January 20, 2010
Systemic Risk and Macro-prudential Regulation
On my recent holiday I took the opportunity to read a few very interesting papers on systemic risk that came out of UK (yes I admit this sounds geeky even to me!). Links to these can be found at the end of the blog, but I want to discuss one, a discussion paper produced by the Bank of England entitled "The role of macroprudential policy", that I found particularly thought-provoking. The paper focuses on how systemic risk can be effectively managed in a global financial system.
It will be instructive to first define "Macro-prudential policy" (since I certainly didn't fully understand what this meant until a short while ago when I was buried in weighty tomes on systemic risk!). Regulation has hitherto been focused on individual institutions - a good example being the Basel II accord that was focused on individual banks. This is Micro-prudential policy. The goal of these regulations is to ensure the viability and solvency of the regulated institution.
Unfortunately the credit crisis that culminated in 2008 showed how ineffective micro-prudential policy alone can be as a regulatory instrument. The problem is that with the increasing complexity of the financial system, it is no longer possible to get a clear picture of an institution's risks (and therefore ensure its solvency) simply by looking at that institution's exposures. As an example, all banks who had considered themselves hedged against sub-prime CDOs by purchasing insurance from AIG suddenly found themselves naked when AIG was threatened with bankruptcy. A risk manager at one of these banks would have no way of knowing how unstable AIG had really become (and therefore had no chance to manage his counter-party risk to his insurer) without understanding the complete scope of AIG's operations. Of course he would have little opportunity to do this since he would have needed transparency into AIG's book of business (or fallback on the traditional approach of listening for scuttlebutt on the street). The solution is for regulators to not only study what makes a particular institution vulnerable due to it's own activity, but also its vulnerabilities due to its connections to other institutions. This is a new and hitherto unprecedented level of analysis of the financial network, and the regulation stemming from it, is referred to as Macro-prudential policy (while the paper itself does not hyphenate the word I like it this way - it's too long and unwieldy otherwise).
The paper is long and interesting (at least if you are into this sort of thing) - a highly profitable read. I won't steal it's thunder by summarizing it all, but will point out a few highlights:
- Financial risk is basically caused by 2 factors - increased leverage (i.e. too little capital and too much borrowing) and maturity mismatches (using short-term borrowing to hold long-term, illiquid assets).
- These risks can become systemic in one of two ways: a) The aggregate level of these risks in the financial system is unreasonably large or b) the risks become concentrated in a few, systemically important (aka "too-big-to-fail") financial institutions
- Managing systemic risk therefore becomes an exercise in managing these 4 factors.
- Aggregate risk can be managed by what's called "Counter-cyclical policy" - forcing Financial Institutions to build up overly generous reserves during the good times so that they can release these reserves during the bust - this ensures a dampening of credit during a financial boom and (crucially) a freeing up of credit during the bust so that the wider economy is not adversely affected. The suggestion of the author is to add capital surcharges (i.e. extra charges on capital) to every institution's existing regulatory capital that are based on that institution's exposure to "over-heated" businesses (e.g. residential mortgages).
- To manage network risk, the proposal is to increase the capital of an institution based on a judgment of it's size as well as connectivity to other institutions.
- The paper then discusses ways to make all this work the real world. Given the scale and diversity of the global financial system, it would be unrealistic to assume that a set of rigid rules would be able to address all the potential ways in which the system could get into trouble - it's clear that discretion and expert judgment are critical to the success of such regulation. Unfortunately expert judgment can fall prey to a number of difficulties - charges of inconsistency and favoritism, for example (think Lehman Brothers vs. Bear Stearns) So discretion must be done transparently.
- Finally there are the problems of logistics to address. Which institutions to cover? Just "deposit-taking institutions" aka commercial banks? Do we include Investment banks and hedge funds as well, since these can these can take over the role of banks in a form of regulatory arbitrage? How do we regulate international institutions - which raises the crucial issue of home-host regulation? And finally, do we have the data required to do the required analysis?
I have not done justice to it's 37 pages with these highlights and highly recommend that you read the original. The purpose of this brief summary is to allow me to examine some of the technology issues raised by the proposals.
