Ahead of the Fundamental Review of the Trading Book Summit 2017, Tony has shared with us an insight into producing taxonomies to index systems and data to ensure data alignment between FRTB processes and P&L.
Tony, can you please tell the Risk Insights readers a little bit about yourself, your experiences and what your current professional focus is?
My background is valuation, risk and model governance, for which I have 20 years experience working in Product Control and Risk departments across several banks. I also have an IT background and recently managed a project with Barclays to develop a database system to document valuation controls, for which we developed a series of linked taxonomies. I am currently working in the Group Strategy team at Barclays covering a variety of initiatives including Structural Reform, IT & Data Strategy and Brexit.
At the FRTB Summit 2017, you will be discussing taxonomies to index systems and data. Why do you believe this is a key talking point in the industry right now and what can risk professionals gain from this insight?
For regulations such as FRTB and BCBS239 banks need to ensure they are using a consistent framework for valuation and risk across Front Office, Risk and Product Control. For many, this is a challenge, due to systems developed in silos or inherited through mergers or acquisitions. A system of taxonomies universally adopted throughout the bank can help to bring order to chaos.
What are the key considerations when using standard taxonomies to index data and systems?
There are many ways such taxonomies can be used and many benefits they can bring such as process standardization, reduction in operational risk, efficiencies. But it’s important to focus on primary uses cases in the definition phase, because there can be many different views on what a taxonomy should look like. It’s also important to fully plan the hydration and consumption phases.
When addressing the use of desk level approvals, what challenges may professionals face?
Approval at desk level is a more stringent requirement than before, with the capital requirements of individual desks under the spotlight, such that capital inefficient desks might face closure. To minimize that possibility clear data categorization and link between transaction data, products and risk factors in the models is essential.