Risk Shifting and Regulatory Arbitrage

50 Pages·2017·0.82 MB·English

Risk Shifting and Regulatory Arbitrage: Evidence from
Operational Risk
Brian Clark* Alireza Ebrahim
[email protected] [email protected]
June 23, 2017
ABSTRACT
Regulations leading up to the financial crisis of 2007-2009 provided incentives for banks shift their
risk profiles toward less regulated areas. We focus on the case of operational risk which went from
being a relatively benign and largely unregulated risk type to a major risk that now accounts for
about 25% of large banks’ risk profiles. We show that capital-constrained banks aggressively took
on operational risk as a means of regulatory arbitrage. Indeed, this contributed to operational
risk’s rise to prominence as a leading risk type in the financial sector and worsened the effects of
the crisis.
JEL classification: G00, G11, G18, G21, G28
*BrianClarkisthecontactauthor. HeisatRensselaerPolytechnicInstituteandtheOfficeoftheComptrollerof
theCurrency(OCC)[email protected]. AlirezaEbrahimisattheOCCandcan
[email protected]. Theviewsexpressedhereinarethoseoftheauthorsaloneanddonot
necessarilyrepresenttheviewsoftheUSOfficeoftheComptrolleroftheCurrencyortheUSTreasury. WethankMike
Carhill, Filippo Curti, David Malmquist, Jonathan Jones, Bill Francis, Christopher Martin, Marco Migueis, Robert
Stewart,QiangWu,andseminarparticipantsatFordhamUniversity,RensselaerPolytechnicInstitute,StonyBrook,
the OCC, the 2016 International Economics of Banking and Finance Conference, and the 2016 Risk Quantification
Forum for helpful comments and suggestions. All errors are our own.
1. Introduction
“Given the complexity of today’s banking markets and the sophistication of technology
that underpins it, it is no surprise that the OCC [Office of the Comptroller of the
Currency] deems operational risk to be high and increasing. Indeed, it is currently at
the top of the list of safety and soundness issues for the institutions we supervise.
This is an extraordinary thing. Some of our most seasoned supervisors, people with
30 or more years of experience in some cases, tell me that this is the first time they
have seen operational risk eclipse credit risk as a safety and soundness challenge. Rising
operational risk concerns them, it concerns me, and it should concern you.”
-Thomas J. Curry, Comptroller of the Currency (2012)1
During the financial crisis of 2007-2009, large U.S. banks proved to be under-capitalized. While
there is still debate as to the extent of the under-capitalization and the root cause, few would
disagree that lapses in regulation were at least partially to blame and contributed to the excessive
risk taking that ultimately resulted in the largest government bailout of the U.S. financial sector
in history and led to the worst recession since the Great Depression of the 1930’s.
Inthispaper,weshowthatweaknessesinregulationsleadinguptothecrisisprovidedincentives
for banks to increase their overall risk and shift their risk taking to less regulated risk areas,
and in particular increase their exposure to operational risk. Such regulatory arbitrage not only
contributed to banks’ under-capitalization in that time period, but also gave rise to the magnitude
and importance of these less regulated risk streams, including operational risk, as components of
the overall systematic risk in the financial industry. Indeed, the viability of operational risk as
a mechanism for regulatory arbitrage during this time contributed to its rise to prominence as a
leading risk type in the financial sector as highlighted by the above quote.
More generally speaking, we show one channel by which unintended consequences of financial
regulations can contribute to the emergence of new risks that can stretch well beyond the financial
sector. In particular, operational risk was unregulated prior to the crisis in the sense that banks
were not required to hold additional equity capital to cushion against operational losses. This
provided banks with an incentive to shift their risk profiles and take on unprecedented levels of
1ThisquoteisfromThomasJ.Curry’sMay16, 2012speechbeforetheExchequerClub. Fulltextisavailableat:
https://www.occ.gov/news-issuances/speeches/2012/pub-speech-2012-77.pdf. Comptroller Curry is the chief officer
of the Office of the Comptroller of the Currency (OCC).
1
operational risk and thus increase their overall risk exposure at the expense of the stability of the
financial sector.
Operational risk is broadly defined as the risk of a loss due to the failure of people or processes.
