Sufyan, please tell our readers a little bit about yourself and your experience
I am currently heading the Pre Sales/Business Solutions team in EMEA for AxiomSL. Having over 10 years’ experience in the areas of trading and risk, I have worked with different solutions and have a deep understanding of complex business/IT requirements from analysing client’s current infrastructure to providing recommendations and best practice approach. Over the past seven years of my career, I have helped firms make informed decisions in the area of best practices in Enterprise Risk Management (ERM), covering topics such as Basel III calculations for Market Risk, Credit Risk, Operational Risk & Regulatory Reporting, Stress Testing, IFRS 9, Data Management Aggregation & Consolidation (BCBS 239), Portfolio pricing and risk for front office trading systems, Business Intelligence, Data & Analytics, Business Analysis & Implementation. Prior to joining AxiomSL in 2015, I served as Associate Director (Solutions Specialist) for Moody’s Analytics covering Enterprise Risk Solution. I have also worked at SunGard Financial Systems – FIS within the Capital Markets space, articulating client trading and risk requirements from pricing to real time risk management.
You will be joining us at the IFRS 9: Impairment and Implementation Summit in London to provide a presentation on leveraging IFRS 9 technology to benefit the business. What key aspects will you be looking to cover at the Congress?
The areas I would like to cover are:
- The challenges in consolidating data for IFRS 9 across risk and finance and reconciling them
- Governance processes around data, data aggregation, optimising the data lineage process and auditability of the results
- Visualisation and automation of the end to end process all the way from data capture, data governance, classification & measurement, impairment, hedge accounting all the way to reporting (regulatory, internal or analytical reporting)
- Versioning of the data, calculation process including the models used across the different asset classes.
What data challenges are banks currently facing ahead of IFRS 9 implementation and how can banks best overcome these challenges?
- The level of granularity of data required for IFRS 9 is extremely high. Every financial instrument needs to be taken into consideration. The challenges banks face are aggregating and consolidating data across a multiple source system in a user friendly way.
- Since the granularity is high, expected credit loss needs to be calculated at every contract level to project future expected losses across multiple macroeconomic scenarios. This requires high level of automation and computation.
- The results based on every contract including contract level information and the different macro-economic scenarios would need to be archived/historized. The ability to create snapshots of the end to end process is a challenge for banks.
- Once banks start parallel runs, it will generate huge volumes of data across different periods along with different scenarios, simulations, model and model data inputs used. Governance and auditability across this entire process is a big challenge.