As businesses have become increasingly globalised and more complex, moving into new territory, regulators have been obliged to adapt compliance rules in a bid to make financial information more consistent. Subrata Majmudar examines the challenges.

With the emerging importance of capital markets as a mechanism for mobilisation and distribution of capital, corporations are increasingly focusing on earnings stability and shareholder value creation. While the capital market has remained the most efficient institution for allocating public capital, over-emphasis on the “perceived” efficiency of corporate earnings performance has increased the scope for window dressing performance. Enron, Worldcom and other examples of corporate malfeasance underline the point. Under such circumstances, regulators have the onus of evolving uniform practices that would make the presentations of public financial information both consistent and transparent for investors to make prudent investment decisions. Drivers of change Innovation in multiple areas and different forms has been the main factor driving regulators to usher in changes. These changes originated from, among other things, advances in economic theory, financial engineering, computational finance or technological advances that made the adaptation of changes a less arduous task. The complexity of businesses venturing into newer areas, or re-engineering their organisations, often compels regulators to calibrate their compliance standards. Such moves by institutions invariably push them into higher levels of compliance requirement as well. Consider, for example, a bank based in the US that decides to buy a stake in a bank based in Switzerland. The US bank would have to comply with International Accounting Standard (IAS) 21, which deals with how different currencies are translated for presentation purposes and IAS 27, dealing with how a parent organisation should consolidate subsidiary entity numbers into its books of accounts. The constant internal flux in business operations has led to the adoption of higher, more evolved compliance standards. These examples are instances of a shift in compliance requirements due to institutions’ strategic or operating decisions. Quite often, the driver for such a shift originates from changes in economic variables beyond businesses’ control. Mandatory compliance with IAS 29, on dealing with restatement of financials to adjust for erosion of purchasing power in the face of hyperinflation, or the introduction of additional complexity in IAS 21, for a currency being suddenly de-pegged, are examples of uncontrollable events driving these shifts. More disclosure Sometimes – and this is becoming the norm rather than an exception – institutions voluntarily disclose more information than that required by statute. There could be many reasons for doing this, such as communicating “best-practice leadership” to the investor community or a desire to impress them with an eye for the marginal dollar. Such willful acts of disclosure raise the bar and serve as “transparency benchmarks” that are quickly adopted by other institutions or by regulators themselves. This creates a virtuous cycle that feeds itself, making public financial information richer in content and quality. Increasingly, the divider between what institutions refer to as “internal management information systems” is vanishing and “internal intelligence” is finding its way into public disclosures. While this trend is more than welcome, institutions now face challenges of making the information not only internally trustworthy but able to pass public scrutiny as well. From accounting to economics The regulatory community has seen winds of change blow over the world of economics in the past few years, which, to a significant extent, has changed the broad perspective of the compliance function. Earlier, compliance was almost completely an extension of the accounting function. Accounting fitted with what regulators were looking for: conservatism in approach and a faithful reporting of what had already happened. The merits of this approach are obvious but what obliterated such a paradigm was that capital markets, in their valuations, look for insinuations of possible future incidents and for that they are often prepared to disregard extrapolation of past trends. This led to what is possibly the most fundamental shift in the compliance archetype: compliance and regulatory reporting moved away from being backward-looking to being a window into the future. With this shift, established accounting rules gave way to theoretical economics, computational finance and financial econometrics. Economists also emerged as front-line functionaries rather than the strategic intelligence providers that they once were. Although such intelligence has always been regarded as ground-breaking in the restricted community, their techniques have found a way into the idiom of regulatory bodies. Take, for example, a rather computationally intensive mathematical technique of finding out a worst-case loss that portfolios might suffer due to extreme movements of price. JP Morgan pioneered the technique in the mid-1990s. Called value-at-risk, it is almost a sine qua non in managing financial risks and is mentioned as a standard approach for several applications in the third consultative paper published by the Bank for International Settlements (BIS). The same statute recommends adoption of advanced econometric techniques like Monte Carlo simulations in predicting the financial impact of future events. ‘Mark to market’ is a technique by which institutions report the value of marketable positions according to what can be realised by unwinding their market position, and has been a standard reporting norm in dealing rooms. Quantitative analysts have used sophisticated models to price positions in instruments that have complicated, non-linear pay-off structures – that is, derivatives. Should these positions be taken as hedges, risk managers internally would evaluate the efficacy of such hedges and adjust the hedge alongside the position that is being protected. Contrast this long-standing practice with what is a hot topic in today’s world of regulatory compliance: FAS 133, otherwise called IAS 39. Motivated by the Financial Accounting Standards Board’s desire to usher in greater transparency, FAS 133 directs institutions to ‘mark to market’ positions in derivatives and record them as either assets or liabilities on their balance sheets. Customer intelligence Organisations that have invested in customer intelligence often try to unearth patterns of customer behaviour. In most cases, the motivation for this is to predict the manner in which the customer is most likely to interact with the organisation in the future. Such techniques are now mentioned in regulatory norms of anti-money laundering, namely the US’s Bank Secrecy Act, which