) that match the velocity of your technology. Prioritize Resilience Over Perfection: In complex digital environments, 100% prevention is impossible. Pivot your framework to focus on Operational Resilience—specifically, how quickly you can detect issues and how fast you can recover when systems fail. Plan for Turbulence (The Human & Process Factor): Transformation is difficult and skilled talent is scarce. Don't just plan for technical failure; prepare a clear governance blueprint for execution failure. Ensure you have the right oversight in place for when resources are stretched or plans deviate