First, it's clear that the proposal will need a wider and more granular set of data than regulators currently receive from banks. The systemic and interconnected nature of such analysis also makes it very important to have clean and consistent data, especially when data will be submitted at a granular level (for example, the repo exposures to each counterparty by collateral type). Initiatives that have troubled the financial industry for a while - having a clean and uptodate list of counter-parties and their hierarchies for example - will become crucial under this new framework. By far the biggest technical hurdle is going to be the need to have all submitting financial institutions upto a minimum standard of data - this will mean ensuring that broad data management principles are disseminated across all these companies. This brings up the issue of scope noted earlier - if the scope is larger and covers hedge funds and other vehicles the issue of uneven technical capability across the regulated base will need to be addressed.
The need for discretion in regulation leads to the other technology implication. In such a situation, transparency becomes crucial. This means that not only must the decisions themselves be well-documented, but the way in which a particular decision was arrived at (such as the decision to apply a systemic risk surcharge to a particular product such as commercial mortgages) must be well-documented as well. This implies an advanced capability for visualization and ad-hoc analysis of detailed data.
In this context I will briefly mention the proposal to set up the National Institute of Finance (see the website of the Committee to Establish the National Institution of Finance or CE-NIF for short). Full disclosure - I have recently started working with this august group - because I find it's goals and methods particularly laudable. The CE-NIF is an entirely volunteer effort. One of its most positive aspects is that volunteers have signed up not only from the regulatory community but also the financial community. In my opinion, this is crucial if we are to have an effective regulatory regime. An effort that is only government-led runs the distinct risk of being heavy-handed or ineffective or both (remember Sarbanes-Oxley?). Check out the CE-NIF website for more information.
As promised, here are links to a couple of other documents I've been reading on systemic risk:
1) The Warwick Commission on International Financial Reform [pdf]
2) Rethinking the Financial Network by Andrew Haldane [pdf]
Before I go, I would like to thank the readers who were kind enough to leave encouraging and positive comments. It's amazing how far such comments can go in boosting one's motivation to produce more postings. My busy working schedule prevents me from posting more articles than I currently do, but the one promise I made myself when I started this is that I would only write a post when I had something worth saying. I'm glad it's working.
Posted by dkrishna at 11:32 AM
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September 23, 2009
Utilizing Technology to improve TARP and Financial Oversight
Below is the written testimony that I gave last week for the hearing before the House House Financial Services
Subcommittee on Oversight & Investigations regarding the role of technology in improving TARP and Financial Oversight. I focused on the idea that the absence of technology and analytics in financial oversight is more a function of awareness and will than of the suitability and maturity of technology itself. What's more, I argued that the very targets of oversight, the large financial institutions, are themselves enthusiastic users of such technology. Government has much to gain by learning from the private sector in this regard.
For transcripts of the other fascinating testimonials at the hearing, please see here.
Chairman Moore, Ranking Member Biggert, and members of the Subcommittee, my name is Dilip Krishna representing Teradata Corporation. Thank you for the invitation to offer testimony today before your Subcommittee.
Before I begin, I would like to also thank Congresswoman Maloney for her leadership in introducing H.R 1242, a bill to amend the Emergency Economic Stabilization Act of 2008 to provide for additional monitoring and accountability of the TARP. Teradata Corporation endorses H.R. 1242 without reservation or qualification and encourages the Congress to pass this legislation as expeditiously as possible.
Teradata, the company I represent, is among the world’s largest companies focused solely on data analytics and data warehousing. Our technology allows business and government to leverage detail‐level data for both tactical decision making and strategic insight, to recognize emerging trends and respond quickly. As an example, many of Teradata’s customers apply data warehousing techniques to detect and respond in seconds to fraudulent activity, allowing them to save millions of dollars per year.
Our government customers include the Centers for Medicare and Medicaid Services, the U.S. Air Force, the US Transportation Command, the US Postal Service, the USDA Risk Management Agency and the States of California, Minnesota, New Jersey, Ohio, and Texas to name a few. Over 50% of the world’s largest financial institutions use Teradata for strategic purposes including risk management, fraud detection and customer management. A Teradata database has been implemented in more than 900 major corporations in every business sector so that on any given business day in almost every industry throughout the world, well over a million users access a Teradata warehouse as they make decisions.
Teradata’s Position – Using Technology for Financial Oversight
Given the economic crisis that we have experienced in the past two years, the problem of comprehensive governmental oversight has become immensely more urgent and important. If the experience of the last two years has taught us anything, it is that our financial institutions are a national asset – the mismanagement or abuse of which can lead to serious, long‐term and detrimental effects to the well‐being of every American. Through this experience, we have learned that money does indeed, make the world go around.
