This question is posed at the conclusion of “As Securities Become More Complex Is Financial Data Management Becoming More Complex?” by Jeffrey Rooney. This paper discusses OTC derivatives as an example of how the financial crisis escalated and Enterprise Data Management (EDM) as a financial data model that offers a solution to data problems faced by the industry.
Based on Rooney’s presentation the financial crisis is a symptom of inefficient financial data management which is the result of intentional use of poor financial models coupled with the intentional misuse of financial models.
Poor financial data management has a cultural and technological basis. The cultural component is the Chinese wall or siloed business unit structure which facilitates and operates on the intentional misuse of financial models for the purpose of preserving the identity and autonomy of independent business units. The technological component includes other issues such as merger activities and “disparate legacy systems” (Rooney 2009, p.2) which results in either use of poor financial models or provides no framework for effective financial models at all.
The IBM-World Bank currency swap was structured with the goal of avoiding highly regulated capital markets and regulation by affected countries. This was a $290 million transaction which paved the way for the creation of the now $700 trillion OTC derivative market. (Rooney 2009, p.3) As a result of these inefficiencies a financial crisis has occurred in multiple sectors of the financial markets.
The financial crisis is the result of the systematic use of poof financial models and inefficient data management strategies built around the primary goal of expanding the derivative market. Avoiding regulation and hiding the complexity of derivative transactions is a primary goal of, resulting in, the inefficient financial data management and financial models.
Rooney, J. (Spring 2009) As Securities Become More Complex Is Financial Data Management Becoming More Complex? FinTech Project. Polytechnic Institute of NYU Finance and Risk Engineering.