Inthebankingindustry,thisessentiallyincludesallrisksoutsideofthetraditionalcreditandmarket
risks. Credit risk is largely driven by a bank’s loan portfolio and market risk largely arises from
tradingactivities. Operationalrisk, however, ismorebroadlydefinedandcapturesalmostanything
that does not fit into the other categories and today accounts for about 25% of the risk on large
banks’ balance sheets. Examples of operational risks include process breakdowns that led to rogue
traderssuchasthe“LondonWhale,”2 fraudulentactivitiessuchastheforeignexchangeandLIBOR
rate rigging scandals, operational failures related to the sale of mortgage back securities, incentive
structures that lead to actions such as improper sales practices, and the resulting regulatory fines
and class action lawsuits. The magnitude of these operational losses are huge and the underlying
behaviors undoubtedly exacerbated the magnitude of the recent financial crisis. For example, the
Boston Consulting Group (2017) estimates that North American and European banks have paid a
total of $321 billion in fines since the crisis, primarily due to actions related to the above examples.
The increase in operational risk in the banking industry also had real consequences because the
effects of banks’ operations can reach beyond the financial sector and directly affect the real econ-
omy. Forexample, laxmonitoringandcontrolsbybanksledtotheforeclosuredebaclethataffected
thousands of homeowners after the crisis as banks systematically mishandled mortgage documents,
adversely affecting borrowers. Poor monitoring and incentives of bank employees have also led
to operational failures such as the recent Wells Fargo cross-selling scandal where bank employees
created fictitious accounts in customers’ names, thus directly affecting hundreds of thousands of
consumers. Even operational events like the LIBOR and foreign exchange rate rigging scandals
had far-reaching consequences on the economy as a whole as banks were accused of manipulating
key interest and exchange rates.
To highlight how important operational risk has become in the banking industry, Figure 1
2TheLondonWhalereferstothelossessufferedbyJPMorganChaseasaresultofaroguetradingincident. The
details of the U.S. Senate report on the loss is United States Senate (2013)
2
shows the breakdown of banks’ risk profiles by risk type for nine large U.S. banks as of 2015:Q3.3 4
Overall, operational risk accounts for roughly 25% of large banks’ total risk profiles in terms of risk
weightedassets(RWA)andismorethan2.75timesgreaterthanthelevelofmarketriskexposureat
these institutions. At the individual firm level, JP Morgan Chase attributed $400 billion of RWA
to operational risk in 2015:Q3 which is nearly equivalent to Morgan Stanley’s $423 total RWA.
Morgan Stanley is the sixth largest U.S. bank. So by any measure, operational risk has grown to
become a significant source of risk to U.S. banks.
[Place Figure 1 about here]
In addition to its economic magnitude, operational risk has a few characteristics that make
it worthwhile risk type to study how banks respond to regulations and manage risk. First, it
was largely unregulated leading up to the crisis which made it susceptible to regulatory arbitrage.
Second, operational losses tend to be heavy-tailed, so increasing operational risk exposure is a
viable way to take on, or manufacture, tail risk. As discussed by Acharya, Cooley, and Richardson
(2010), leading up to the crisis banks had incentives to manufacture tail risks that were systemic in
nature. Taking on operational risk was one channel through which banks could effectively expose
themselvestotailriskwithouthavingtoholdcapital. Manyofthelargeoperationallosseswerealso
systemic in nature as they stretched across a number of banks that were involved in the same or
similar events (e.g., high profile cases such as LIBOR manipulation and mortgage-related lawsuits).
Third, the nature of operational risk is such that there is often a significant time lag between
the decision to take on operational risk and the time when losses are incurred from an accounting
standpoint. For example, a reluctance to invest in and maintain proper IT infrastructure increases
net income by limiting short term costs but also increases the probability of major failures months
or years down the road. Fraudulent behavior such as interest rate manipulation schemes also take
time to detect, all the while a bank is (presumably) booking short term trading gains. Operational
3Thefigureshowsthepercentageofriskweightedassets(RWA)allocatedtothethreemainrisktypes–operational,
credit, and market – and a fourth category of miscellaneous adjustments. The nine banks shown in the Figure 1
are the only ones publicly reported risk-based capital numbers under Basel II capital regulations as of 2015:Q3.
The miscellaneous category includes credit value adjustments (CVA), assets subject to general risk-based capital
requirements, and less excess reserves.
4Note that the RWA numbers in Figure 1 based on Basel II regulations that were not in place prior to 2010.
However, they are a useful benchmark to gauge the extent of operational risk exposure vis–a`–vis other risk types in
large financial institutions.