Thorough and effective oversight of the financial system is critical to our success. At the same time, we all want efficient government as well. And critically, we need to ensure that the system of oversight continues to allow the financial sector to provide the high level of innovation and leadership that has propelled the prosperity of our market‐based system for over two centuries.
This is where information technology must take its place in the process. All around us, we see evidence that the proper use of technology can generate immensely valuable results while at the same time improving efficiency and reducing costs. Now is the time to apply technology to address this most important issue.
The good news is that a vast amount of work has already been done with technology in finance. Technology has advanced to the point where the oversight of large, complex financial enterprises is now feasible. In fact, large organizations around the globe routinely use technology for financial risk management. One of the key areas in this regard is in the management of risk data and analytics.
Use of Data and Analytics in Financial Institutions
Financial institutions have been using information technology to improve the efficiency of their operations for quite some time. Information technology makes it possible for companies to collect, merge and analyze very large amounts of customer data in real time to better and more efficiently serve their customers, leading to competitive advantage. Technology has also made it possible for financial firms to manage their risks effectively while managing substantial growth and consolidation in their business lines. For example, banks are able to serve a significant growth in customers even as they keep a tight control on fraud through the use of advanced, real‐time information technology that utilizes data related to current activity and provides insight into and comparisons with historic trends and behaviors. Other banks have developed systems that give them a view to their firm‐wide risk exposure on a frequent basis.
It may well be asked why, with all these advanced systems, these financial institutions experienced such unprecedented losses during the economic crisis. The answer is simply that technology can only be useful if it is employed properly ‐ it was not properly employed to deal with the types of toxic assets that caused these catastrophic losses.
Transparency and Financial Oversight
Transparency is the cornerstone of financial oversight. While it is not desirable for the public at large to have complete transparency into the operations of financial institutions, it is important that transparency is preserved for regulators charged with oversight responsibilities, without undermining consumer privacy. Put in the context of financial information, transparency can be understood as that quality that gives all stakeholders full confidence in the veracity of that information.
It is important to realize that trust lies at the heart of transparency. It is only in unusual circumstances, or at very high cost, that financial information can be demonstrated to be completely authentic. There are numerous areas where users of such information (e.g. shareholders, banking customers, regulators, etc.) simply have to believe that its preparers have performed according to expectations. While this may seem like a tall order, examples of relative transparency are all around us. Every day financial analysts and ordinary investors rely on financial reports issued by companies. An even more practical example is the implicit belief we all have that the account statements we receive from our bank accurately reflect the balance of all our transactions.
In these cases, transparency relies on at least two principles:
1. The goals of information disclosure are well understood: In the case of our bank accounts, we want to understand, in as timely a manner as possible, the accurate financial state of our accounts. In the case of financial reporting by companies, the goal is to give as full a picture of the company’s performance as possible. In both cases, we understand what action (or non‐action) is needed as a result of the information being timely and accurate.
2. The information assembly line is robust: Data needs to be complete and detailed while it is transformed into useful information as it moves from the transaction systems to the point of disclosure. Confidence in the reported information can only be gained when there is confidence in the robustness of the assembly line (for example, via knowledge that all changes during the process of creating the information are fully audited and controlled).
The following comments will focus on the subject of the information assembly line.
Information Needs of Financial Oversight
Financial oversight depends critically on a deep understanding of the situation at hand at all times. There are two broad aspects to be addressed – monitoring and predictive analysis.
First, there must be an efficient system for monitoring known risks. If the monitoring system does identify warnings, there must be an efficient, quick way to analyze the situation to get to the root cause of the problem. But just monitoring known risks is not enough. It is critical for an oversight mechanism to also constantly be on the lookout, via predictive analysis, for risks that are not known. A robust and efficient information assembly line is critical to both functions.
A monitoring system expects to see the same data within pre‐defined periods of time such as every day, every month or every quarter. The mathematical models that are run on this data must necessarily be the same every period, so that periodic comparisons can be done. Unexpected deviations in the output of these models act as warning indicators. Once warnings are seen the system must allow the ability for rapid, flexible research into the root cause of the problem so proactive steps may be taken. Data used must be “industrial‐strength” – it must be prepared to standards of high‐quality and timeliness.
