Risk management has always placed great emphasis on studying the past. If one can determine the risk events and losses in the past, one can learn how much capital to set aside for future losses. If one can understand how much market losses there were in the prior period, one can identify the scope of potential losses in the future. While this approach may have been adequate in the past and does provide an effective measurement baseline, it is not sufficient for the future and so in later chapters we turn to explore newer, more modern approaches and techniques. It is not just financial loss that is at stake but the loss of reputation with clients and the broader community, as recent scandals have shown. A more ambitious goal set by the most innovative risk managers today is to understand the past, not just to measure it but also to prevent it from recurring in the future.
In Chapter 20, we turn to new tools of risk management that involve advanced cognitive understanding of human behaviors and motivations. The use of psychological insight and data analytics are tools that can create incentives and programs to prevent risky behaviors and drive employees toward improved outcomes in the field.
It is no exaggeration to say that proper and appropriate trade surveillance could have helped to avert or reduce the impact of many of the events that banks have been paying for in the past few years. In Chapter 21, we explore new cognitive AI tools that can complement the current trade surveillance activities to identify risky behaviors before they result in losses and reputational damage.
Finally, we discuss external factors, in particular, the role of external stakeholders, from regulators to society at large. The level of interdependency between institutions was shown for all to see in 2008 and needs to be studied to understand how a reoccurrence of those types of events can be prevented. This may be critical in helping our banks and society to avoid a repeat of the 2008 Financial Crisis in the near future.
Acknowledgments
I could not have written this book without the many colleagues over the years from whom I have learned so much. There are too many to name, but you know who you are. Thank you!
I would also like to acknowledge the following who have helped me to bring this book to fruition: Dickie Steele, my fellow Bowdonian in New York who provided insights and ideas right up to the final deadline; Josh Getzler, who provided the initial encouragement in my writing endeavors; Steven Stansel at IBM Press who helped navigate the publishing pathways at IBM, and Bill Falloon and rest of the team at Wiley who provided such brilliant support throughout this process. Lastly, to my family – you're simply the best!
About the Author
Andrew Waxman is an associate partner in IBM's Financial Services Risk and Compliance consulting practice with over 20 years of experience, in the United States and the United Kingdom, helping financial services organizations manage complex business issues.
Andrew has written on risk and banking issues in journals such as American Banker and Wall Street and Technology for many years.
Andrew lives in New York, where he shares his home with his wife and two daughters.
CHAPTER 1
The Historical Context
Wall Street has changed immeasurably in the past several decades. Key changes that have occurred include computerization of trading, the growth of universal banks (and hedge funds), and the development of financial engineering. Each of these changes enabled major revolutions to take place in our larger society. Banks are not what they used to be, but while they were agents in enabling change in society – changes that brought major benefits – with these benefits also came major costs.
First, computerization of trading has helped to facilitate the growth of a shareholder society. The casual, retail investor now has access to trading tools that provide access to very liquid and fast‐moving markets with the ability to execute shorts, options, swaps, foreign exchange (FX), and other complex transactions from their PC or smart phone. The cost of participating in such trading activities has declined dramatically and, as a result, millions more people9 own shares today than in the past. This has been in large part due to the creation of new trading and computer technologies and resulting cost reduction. Such gains are not achieved without risk, however. Some of the operational risk incidents we will review in the coming chapters stem from the technical challenges that are posed by such technological advances.
Second, the growth of universal banks10 with massive capital resources and services aimed at every customer segment has helped achieve major efficiencies in the promotion of new capital structures and investment vehicles. The availability of credit to greater numbers of people and the provision of new types of financial innovation to every type of corporate entity has enabled the creation and expansion of new productive capacity in the United States. These advantages were particularly clear during the expansion years of the 1990s and early 2000s. However, these benefits also brought problems in their wake.
