The deadline to implement Basel IV is just a year away for many banks. Basel IV has been through many iterations over the last few years. Implementation has been deferred from 1 January 2023 to 2024 by the Basel Committee on Banking Supervision.
The most recent updates followed the collapse of regional US banks such as Silicon Valley and First Republic. The framework aims to prevent further failures by ensuring that banks can calculate risk profiles for customer credit applications more accurately and have sustainable levels of capital in reserve.
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These requirements rely heavily on analysis of contextual, historical data and past trends to inform forecasts, risk models and reporting. Data will also be used to demonstrate governance via an auditable data chain.
However, questions remain as regards some banks readiness to comply. Moreover, recent research from Cloudera shows compliance is the main data management concern for 80% of EMEA IT decision makers.
“Despite Basel IV being amended and pushed back by the BCBS, we know for certain that it’s coming. Banks must lay the groundwork and develop a modern data architecture otherwise they will face compliance headaches. This will enable banks to react quickly to any regulatory changes. And ensure compliance from day one,” said Joe Rodriguez, Sr, MD, Financial Services, Cloudera.
To get ready for Basel IV and optimise use of data, Rodriguez has a number of recommendations for banks.
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By GlobalDataUtilise AI to cut complexity
For banks – particularly challengers and smaller organisations that have limited compliance and legal teams – AI can be a useful tool to help rapidly summarise the key points of Basel IV, which spans more than 1,800 pages. By laying out the requirements in a coherent, easy-to-consume fashion, banks can map them against their own data practices. This will help them gain a deeper understanding of what changes are needed, if any, in order to comply.
Draw on new data sources
Traditional credit scores can be unreliable. Banks need to draw on new sources of data when it comes to credits risk assessments. Banks need the capability to be able to analyse alternative sources of market intelligence. Examples include such as late payment or social media data, to build a better picture of customers risk profiles. This not only helps to ensure more accurate assessments. It can enable banks to offer services to new customer that were previously underserved.
Drive value from data, no matter where it resides
Cloudera’s research shows that 66% of banking and finance organisations in EMEA have a hybrid cloud model. This is where data sits on the cloud and on-premise environments. This adds to compliance complexity, meaning many banks are unable to easily retrieve data and make it auditable. To ensure that banks can deliver insight quickly and accurately report compliance, they need to be able to access their complete data set, no matter where it resides.
Refine risk models and continuously test them
Banks need to be able to regularly fine tune their risk models to ensure they’re as accurate as possible. With Basel IV placing risk assessment under the microscope, they must have constant access to all their data rather than just a subset, in order to continuously refine and test models.
Apply compliance always and everywhere
Many banks operate across multiple geographical locations. While most will already have a rigorous set of data policies, applying them across territories is a challenge. So, banks need to ensure they have the ability to apply policies to all their data, regardless of where it resides and what platforms it is on. It’s vital that compliance is always-on and everywhere.
“The compliance landscape continues to evolve. Banks can’t afford to stand still,” added Rodriguez. “Beyond Basel IV, other regulations such as the Digital Operational Resilience Act (DORA) are on the horizon. Banks need to have the capability to move data between on-premise and cloud environments in a secure and compliant manner. Modern hybrid data architecture enables banks to maintain comprehensive audit trails at scale, while making all data available for analysis.”