The parallel track of predictive risk analysis can be likened to scientific research, which requires a system with immense flexibility. Economists and regulators looking for new problems use a “test‐and‐learn” process. That is to say, they first have a hunch of what can go wrong. Then they use information to either confirm or invalidate their hypothesis. The information system must therefore be able to answer their questions “at the speed of thought”. Furthermore, the system must serve up this information without having a pre‐conceived notion of what they will want to know about. The system must also be able to incorporate information from new sources on demand.
The two drivers of oversight therefore have conflicting needs – industrial‐strength robustness vs. lab‐environment flexibility. What is exciting about today’s information technology capabilities is that both of these needs are being satisfied by the same analytic system, to at once support a complete, robust oversight environment that is also cost‐effective. For example, some leading financial companies are using such systems to stop fraud in real‐time (via monitoring) as well as enabling users (via predictive analysis) to develop newer, more effective models to stop the next‐generation of fraudsters, both tasks being performed on the same system.
The Information Assembly Line
Information is knowledge derived from raw data. Data collected from across the financial sector for the purposes of oversight must be interpreted before it is useful. A series of steps is required to cleanse data before it can be used and interpreted. It is only after data is conformed in this manner that it can be analyzed in ways consistent with the goals of financial oversight.
The process is similar to that within a factory assembly line. The raw material is data that is collected from across the financial landscape. This includes not only information from financial firms but also relevant market and statistical data from a number of sources. Data then needs to be cleansed and otherwise modified so that data from all sources are brought into parity. This can be likened to a manufacturing process where raw material is processed to deliver finished goods – in this case the output is information. One departure from this analogy is that the “raw material” of input data is still available after processing, allowing one to isolate inputs to further confirm hypotheses.
The finished goods must be stored in a warehouse before being distributed – the Data Warehouse. The data warehouse then serves to distribute information both for monitoring and predictive analysis. Statistical analysis software, for example, is used to reduce large amounts of data to easily interpretable figures. Financial models are being developed and run periodically against data in the warehouse – the results of these models are critical to the monitoring process and, once validated, can eventually become part of the monitoring system. Finally, information must be distributed to regulatory authorities and other information consumers. This specialty is called Data Visualization. Data is aggregated and presented in ways that can bring to life trends and patterns so they are easily understood. A key issue in data distribution is that of data privacy, which has been a focus of effort for most firms in the industry.
This data assembly line just described is becoming accepted as a common way of creating processed information from multiple sources of data. Large technology firms from across the industry espouse essentially the same vision, and their customers in every industry are responding by implementing this vision in their enterprises.
Leveraging Information Technology for Financial Oversight
Chairman Moore and members of the Subcommittee, this is very good news for consumers of such technology. Having a preponderance of firms marching towards a
common vision results in various parts of this assembly line being perfected at the same time. For example, there are a number of high‐performance offerings that deal with the quality of raw data. Technology for data warehousing has developed to the extent that it is not uncommon to see systems where firms are able to react in seconds to customer activity, yielding huge returns on the investment in technology. Finally, analytics and visualization technologies have also advanced significantly so that complex calculations can be completed and presented extremely rapidly for quick response. In line with what may be expected of technology advances in general, not only are the capabilities improving at a tremendous rate, but costs are also dropping precipitously. Simply put, the time has never been better for leveraging information technology to create a strong system of financial oversight – it is proven and successful and can be implemented today.
Again, thank you for the opportunity to testify this morning. I look forward to answering your questions.
Posted by dkrishna at 01:50 PM
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December 18, 2008
A ray of sunshine on TARP
"Sunshine", Justice Brandeis famously said, "is the best disinfectant". Last week I had the interesting experience of seeing this in action at the hearing of the House Financial Services Committee to consider a report by the Government Accountability Office (GAO) on the Treasury Department’s implementation of TARP (you can see the full hearing on C-SPAN's web-site).
My first experience doing this sort of thing - it's fascinating to see the gears of government working up-close.