The sheer size of these universal banks and the stitching together of different legacy systems and bank cultures has created patchworks of manual process and controls that became too complex to manage. The risk of great and complex failures inherent in such unwieldy structures has, in the eyes of many analysts, grown, rather than retreated since the Financial Crisis of 2008. Most recently, Neel Kashkari, chief of the Federal Reserve Bank of Minneapolis, has argued for further controls to be put in place against banks that are so called “too big to fail.”11
To his point, managing multiple businesses and multiple country branches brings a level of complexity that makes it much more difficult to monitor activities across an entire organization. Additionally, privacy laws that have multiplied in different countries have further exacerbated this issue. This can and has led to failures to assert centralized controls and unified lines of defense against suspicious trading activity and the like.12
Third, the growth of financial engineering took place in the context of relatively light regulation and planning. Credit default swaps, for example, started as a relatively obscure product in an obscure trading group within investment banks. While investment banks and broker/dealers are required to oversee new product development in a careful way, new products have a habit of getting through with relatively little scrutiny and planning. This lack of planning is, in part, a reasonable response to the nature of the trading market. Many products are thought up in the twinkle of a trader's eye and many of them fail to take hold. In the case of credit default swaps,13 however, within a very short time frame, billions of them were being written to cover bondholders and non–bondholders. Expansion in areas like this brought much greater profits to the banks, at least for a time. It also brought much greater complexity to the business. Obscure products like credit default swaps can thus grow from a relative backwater status to a major profit center in a short space of time in a way that is hard to predict or plan for. The ability to manage the resulting complexity, however, does not tend to keep up. The rash of scandals, penalties, and significant operational losses in the case of mortgage‐securitized products are one indicator of that.
The rapid change at investment banks as a result of these particular areas of innovation has made it hard for regulators to keep up in their ability to understand and monitor these changes. Yet the role of regulators has never been more important. In some ways, the battle over regulation that took place in the years after the 2008 Financial Crisis, and in particular, the battle to introduce the Dodd‐Frank legislation was similar to that played out in the original battles fought by Washington and the SEC to establish US securities laws and the SEC in the 1930s. This will be discussed further in
In the 1960s, finance's share of the GDP accounted for less than 5 percent of the US economy's output. By the 2000s, the proportion had risen to over 8 percent, fueled by a combination of middleman fees, for example, in asset management, and the credit explosion fueled by securitization (more of that later). The repeal of Glass‐Steagall enabled large banks to take advantage of these secular trends and bulk up through acquisition to provide services across the whole range of banking services, including retail, wholesale, asset management, treasury services, etc. Banking balance sheets of over $2 trillion came into being in the 2000s.
As interim Assistant Secretary of the Treasury for Financial Stability from October 2008 to May 2009, Neel Kashkari oversaw the Troubled Asset Relief Program (TARP) that was a major component of the US government's response to the financial crisis of 2007. Subsequently, as Chief of the Federal Reserve Bank of Minneapolis he has been an outspoken proponent of further reforms to manage risks posed by large banks. His most recent proposals made in November 2016 were covered widely by the press, including the article reference below: http://www.reuters.com/article/us‐usa‐fed‐kashkari‐idUSKBN13B1LD.
JP Morgan Chase agreed to pay $1.7 billion as part of a deferred prosecution agreement reached with the US Attorney's office for the Southern District of New York in January 2014 on charges that its failure to maintain an effective anti‐money laundering program helped to facilitate the multi‐billion‐dollar Ponzi scheme orchestrated by Bernard Madoff. The crux of the complaint by federal prosecutors was that the bank maintained the relationship despite internal concerns and red flags. These red flags were actually raised by the London Branch with the UK's Serious Organized Crime Agency but were not shared with the AML Compliance team in the United States. Whether that was because of misplaced concerns over potential noncompliance with data privacy laws in the UK if such client concerns were raised in another country is a troubling possibility. Be that as it may, much work has been done since then, to improve the AML program at JP Morgan Chase, including significant investment in systems and expertise. Information on these charges was reported widely and a good analysis can be found at the link to a DealBook NY Times article: https://dealbook.nytimes.com/2014/01/07/jpmorgan‐settles‐with‐federal‐authorities‐in‐madoff‐case/.
A credit default swap (CDS) is a financial swap agreement that the seller of the CDS will compensate the buyer (usually the creditor of the reference loan) in the event of a loan default (by the debtor) or other credit event. This is to say that the seller of the CDS insures the buyer against some reference loan defaulting. The buyer of the CDS makes a series of payments (the CDS “fee” or “spread”) to the seller and, in exchange, receives a payoff if the loan defaults. It was invented by Blythe Masters from JP Morgan in 1994. By the end of 2007, the outstanding CDS amount was $62.2 trillion, falling to $26.3 trillion by mid‐year 2010 and reportedly $25.5 trillion in early 2012. CDSs are not traded on an exchange and there is no required reporting of transactions to a government agency.
