As Gensler and the Democrats continue to face off against the Republicans and Wall Street over the consequences of the Dodd-Frank Act, one thing is clear; corporations will continue to try to mitigate their exposure to risk through greater oversight of the information they handle and process. This is not simply because they had trouble figuring out their real risk exposure during the collapse of the financial markets in 2008, but also due to the greater transparency required in their transactions, and new incentives for whistleblowers to turn them in.
Though not getting the same amount of press as the regulation of swaps, this proposed whistleblower legislation establishes monetary rewards for whistleblowers and allows them to report potential violations directly to the CFTC, bypassing the internal compliance process which was recently beefed up under the post Enron Sarbanes-Oxley legislation. This is giving greater impetus to the process, already underway, of companies removing any manual handling of key data and analysis, and putting in place automated processes. These companies understand that apart from reducing the number of human errors (sometimes dramatically), automating the collection, integration and analysis of data underlying their trading and hedging practices provides a clear audit trail. It also ensures that they have a clear way of understanding the logic behind decisions which are based upon complex and multifaceted models, unlike in 2008 when very few people understood the assumptions built into their derivatives trading and the real risks of their positions.
In the end, I suspect that we will not see any real spike in the number of whistleblowers in spite of the financial incentives, for a couple key reasons. First, companies are using Data Management Systems like ZEMA which carry out business process automation at the collection, validation, analysis and distribution levels. This process is centrally managed and ensures that alert mechanisms can be set which monitor changes to the data management process. This makes it difficult to tamper with the data without leaving a trail which would quickly be discovered.
Second, companies are discovering the inherent advantages of automating the management of their forward curves which provide the basis of their futures trading activity. For example, with ZEMA, the forward curve automation process allows the users to drill down into derived curves to view all the dependencies both raw data and formulas. This provides a transparency into the underpinnings of complex models that would be impossible in a company which still used spreadsheets to manage its hundreds, if not thousands of forward curves.
Even without the pressure being applied by the more stringent regulatory climate and the vast amounts of data that companies must contend with, these companies would still be turning to Data Management systems such as ZEMA to improve their efficiency and decision making capacity. However, with these pressures, they will soon be the cornerstones of every trade and risk team in both the financial and commodities markets. And executives will sleep better at night for it.