3
losses such as rogue traders often stem from a root cause of poor internal control systems that
are put in place months or years before losses occur. In addition, bank managers may have the
abilitytoprolonglitigationsinordertodeferrealizationofcertainoperationallosstypes. Theseare
important examples to understand the nature of operational risk because they show how managers
can effectively book short term gains in the form of increased trading revenue, reduced operat-
ing costs, or inflated accounting profits by taking on operational risk. As such, operational risk
management is not purely a cost minimization problem; rather mangers have profit motives for
increasing operational risk exposure. For example, Chernobai, Jorion, and Yu (2011) show that
managerial incentives that focus on short-term metrics are positively related to the frequency of
operational losses.
However, despite the sheer magnitude and apparent importance of operational risk to financial
regulators, supervisors, market participants, and the economy as a whole, it is still up to debate as
to how it came to play such a major role in recent years. We therefore ask the questions of how
and why did operational risk grow from a seemingly innocuous risk type to play such a prominent
role in bank risk management?
We hypothesize that weaknesses in regulations contributed to the excessive amounts of opera-
tional risk in today’s banking sector. The specific regulations we use to identify our tests are the
Basel I capital accords. Under Basel I, U.S. banks were not required to hold capital for operational
risk which meant that regulatory capital-constrained banks could shift their risk profiles in favor of
operational risk to avoid capital charges; a process commonly known as regulatory arbitrage. Do-
ing so enabled banks to increase their overall risk exposure without having to hold commensurate
loss-absorbing capital buffers and thus contributed to the widespread effects of the crisis.
Our main testable hypothesis is that capital constrained banks took on operational risk to shift
their risk profiles and effectively engage in regulatory arbitrage. To identify our tests, we exploit a
rich set of operational loss data collected by regulatory agencies for a sample of large U.S. banks.
The data includes the universe of operational losses collected by our sample of banks. Depending
on the institution, reliable operational loss data collection dates as far back as 2001. The data is
collected by the Federal Reserve on a quarterly basis and is part of the FRB Y-14Q data series.
We merge this data with data from the Federal Reserve’s FRB Y-9C data to control for bank
characteristics.
4
Our data has several unique features that allow us to examine our research question. First,
banks report every operational loss event above a low collection threshold so this is the most
comprehensive set of operational loss data currently available and the cross-sectional nature makes
it even richer than banks’ own internal data. Second, banks report detailed information for each
loss. Importantly they assign and report an occurrence date, discovery date, and accounting date
for each loss. The accounting date is the date at which the loss hits the income statement. The
discoverydateiswhentheoperationaleventisdiscovered. Theoccurrencedateisthedatetowhich
the bank is able to trace the root cause of the operational failure.
Theoccurrencedateisvitaltoouridentificationstrategybecauseweuseittoproxyoperational
risk exposure. In doing so we assume that loss occurrence amounts are proportional to overall op-
erational risk exposure. This is important because measuring operational risk exposure is different
from credit or market risk applications where you can define exposure based on the size of the cur-
rent loan or trading asset portfolio. Additionally, we are more concerned with when banks take on
operational risk exposure (i.e., the occurrence date) than when losses are realized (the accounting
date) because we are hypothesizing that banks take on operational risk for regulatory arbitrage
purposes. Therefore changes in exposure should be more indicative of risk shifting behavior as
compared to the realization of losses which often occur months or years after managers shift their
risk profiles toward operational risk. We discuss this in detail in Section 3.
Our empirical design is similar to Acharya, Schnabl, and Suarez (2013) who test for regulatory
arbitrageintheasset-backedcommercialpaper(ABCP)market. Westartbyregressingmeasuresof
operational risk exposure on measures of capital adequacy (regulatory capital and leverage ratios).
Weshowthatleverage, definedasequitydividedbytotalassets, isnegativelyrelatedtooperational
risk exposure. This finding is robust to several different model specifications. We focus on leverage
because the relation between regulatory capital ratios and regulatory arbitrage is likely to be
downward biased. The reason is that banks engage in regulatory arbitrage to increase regulatory
capital ratios so the relation between regulatory capital and regulatory arbitrage should be muted
to the extent that banks can effectively increase risk that is not reflected in their regulatory capital
ratios. Also, as discussed by Acharya et al. (2013) and shown by Demirguc-Kunt, Detragiache,
and Merrouche (2013), leverage ratios have been shown to be better predictors of financial distress
and bank stock returns than regulatory capital ratios.
