Why an enterprise architecture?


As a result of the financial crisis, one of the main disruptive forces for financial institutions has been regulatory, with a bombardment of stipulations from international and national bodies. These are intended to address different perceived risks within the market. The initiatives sometimes overlap in terms of timescales and, often, requirements, and there was no end in sight. Stress-testing, collateral management, real- time monitoring and risk data aggregation and reporting have been key areas of focus. ‘Look where they got us,’ might be a pertinent observation about the pre-crisis regulations. If financial institutions were having to rethink back then, how much greater is that need now given the events since the second half of 2008, with the market slipping from subprime crisis into a fully-fledged, global banking crisis and recession. The regulations that, it could be argued, rather missed


the mark included new accounting standards, corporate governance


rules, customer protection legislation and


guidelines, anti-money laundering/Know Your Customer (AML/KYC) regulations, counter-terrorist finance legislation, and credit, market and operational risk legislation. These had been embodied within names and acronyms that have become only too well-known in the sector, such as Sarbanes- Oxley (SOX), Basel II, IFRS, IAS and MiFID, the Payment Services Directive (largely centred on consumer protection) and the measures drawn up by the Wolfsberg Group (relating to counter-terrorist financing and the information – or lack of it – within some Swift messages). Next have come Basel III, EMIR and BCBS 239 with more to follow. At the crux of the response by financial institutions is the need for a coherent architecture that is increasingly likely to span both finance and risk, with the ever more overlapping needs of the two disciplines constituting a persuasive reason for a single solution. There also needs to be integration across risk associated with both the banking book and trading, as well as full coverage of an entire group, so domestic and international operations, core businesses and group ones. For instance, a European bank’s main exposure could be in its US mortgage subsidiary – that business that it seemed a good idea to acquire a few years ago – so it is no good measuring and viewing such businesses in isolation. The financial crisis showed that there were ticking bombs in both the banking books and trading, and in different parts of an organisation. The architecture to address this can take different forms,


in part probably driven by the size of the institution. It will need to evolve, as the requirements themselves evolve, so too the institution itself, with the latter including future mergers and acquisitions. It is likely to embrace some or all of the


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following: data warehouse(s), data marts, ETL tools, business intelligence, and business process management (BPM). And there is then the additional complexity of what needs to be real-time or near real-time and how to achieve this, especially as ever more data is involved in the computations. Above all, attention has to be given to the quality, consistency and consolidation of data. This means there is a major reconciliation effort and much more focus on the original source of data as well as how it is manipulated once it has entered an organisation. As Simon Barkla, senior manager, corporate technology solutions, Toronto Dominion, observed in relation to Basel II: ‘It has stepped up the requirement for data beyond anything anyone had thought of’. The lack of clarity makes it difficult to plan and invest so that many banks have ended up with a mish-mash of solutions, some of which are real-time, others that are quasi real-time and the rest as batch. The proportion of systems in each category is likely to be largely determined by the technical architecture and the majority of banks still rely on end-of-day crunching of numbers. Clearly, life has become much more complicated. From


setting limits on the same basis as traditional lending, there was the move to add-on methodologies then, for some, Monte Carlo simulations. Regulatory capital has gone through a similar sequence of added complexity, with more sophisticated internal models and the requirements mounted, through Basel II, bringing a need for new systems, processes and quant skills. The financial crisis heralded more regulation, rapidly accelerated the shift of OTC derivatives to central clearing and giving prominence to Credit Valuation Adjustment (CVA), whereby the value of a derivative is influenced by the associated counterparty risk. Collateral management moved firmly into the spotlight, with this typically shifting from the operations department to the front-office. CVA is used to incorporate counterparty risk into the pricing of deals and for inter-desk charging within institutions. The need for a single version of the truth across the


enterprise is a common rallying cry. This needs to traverse all areas of the bank. It may come to be centred on a single data warehouse but the size of such a repository, particularly given the historical data requirements, might mean it is not logistically feasible, so many larger institutions are moving towards a single data architecture, but spanning multiple, coordinated data marts. For good reasons, the industry has moved away from


the idea that the general ledger should constitute the main data repository; it will be one connected part of the eventual configuration but will not be the main repository for risk


Risk Management Systems & Suppliers Report | www.ibsintelligence.com


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