IRB survey: Could AI reshape internal ratings-based models?
ArticleSurvey insights into internal ratings‑based (IRB) models, regulatory challenges and the role of AI under Basel 3.1.
Financial services firms spend 50-70% of their change budget on regulatory programmes.
New regulations continuously emerge and you need to scan, assess, and respond in an effective, timely, and sustainable manner.
Ensuring repeatable processes to effectively respond to regulatory change is an important aspect of having an ‘effective control environment for managing regulatory change’.
Ability to horizon-scan, evaluate, and respond to multiple regulations across jurisdictions, products, and customers. This is critical for regulated firms.
Industry approximation is that 50% of regulatory change is not executed well, costly, and at times results in remediation and regulator censure. Regulatory assurance is an effective method to ensure content-based intervention. An early warning signal and course correction can ensure the regulation is implemented right first time in a client/customer-friendly, cost effective, and sustainable manner.
RegTech is any technology, automation, or data-based solution which results in simplifying regulation, reducing cost, and increasing the confidence of meeting regulations in a sustainable manner.
Our regtech enablement model is a tried and tested approach to ensure real benefits of implementing a solution. Regtech enablement is achieved through identification and selection of the most appropriate software, with effective implementation.
A number of critical conduct, prudential, tax, and financial crime regulations can be solved through rigorous data-led solutions. Examples include DGSD/FSCS, FATCA/CRS, MIFID II, Dodd-Frank EMIR, 5th AMLD, etc.
Architecting a solution which is data-led and with a common data model results in reducing the work-load, improving completion and accuracy, and minimising impact on the end customers. Recent ‘Dear CEO’ letters have focussed on regulatory reporting and data quality issues.
A number of critical regulatory reports and attestations across prudential, conduct, financial crime, and data protection regulation requires regulatory operations.
Unfortunately, regulatory operations are heavily manual, have issues in offshore/onshore mix, skills and capability gaps, and are costly.
Regulatory intelligence, data-led solutions and automation can result in cost effective, sustainable, and client-friendly regulatory operations functions.
You can get insight and guidance from our expert teams across multiple key areas:
Survey insights into internal ratings‑based (IRB) models, regulatory challenges and the role of AI under Basel 3.1.
We unpack the FCA's motor finance redress scheme rules, and cover the regulators' operational incident and third-party reporting.
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