5
We conduct several robustness tests. First, we employ first-difference regressions to control
for possible spurious correlations that could be driving the relation between capital adequacy and
operational risk. We then test conditional models whereby we test the relation between economic
capital ratios and operational risk conditional on banks’ regulatory capital ratios. Consistent with
our expectation, banks operating closer to their regulatory capital minimums exhibit more aggres-
sive risk shifting behavior because regulatory capital constraints push them to take on operational
risksthatcarrynocapitalcharge. Wealsoconsideraplacebotestusinglossaccountingdateswhich
should not have a strong relation with measures of economic capital because many of the losses are
realized well after the operational risk exposure is undertaken. We find no relation between the
realization of operational losses based on accounting dates and leverage. All of these robustness
tests support our main finding. Additionally, we show that capital constrained banks are likely
to increase the duration of operational risk exposure suggesting that operational exposures that
prolong the realization of losses are preferred.5
We contribute to the literature in several ways. First, we show that operational risk is one
mechanism through which financial regulations can have unintended consequences that affect the
realeconomy. Inparticular,ourresultssuggestthatthelackofregulationofoperationalriskleading
up to the crisis contributed to the emergence of operational risk as a leading risk type in banks’
risk profiles in today’s banking sector. Given the fact that operational risk, which was previously
unregulated, now comprises roughly 25% of banks’ total risk, this is an important finding. Other
papers show that regulations can have unintended consequences in other areas. For example, Keys,
Mukherjee, Seru, and Vig (2009) show that more heavily regulated banks actually originated lower
quality mortgages in the originate to distribute model leading up to the crisis. Gropp, Hakenes,
andSchnabel(2011)showthatpublicguaranteeshaveunintendedconsequencesbeyondtheobvious
increaseinmoralhazardofregulatedbanksinthattheyactuallymakecompetitorbanksmorerisky
as well. Agarwal, Lucca, Seru, and Trebbi (2014) show that even the implementation of consistent
regulations can vary in how they are implemented. More broadly, there is a stream of literature
that focuses on how banks respond to government actions such as too big to fail guarantees and
5Our measure of the duration of operational risk exposure is conceptually similar to the duration of a bond. It
referstoaweightedaverageofthelengthoftimebetweenthedatethatbankstakeonoperationalriskexposure(the
loss occurrence date) and when losses are realized from an accounting standpoint. A longer duration means losses
take longer to realize. We define the measure in Section 5.2.4.
6
deposit insurance. Most of these papers focus on the role of bailout policies on banks’ overall risk
taking behavior. For example, Duchin and Sosyura (2014) show that bailed out banks increase
their risk in ways that are difficult for regulators to detect. We contribute to this area by showing
one specific risk type that allowed banks to leverage up while still complying with regulations.
We also contribute to the closely related literature on regulatory arbitrage. Most papers that
study regulatory arbitrage focus on weaknesses in the regulation of complex financial instruments
such as mortgage backed securities (MBS) and other derivatives or examine large-scale investment
decisions such as cross-border acquisitions (Karolyi and Taboada, 2015). For example, Acharya
et al. (2013) show that banks underwrote ABCP conduits to shift risk off their balance sheets
to avoid holding regulatory capital. The issuing banks retained much of the ABCP and suffered
the losses when they defaulted during the crisis, thus suggesting that the risk transfer was done
primarily to evade capital regulations. Demyanyk and Loutskina (2016) show similar evidence
of regulatory arbitrage in the shadow banking market and in particular the securitized mortgage
markets. Even prior to the crisis papers such as Jones (2000) provided caution that banks could
effectively work around capital regulations to engage in regulatory arbitrage. A more recent paper
by Boyson, Fahlenbrach, and Stulz (2016) shows that some banks issued trust–preferred securities
(TruPS) as a form of regulatory arbitrage but this behavior was limited to capital constrained
banks suggesting that not all banks engage in regulatory arbitrage.
We argue that taking on operational risk is fundamentally different than investing in or issuing
specific financial products as in the aforementioned papers. Importantly, taking on operational risk
exposure does not necessarily require banks to be involved with complex financial products such as
ABCP (Acharya et al. (2013)), MBS (Demyanyk and Loutskina (2016)), or even TruPS (Boyson
et al. (2016)). This is important to note because the majority of the papers in this area focus on
specific loopholes in regulation that banks were able to exploit using innovative financial products.
With regards to operational risk, regulators overlooked a broad type of risk present at all financial
institutions that once measured turned out to account for roughly one quarter bank risk.
