In recent years, UK banks have increasingly found themselves allocating a significant portion of their risk budgets to Internal Ratings-Based (IRB) remediation programmes. This trend underscores a pervasive underestimation of the challenges involved in building and operating effective IRB models. As we look ahead, it is clear that a more effective approach is not only possible but essential for navigating the upcoming waves of regulatory scrutiny and operational demands
Our experience - as well as regulatory feedback - shows that robust governance and senior ownership is important, reflected in committee membership and a culture of review and challenge of key judgments
One critical issue is the composition of the teams tasked with model development. While these teams often possess substantial IRB expertise, they frequently lack robust coding skills. Although banks have established enablement and engineering teams to bridge this gap, the collaboration between these groups is often not fully functional. As a result, much of the code remains monolithic and SAS-based, which complicates quick implementation and increases the likelihood of errors. This disconnect highlights the need for a more integrated approach that combines modelling acumen with technical proficiency to enhance the efficiency and accuracy of IRB model development
To address these pain points effectively, we recommend three key strategies. First, creating mixed teams of modellers and experienced coders can significantly enhance the development process. By integrating technical expertise with modelling knowledge, banks can improve workflow efficiencies. This collaborative approach not only streamlines the development timeline but also ensures that the initial code is closer to a deployable state. We have also found firms benefit from code sharing through platforms like GitHub, and establishing rigorous code review processes. Code libraries and ‘scaffolding’ (re-usable code structures) also make model development more controlled, repeatable and efficient.
Second, when using external support, implementing risk-sharing arrangements for delivery can lead to more successful and cost-effective outcomes. By fixing delivery costs while also aligning incentives for successful model results, banks can attract the right level of seniority and mix of resources necessary for effective model development. This shift in focus can help mitigate the risks associated with failed deliveries, ultimately leading to better resource allocation
Lastly, fostering greater involvement of internal stakeholders throughout the model development phase is crucial. By explicitly engaging these stakeholders and focusing on their understanding of risk management practices and the operational environment, banks can ensure that modelled approaches are more closely aligned with business needs. Additionally, enhancing the education of business units about IRB processes can facilitate stronger collaboration and reduce tensions between modelling teams and business units, ultimately improving the overall effectiveness of IRB models
In conclusion, while the journey towards effective IRB remediation is challenging, there is a clear path forward. By addressing the pain points head-on and adopting a more integrated and collaborative approach, UK banks can not only ease the current IRB pain but also develop sustainable modelling capabilities going forward. If you would like to get more information on how we organise our teams in our risk-sharing agreements on IRB delivery, feel free to reach out
This post was authored by Cem Dedeaga, a partner in our Finance and Risk Practice, based in the London office, specialising in prudential credit risk topics. With extensive experience across a diverse range of financial institutions, Cem leads large-scale prudential credit analytics delivery (IRB, IFRS 9) in the UK and Europe. His expertise encompasses the delivery of comprehensive credit risk models and frameworks, helping banks improve compliance with regulatory standards