For those who haven't kept up on the day-to-day action on TARP, there is big debate about the use of the $700 billion approved by Congress this October. The Treasury secretary had initially suggested that the funds would be used to absorb mortgage debt and stabilize the market (both in the form of whole loans as well as debt securities - MBS, CDOs and other mortgage securities). Reacting to market events the Treasury instead used the first $350 billion tranche of these funds to buy preferred stock in various banks both large and small (see the latest Treasury Transaction's report for details). Secretary Paulson's argument for this decision is that the objective of saving the US financial system can be best met by better capitalizing the rather than buying up assets. This is certainly a viable argument for anyone who understands the multiplier effect of banking. The hope is that well-capitalized banks can inject credit into the economy as a whole, easing the crisis and letting ordinary Americans and their small businesses get on with their lives.
Lawmakers, on the other hand, are furious about the switch. Largely, I think, due to the perception it creates of helping "rich Wall Street bankers" at the expense of "Main Street". Trickle down economics, it appears, is a powerful argument when it comes to taxes, but not so in the credit markets. The promised expansion of credit has not reached the consumer - or in the minds of Congress - the voter. What has exacerbated this debate are some unfortunate, sensationalized, but coincidental events such as Bank of America's decision to exercise its options to buy an additional $7 billion stake in China Construction Bank. While it's not clear that Bank of America figuratively took this money from the same pot into which TARP capital infusions were made, the timing sure looks suspicious to anyone not familiar with the arcana of bank capital management. The call of the day is for increased transparency into how banks are utilizing the funds invested by the tax-payer.
The matter is of course not quite as simple as it sounds. Banks don't simply take capital infusions and "spend" it on loans. Rather they apply leverage to these funds by borrowing in the market (through depositors, the Federal Reserve or anyone else) and then lending these funds out to small businesses, individuals and other on "Main Street". If your simply following cookie crumbs to see where the money ended up, it comes to an abrupt halt at the point of the purchase of preferred stock. There is no obvious way to link the purchase of $25 billion in preferred stock to a $100,000 small business loan made to someone in Peoria.
If direct transparency is not possible, perhaps indirect methods must suffice. The report by the GAO (see here) lays out some of these methods. After all, what Congress is seeking to ensure is that the infusion of TARP money into the banking system results in actions that improve the overall condition of the economy and also have positive effects on individual consumers. For example, small businesses must find it easier to borrow to run their businesses. Another issue that has come up lately, given its little-guy appeal, is the easing of the crisis in the mortgage market by applying modifications to mortgage loans. All these purposes would be seen as legitimate use of TARP funds, at least in the eyes of lawmakers and those who hold the purse strings to the second tranche of TARP worth $350 billion.
In this sea of accusations and counter-recriminations, largely unsupported by actual facts, the situation is crying out for is more information. Anything that can correlate the infusion of TARP funds to economic stability would be useful at this point. This point is not lost on the government auditors. They note in the GAO report that there are several economic indicators that could suggest the impact of the TARP infusion on the markets. Among them:
1. Treasury-LIBOR spread (TED spread)
2. Corporate spreads
3. Mortgage market indicators: Mortgage Rates, Origination volumes, Foreclosure and default rates
A host of other indicators can also be used such as the prime lending rate, CP rates, Stock prices, House prices etc. The problem with all these indicators is a variety of factors affect them including the actions by the Federal Reserve, FDIC and FHFA. Global economic conditions will also have effects to the point that it may be difficult to show unequivocally that the $350 billion capital injection positively influenced the credit situation in the US economy.
One suggestion in the GAO report has intriguing possibilities - this is to study the FFIEC call report data that banks and thrifts have to report quarterly. This is a compendium of vast quantities of financial data on each bank, parts of which are available to the public (data hounds can find lots of interesting information here). The call report data - available in XML format as well as in a more traditional PDF format - can, over time, give a comprehensive overall picture of the functioning of the economy. The way I would see this happening is for Treasury to build some kind of dashboard showing key metrics from call-reports for all banks. Metrics such as "Other consumer loans (includes single payment, installment, and all student loans)" could be tracked over time and correlated with the infusion of funds to banks.
What would be even more compelling is if this analysis could show where the lending activity is going - for example by industry. A sure-fire attention getter in Congress would be to show this by state. Of course the data is not available at this level of detail. Nor is data available at frequent enough intervals - quarterly reports are just too slow for to meet the transparency needs of an angry public. But these are issues that can be addressed - especially since the advent of XBRL technology within this process.
Transparency to TARP funds is achieveable. These are problems will have to be addressed - but as the old saying goes where there's a will there's a way.
All comments will be much appreciated.
Posted by dkrishna at 09:44 PM
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