In summary, we provide evidence that financial regulations can have far-reaching consequences
that stretch beyond the financial sector. In particular, a lack of regulation of operational risk
contributed to its rise to importance as a portion of banks’ risk profiles, ultimately culminating in
a risk type that now accounts for about 25% of large banks’ total risk. We find evidence consistent
7
with the hypothesis that banks actively took on operational risk exposure prior to the crisis in an
attempt to shift risk and engage in regulatory arbitrage. While new regulations require banks to
hold capital for operational risk, it is an important source of risk that should not be overlooked
by regulators or academics. Our results also support the notion that regulatory arbitrage in the
banking industry does not necessarily have to involve complex financial instruments as much of the
operational losses have little to do with complex financial instruments or financial innovations gone
awry. One implication is therefore that human behavior, a driving force behind operational risk, is
an important risk factor for banks.
2. Related Literature
Although excessive risk taking is not specific to banking sector, it seems to be a more severe
problem in banks. The classical concept of risk shifting refers to the moral hazard problem that
arises from separation of ownership and control (Jensen and Meckling (1976)). However, the risk
shifting in the banking industry that we refer to is a slightly different problem whereby banks have
an incentive to take on excessive risk beyond their regulatory capital requirements. As such, banks
shift from risks for which they would have to hold capital to risks that carry no explicit capital
requirements.
Extant literature suggests that securitization and other recent financial innovations have en-
abled banks to substantially elevate their portfolio risk relative to their regulatory capital through
regulatory capital arbitrage. For example, Acharya et al. (2013) provide evidence of regulatory ar-
bitrage in the ABCP market and Demyanyk and Loutskina (2016) show that regulated depository
institutions were able to use the shadow banking sector to engage in regulatory arbitrage. Other
papers show that inefficiencies or lapses in regulation contributed to the extent of risk shifting and
regulatory arbitrage in the financial sector. Keys et al. (2009) argue that increased regulation of
financial institutions actually worsened the moral hazard problem in the mortgage securitization
market and as such market forces would have been more effective means to properly incentivize
lenders than regulations.
More generally, there are a number of papers that document changes in bank behavior in
response to regulatory actions such as capital requirements, reserve requirements, and deposit
8
insurance premiums (see, Cumming et al. (1987),Baer, Pavel, et al. (1988), Jagtiani, Saunders, and
Udell (1995), Pennacchi (1988), James (1988), Merton (1995)). These papers provide a context
for our study that focuses on the link between risk shifting, regulatory capital requirements and
operational risk.
There are a number of theoretical reasons for risk shifting in banking sector. First, banks
typically desire to have high levels of leverage and risk-seeking banks have incentives to take on
risk beyond their regulatory limits. The most notable incentives are due to the presence of explicit
and implicit government guarantees that result in privatized gains and socialized losses (see, e.g.,
Bhattacharya and Thakor (1993), Admati, DeMarzo, Hellwig, and Pfleiderer (2011), Admati and
Hellwig (2014), and others). The opaqueness of banking assets and risk management practices also
facilitates risk shifting (Myers and Rajan (1998), Diamond and Rajan (2000)). Another strand
of literature suggests that regulatory arbitrage is an unintended consequence of minimum capital
standards. These papers argue that regulatory standards would cause bank capital and asset risk
to become substitutes and consequently, banks facing increased regulatory capital charges would
achievetheirdesiredtotalrisklevelbyincreasingtheirassetrisk. Accordingly,thesestudiessuggest
a potential positive relationship between regulatory capital and risk in banks that operate at or
above regulatory capital minimums (see Kahane (1977), Koehn and Santomero (1980), Kim and
Santomero (1988), Gennotte and Pyle (1991), Blum (1999)).
On top of the already sizable incentives to risk shift, incentives for risk shifting are stronger
when shareholders’ stake in the bank is smaller. This is the main reason why capital requirements
are in place to force shareholders to keep some “skin in the game” (Demirguc-Kunt et al. (2013)).
Therefore, the presence of a negative relationship between changes in risk and capital (or leverage)
ratios in risk seeking banks is a sign of risk shifting. There are several studies in the literature that
documentanegativerelationbetweencapitalratiosandassetrisk. Forexample,FurlongandKeeley
(1989) demonstrate that capital requirements reduce banks risk-taking incentive. Also, Jacques
and Nigro (1997) find that increases in banks capital ratios, caused by risk-based capital standards,
resulted in lower portfolio risk in the banks. Focusing on the impact of FDIC improvement act
of 1991, Aggarwal and Jacques (2001) find that while banks increased their capital ratios, they
reduced their level of portfolio risk. More recently, Rampini, Viswanathan, and Vuillemey (2015)
show that poorly capitalized banks banks tend to reduce hedging.
9