The 2008 financial crisis exposed serious gaps in the core architecture of the industry and the ability of financial services institutions to adequately measure credit and market risk. A major factor that exacerbated risk and contagion was the complexity and interconnected nature of the corporate structures of securities issuers and market counterparties.
As the industry debates regulatory reform and the course toward greater transparency and stability, we are entering a new phase in the evolution of financial data and a potential renaissance in the approach to risk management. Legal entity data will be the core building block of this renaissance.
In the wake of the crisis and the serious challenges faced by financial institutions, it’s normal to think in defensive terms - reducing costs, avoidance of risks, etc. However, you measure risk and opportunity by the same benchmark: they are inseparable. Therefore, it would be a mistake to overlook the potential predictive value of legal entity data in terms of discovering revenue opportunity and supporting investment and trading decisions. Beyond risk, compliance, and other operational functions, the true potential of legal entity data will be realized when the focus evolves from looking at the world in terms of cost, to looking at it in terms of revenue – from playing defense to going back on offense.
When it comes to the global economy, there are at least two things we know to be true: First, markets tend to surprise us. Second, there are great fortunes to be made by those who are slightly less surprised. The ability to understand the full dimensions of the corporate organism may be the key to being slightly less surprised.
Regulatory Reform and Legal Entity
In the wake of the crisis, it became very clear that we didn’t understand the interactions between markets, liquidity, valuations, correlations, and prudent risk management. The severity and uncertainty it created has fundamentally changed public perception of the banking industry, and populist politics in many countries have influenced the approach to legislation and reform.
There are three common themes that many regulatory initiatives share: First, institutions must have the ability to uniquely and unambiguously identify the entities they do business with – be they an issuer of securities, a customer, or a trading counterparty. Second, the first principle of risk management and regulatory reform is to know who you are dealing with. That means institutions must understand the corporate structure and nature of the business of those entities – what is their country of risk, industrial classification, credit rating, whether they have been sanctioned by a regulator, who is the owner or obligor, etc. Third, institutions must have the ability to roll up, assess, and disclose aggregate exposure across all asset classes to legal entities, countries, and industrial sectors. Silos Are Here To Stay
Assessing exposure is a complex matter, because a complex portfolio will run the gambit across a variety of asset classes. The primary challenge stems from the fact that trading desks, business applications, and operations for most firms were developed in silos to meet the specific needs of one asset class. As the infrastructure in the capital markets industry evolved, silos of incompatible data structures and technologies storing all the relevant transactions, positions and reference data were the logical result.
Multiply asset class silos by the number of lines of business and geographies a global firm competes in and the challenge of risk aggregation grows larger. Now consider the complexity of the interwoven corporate structures and legal entity hierarchies that represent market counterparties linked to asset class, transitions, and positions and the problem grows exponentially. All of these factors have resulted in an inability to execute timely or accurate risk assessments across asset classes, lines of business, and geography.
The primary challenge in risk reporting stems from this proposition that the capital markets industry evolved with a “securities-centric” view, where the asset class or security became the center of the data universe. Various security master files became among the most important databases of record within the institution and drove the processing of trades and reporting across the enterprise.
A security and its price became the center of data management strategies. Since it is the instrument of trade and measurement, it is logical that it evolved as the focus of our data management strategy. Developing siloed systems and processes to cater for the unique behavior of an asset class was a practical approach to manage new asset classes as they emerged. In a perfect world it might be possible to have all systems that are multi-asset class, but the reality is that silos are here to stay. The task that remains is how to logically join together silos of trade and position data for functions that require a holistic view. Legal entity data will be the cornerstone of this effort.
The New Center of the Data Universe
The financial services industry will become more entity-centric by putting the legal entity at the center of the data universe. The approach will not only advance the ability to aggregate and measure exposure for risk management or compliance but will join data sets together for the first time that will help discover trading and investment opportunities.
The journey toward this goal starts with acquiring and linking as much information to the entity itself. This includes not only unique identification and an accurate description of the entity and its corporate hierarchy, but all relevant information that can provide predictive insight into the risks of doing business with the entity, whether it is as a customer, counterparty, or investor. It is impossible to over-emphasize the importance of getting the core data right, such as an entity’s name, address, country of domicile/risk, cross-referencing of identifiers, and industrial classifications.
The next step is linking securities instruments to a specific issuing entity, and then tying the entity to its ultimate parent. The ability to roll up exposure to a single entity is a primary use-case for a host of critical functions related to concentration and exposure. This is the foundation for legal entity data but it’s the ability to link value added content sets to the entity that holds the greatest potential.