requires financial institutions to “patternise” customer behaviour to detect recursive patterns that might indicate the intention to deceive. Examples such as these abound in current regulatory literature. It is apparent that the future of reporting will be dominated not by pure accounting numbers but by analytical interpretations of business processes and functions. This trend will accelerate and the contents of compulsory disclosures will be dominated by contents that earlier were used only for internal evaluation of business efficiency. The fundamental shifts in the paradigms mentioned above have significant ramifications for how companies manage their information and create forward-looking analytics. An added dimension of complexity in the compliance process for many organisations today is the geographical spread of their businesses, making these institutions accountable to multiple regional regulators. But, despite the many compelling reasons for changing the regulatory presentation of business facts, doing so poses a challenge to those being regulated. Collating data The first hurdle that institutions have to overcome en route to their goal of optimal internal and external compliance is collating every single piece of information about different aspects of their businesses. As organisations grow in size and complexity and spread over multiple locations, information stores proliferate alongside them. Given the ever-evolving nature of compliance information requirements, institutions can no longer cherry-pick the information they need to collect and store. This makes the architecture of data storage a challenge in itself because institutions need to choose judiciously between information repositories that contain granular data for more operational reporting and analysis, and aggregated data stores for compliance analytics that do not necessarily require the most granular information. Multiple levels of aggregations in the aggregated repositories may occur, depending on the nature and frequency of the analytical operations carried out. Increasingly, institutions would be forced to create an enterprise-wide information store that spawns off information marts (which could be local or distributed) that use information subsets from the global data source. For instance, there could be an elaborate, and possibly granular, subject area defined in the global repository to store information for Basel II compliance. It is likely that information about collaterals, internal ratings and operations risk loss data could be spawned off to create more focused and, possibly, more aggregated data stores for further analytics. Expanding data spread Compliance information will increasingly become enterprise-wide. The finance function no longer bears only the mantle of compliance-related processes and reporting. Regulators are increasingly demanding cross-functional analysis. The Banking Secrecy Act requires the identification of customers’ behaviour superimposed on their financial transactions as a method of determining possible dishonest intent. Such instances abound in current compliance norms. This makes an obvious case for integrated common data sources for enterprise-wide analytics. Data definitions Organisations need to breathe life into the raw data collected in order to define what a piece of data represents. On the face of it, it seems a rather simple task, but the complexity is that such definitions most probably will undergo changes over time. Thus, the definition holding good today for a data element may not accurately define the same data collected some years ago. Such time variance of definitions could jeopardise the accuracy of the compliance information provided. The complexity related to definition is taken a degree higher when the potential of regional differences in definition is added to the picture. Consider the following example taken out of a possible Basel II norm that requires classification of obligor entities as small and medium enterprises (SMEs). There is a possibility of misclassification of an entity if rules applicable today are carried forward into the future after they have been altered. Obviously, the solution is not to simply overwrite the old rule with the new one because one would then end up with an incorrect retrospective classification. Now, consider a situation where the same bank is operating in multiple countries, with local regulators having their own classifications and calibration frequencies of rules. The analytical system put in place by the bank must be geared to handle such complexity of definition elegantly and accurately. Information reporting As compliance norms evolve, the focus is likely to shift from the data reporting framework of today towards information reporting. Enterprises continue to consider internal processes to be proprietary and sensitive, and use such information largely for internal consumption. This is likely to give way, as regulators would increasingly demand a peek at organisations’ processes and make such information public. This trend has already begun, modestly, in the Basel II guidelines that make it obligatory for an institution to disclose to local regulators the processes they have used in arriving at the risk-weighted assets (and hence regulatory capital), which represent the end-state of the Basel II credit risk compliance process. In fact, the BIS places great importance on reporting processes and such norms form what is popularly known as pillar II of the Accord. Leap-frog in maturity In the current breed of corporate legislations, regulators tend to reward the more efficient. This extension of Darwinism is vetted by the fact that several financial institutions believe that were they to follow the more advanced norms of Basel II, both for credit as well as operations risk, they would have to hold less regulatory capital than if they followed less advanced options. This realisation would compel organisations to try to leap towards a higher maturity level, rather than following the slow metamorphoses of regulatory maturity. This places a larger responsibility on these organisations’ information management function because they would have to either buy systems that jump-start this process or quickly mould internal technology architectures to cope with this self-imposed challenge. Propelled by the changes in financial markets and applied economics, regulators have shed the earlier stance of accounting-driven compliance in favour of regulating business environments with forward-looking analytical information. This shift in paradigm is likely to intensify in the future, forcing enterprises to either look again at how their current intelligence framework is structured or possibly invest in integrated business intelligence architectures. Subrata Majumdar is business solutions architect at Reveleus

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