In the ever-changing financial landscape of today, executives in global banking are constantly faced with the challenge of optimising capital allocation while maintaining strong risk management. The traditional methods of calculating Risk-Weighted Assets (RWAs) can sometimes limit capital efficiency. However, new technology solutions have made it possible to gain a deeper understanding of RWAs, which can unlock significant capital and enable a broader transformation of the treasury.
This blog explores Oracle's Financial Services Analytical Applications (OFSAA) and emerging technologies like Generative AI (GenAI) that can empower banks to free up capital for more profitable use.
RWAs play a crucial role in determining a bank's capital adequacy requirements. Assets held by the treasury, such as loans and government bonds, all carry different risk weights assigned by regulators. These weights directly impact the bank's overall RWA calculation and, consequently, the amount of capital it needs to hold.
Understanding and challenging RWA calculations is critical to ensure a bank is utilising capital to optimise profits. We've seen across our clients a cautious approach to calculating RWA values to meet their capital adequacy ratios, but even the smallest change in freeing up capital reserves can have a significant impact on the bottom line.
The financial landscape is evolving rapidly, and successful banks are embracing treasury transformation. Here's a deeper dive into some key trends:
Oracle OFSAA (Oracle Financial Services Analytical Applications) offers a comprehensive platform specifically designed to address the challenges of optimising a bank's capital. At a high level, OFSAA empowers RWA optimisation and treasury transformation by:
Going deeper, the platform can have a significant impact in the following critical areas:
Traditional RWA calculations rely on standardised approaches, typically set by regulators. These approaches might not always capture the nuanced risk profiles of a bank's specific assets.
By leveraging advanced analytics and data-driven modelling techniques, banks can analyse historical data, market trends, and internal risk factors to create more precise risk assessments for their specific loan portfolios and counterparties.
By utilising these models, banks can potentially demonstrate to regulators that their actual risk profiles are lower than those reflected in standardised approaches. This could lead to lower RWAs for certain assets, freeing up capital reserves.
The accuracy of RWA calculations hinges on the quality of the data used. Inconsistent or incomplete data can lead to overstated or understated risk assessments.
Solutions like OFSAA have pre-configured data models that can process a wider range of granular data points related to borrowers, loans, and counterparties. This can include credit history, collateral details, industry trends, and external risk ratings and encompass hundreds of millions of potential data points.
By having a more comprehensive data picture, banks can better tailor their risk assessments and potentially negotiate lower risk weights with regulators, freeing up capital.
The regulatory landscape surrounding capital adequacy is constantly evolving. Keeping up with these changes and ensuring compliance can be a challenge. This is where we see our clients spending millions building in-house solutions that have very challenging delivery outcomes.
The OFSAA approach offers automated tools to streamline regulatory reporting processes that are continuously updated by Oracle, including those related to RWAs. These solutions can help ensure data accuracy and adherence to evolving regulations.
By streamlining compliance processes, banks can free up people previously dedicated to manual reporting tasks and allow them to focus on optimising RWA calculations and capital allocation strategies.
Banks are required by regulators to perform stress tests to evaluate their capital adequacy in different economic scenarios. However, we have noticed that many of our clients are investing a considerable amount of money into in-house stress test projects that yield uncertain outcomes. These projects are often expensive and generate minimal tangible results.
Traditional stress testing often relies on pre-defined scenarios. However, banks are now exploring more advanced techniques, such as stochastic modelling.
Stochastic modelling allows banks to simulate a wider range of potential future economic conditions. This can help them identify potential risks and opportunities for capital optimisation. By demonstrating a robust risk management framework through these advanced stress tests, banks can potentially convince regulators to allow for lower capital buffers on certain assets.
It's important to note that these approaches are still evolving, and regulatory approval is often required for implementation. However, they represent promising avenues for banks to potentially free up capital reserves by achieving a more accurate and nuanced understanding of their risk profiles.
We've seen how OFSAA delivers RWA optimisation and assists in treasury transformation with a process workflow similar to this:
The Oracle solution has the ability to integrate with and enhance existing banking investments in platforms such as SAP, AWS, and GCP. We have noticed that while large-scale and complex internal development projects are in progress, the OFSAA solution can help expedite the delivery process. It can also aid in making internal development efforts more efficient by using Oracle's standard data models, business rules, and best practices. We often recommend our clients consider the OFSAA approach as a "tactical" decision while the bank continues to deliver its strategic end state with SAP, AWS, or GCP.
We've seen significant investment and focus from Oracle exploring how emerging technologies like Generative AI (GenAI) can further empower treasury transformation. While some use cases, like complex scenario generation, are still under development, there are promising near-future applications:
Oracle remains committed to staying at the forefront of innovation and integrating emerging technologies like GenAI into its solutions. As GenAI capabilities evolve, we can expect even more powerful use cases to emerge, further optimising RWA management and treasury transformation.
Revvence can help in several valuable ways: