Given the vastness of today's global financial system and the volume and complexity of data that financial institutions must deal with every day, firms must learn how to proactively manage liquidity risk and avoid the pitfalls that sparked past financial crises. Predictive analytics and advanced risk-monitoring systems are among the tools available to help these institutions overcome the challenges of doing business in an increasingly connected world.

1. •
Cognizant 20-20 Insights
Enterprise Liquidity Risk: Overcoming
the challenges
Predictive analytics and advanced risk-monitoring systems are some of
the tools available to financial institutions looking to minimize liquidity
risk in an increasingly connected world.
Executive Summary
“…The U.S. financial system experienced
conditions that were among the most difficult
and chaotic in its history. Waves of bank failures culminated in the shutdown of the banking
system (and of a number of other intermediaries
and markets). On the other side of the ledger,
exceptionally high rates of default and bankruptcy affected every class of borrower except
the federal government.” 1
Even though the statement above very closely
summarizes the financial crisis of 2008, it is
not about that (the most severe financial crisis
of recent times). It is an excerpt from a 1983
working paper by Federal Reserve Chairman
Ben Bernanke, who was then a student studying
the Great Depression of 1929.
Liquidity risk – the risk that a given security or
asset cannot be traded quickly enough in the
market to prevent a loss – is not a new phenomenon in financial markets. In fact, liquidity risk
has been a significant factor in most previous
financial crises, from the Great Depression to the
Latin American debt crisis. Each downturn has
cognizant 20-20 insights | december 2013
thrown new challenges at the financial industry –
leading to changes in regulations such as the
Securities Act of 1933 and the Sarbanes Oxley Act,
and altering the way banks and economies operate. The most recent financial crisis is no different.
In this paper, we will provide a historical perspective on the role that liquidity risk played in earlier
financial crises. We will also discuss challenges
that banks and financial institutions traditionally face when building operations, platforms
and infrastructures to manage liquidity risk. We
will then offer our point of view on how to better manage liquidity risk operations in light of
new dynamics, such as the increasing interdependencies within the global financial system,
the abundance of data, and new technologies
that have added dimensions to an already
complex liquidity problem. Finally, we will provide recommendations for how banks can better
manage these challenges.
Liquidity Risk – A Fundamental
Understanding
Shakespeare’s play, “Merchant of Venice,” is
a good primer for understanding the complex

2. financial concept of liquidity risk. In the play,
Shylock loans money to Bassanio with Antonio’s
ships at sea as collateral. Antonio’s ships are then
rumored to have been wrecked at sea, leaving
him unable to repay the loan. In financial terms,
the asset that was used as collateral was impaired –
presenting the risk that the outstanding liability would not be met. This is known as funding
liquidity risk2 – one of two types of liquidity risk.
The other type of liquidity risk is market liquidity
risk.3 This arises when the market is unwilling to
buy your assets, or at least not at the price you
want. To extend our analogy, if Antonio’s ships
had arrived safely but the ships carried goods
that were already abundant in Venice, Antonio
would have been exposed to market liquidity risk,
since nobody in the market would have wanted to
buy the goods that those ships brought.
Both funding liquidity and market liquidity risks
have played a key part in all financial crises.
Understanding the role of liquidity risk in past
financial crises is necessary in order for individuals and institutions to prepare for the future.
Liquidity Risk and Past Financial
Crises
Crash of 1929 and the Great Depression
The crash of 1929 and the Great Depression followed the speculative boom in the 1920s. From
steel production to railway receipts, everything
was rising.4 Hundreds of thousands of Americans
invested in stock, many with borrowed money.5
A crucial factor contributing to the bullish stock
market was the favorable commodity outlook in
the 1920s, especially for wheat production. When
wheat prices were at their peak in the U.S., France
and Italy boasted about their own robust wheat
production – sending wheat prices plummeting in
the U.S. This sent shivers down the stock market.
Panicked investors who had bought stocks with
borrowed money now started selling – depressing
the stock markets even further.
This led to massive defaults by individual
borrowers, causing banks to suffer severe losses.
Structural support like today’s FDIC insurance did
not exist – prompting depositors to rush to their
banks. This created a run on the banks – ultimately
causing some to fail. The lack of a coordinated
government effort further complicated matters.
International trade came to a halt – affecting
millions of workers.
cognizant 20-20 insights
Liquidity risk was at the heart of the Great
Depression. Market liquidity risk caused wheat
prices to fall; funding liquidity risk saw borrowed
money flee the stock markets. Banks’ credit risk,
coupled with their liquidity risk, exacerbated the
downward spiral that lasted for a decade.
The Savings and Loans crisis of the 1980s, the
Asian financial crisis of 1997, the Latin American debt crisis of the 1980s and the 2008 Global
financial crisis followed similar trajectories.
Savings and Loan Crisis
The two decades following the end of World War II
witnessed rising economic activity and the arrival
of the baby boomer generation. Interest rates
were rising, luring savings deposits. The economy
was growing and more people were taking out
mortgages. By the mid to late 1970s, the economy
was slowing, whereas interest rates and inflation
continued to rise. Soon, the U.S. economy hit a
stage that later came to be known as stagflation –
a combination of stagnating growth and rising
inflation.6 This meant that fewer people qualified
for mortgages, which lead to losses for many S&L
institutions and caused 747 of 3,234 – or about
25% – of them to close their doors. The failed
institutions represented a total book value of
US$402 billion.7
Liquidity risk led to these institutions’ inability
to generate income, and ultimately to a severe
financial meltdown.
Asian Financial Crisis
In the case of the Asian financial crisis, South
Asian countries such as Thailand, South Korea
and Indonesia had maintained high interest
rates to attract foreign capital. This caused
heavy capital inflows into these countries, and
increased their foreign debt-to-GDP ratios
from 100% to 167% in the three years between
1993 and 1996. This worked well as long as U.S.
interest rates remained low. However, once
those rates started rising under Federal Reserve
Chairman Alan Greenspan (who wanted to thwart
inflation), these Asian countries witnessed
massive capital outflows.
Market liquidity risk – the risk that the market
would not want your assets, in this case Asian
debt – was a key reason for the Asian financial
crisis.
2

3. Latin American Debt Crisis
Global Financial Crisis of 2008
Countries such as Brazil, Argentina and Mexico
borrowed heavily to carry out industrialization
in the 1960s and 1970s. In less than a decade,
Latin America’s debt grew by 400% – from
US$75 billion in 1975 to US$315 billion in 1983.
Interest payments grew in tandem to US$66
billion from US$12 billion in the same period.
To compound the problem, in the 1970s and
1980s a global economic recession witnessed
skyrocketing oil prices, raising U.S. interest rates.
Depreciating Latin American currencies made
debt repayment much more expensive.8 This led
to a full-blown Latin American debt crisis and to
what later came to be known as “the lost decade”
for the region.
Liquidity risk was one of the key factors in the
financial crisis that lasted from 2008-2010.
Subprime mortgages were aggressively sold to
people who could not afford them. Availability
of cheap mortgages jacked up demand for real
estate, inflating prices.
It was funding liquidity risk – a risk that left Latin
America unable to service its debt – that was at
the heart of this crisis.
While banks sliced and diced the mortgage securities they owned, every bank had substantial
amounts of these assets. Additionally, all banks
were highly leveraged against these assets. When
mortgage owners started defaulting, the financial
markets witnessed an unprecedented downward
spiral of asset pricing and ultimately the bursting
of the asset bubble. The effect was pronounced –
coming in the forms of market liquidity risk for the
MBSs, CDOs and CMOs that nobody wanted to buy
anymore… funding liquidity risk for the banks that
were highly leveraged against these assets… and
liquidity risk for mortgage owners. These three
forces combined to initiate an economic meltdown.
Summary of Major Financial Crises
Crisis
Year
Affected
Asset Class
Entities Impacted
Consequences and Outcome
Wall Street
Crash of 1929
and the Great
Depression
1929 to
1939
Primarily
stocks
• Stock markets
• Commercial banks
• The U.S. and the
world economy
• Creation of Securities Act of 1933
• Creation of Securities Act of
1934 that created Securities and
Exchange Commission (SEC)
• Creation of Glass-Steagall Act
• Federal insurance of bank deposits
Savings and
Loan Crisis
1980s
and
1990s
Deposits
and loans,
primarily
mortgage
loans
• Savings and Loans
or “‘thrift’ institutions” – 747 of
3,200+ or about
25% of S&Ls failed.
• Financial Institutions Reform,
Recovery and Enforcement Act
of 1989 (FIRREA)
• Creation of Federal Housing
Finance Board (FHFB)
Asian Financial
Crisis
1997
Asian
currencies
• Countries such as
Thailand, Indonesia,
South Korea and
Malaysia
• IMF intervention and bail-outs
of most nations involved
• Political upheaval, including
the end of the 30-year rule of
Indonesian President Suharto
Latin American
Debt Crisis
1975 to
1982
Latin
American
country
debt
• Government bonds
of Latin American
countries such as
Mexico, Brazil and
Argentina
• IMF bailed out affected nations.
• Interest rates shot up – slowing
down real GDP growth.
• Per capita GDP witnessed
negative growth of 9%.
Subprime
Mortgage Crisis
Leading to
Global Financial
Meltdown
2008 to
2010
Real estate,
stocks and
mortgage;
corporate
and government bonds
• U.S. banks, insurance
and financial industry
• Mortgage firms such
as Fannie Mae and
Freddie Mac
• Greece, Ireland,
Iceland, Spain and
Portugal
• Global financial
markets
• Bailouts of major top-tier U.S.
banks
• Monetary easing in the
U.S., Europe, Japan and
other major economies
• Regulatory responses such as
Dodd Frank Act, FATCA, etc.
Figure 1
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4. New Challenges Involving
Liquidity Risk
Changes in Regulatory Oversight and the
New Normal
While liquidity risk has historically played a
significant role in all financial crises, its effects
are even more pronounced today. In addition to
the traditional challenges discussed in Figure 2
below, today’s banks face new hurdles involving
liquidity risk. We enumerate these challenges
below and, based on the experience gained from
previous financial crises, recommend approaches
that banks can adopt to successfully confront and
overcome these issues.
Complex financial products, such as credit default
swaps and collateralized debt/mortgage obligation bonds, were front and center in the recent
financial crisis. Since most of these products
were not traded on any exchange, there was a lot
of ambiguity about the quality of these assets.
Allegedly, improper ratings given to these assets
by top credit rating agencies only added to the
complexity. The Dodd-Frank Act now mandates
that all derivatives trading be conducted on
exchanges. Nonetheless, banks need to be much
more proactive and establish clear internal guidelines about what defines high-quality assets, and
ascertain with precision the quality of assets that
sit on their balance sheets. These actions would
change how banks’ balance sheets and income
statements look in the future. Given the intricacy
of business and financial products, preparing for
regulatory oversight is one of the biggest roadblocks facing banks today.
Multiplier Effect of Increased Globalization
In his book “Blink,” Malcolm Gladwell points out the
multiplier effect of information in today’s world.
This effect is even more pronounced in the financial system. Globally, economies are intertwined to
an unprecedented degree. Additionally, the world’s
biggest banks have expanded their international
presence and are now more interdependent than
ever. The result is that a single major liquidity failure in any given asset class can quickly create a
ripple effect that impacts banks across the world
and threatens the entire global financial system.
Velocity of Information
The world’s financial system today is more
transparent and more efficient than ever before.
Financial analysts now have the kind of access to
information that was unimaginable just a decade
ago. Information spreads at unbelievable velocity.
When the Wall Street crash of 1929 occurred on
“Black Thursday,” newspapers around the world
covered the story over the weekend. The world
markets therefore took four days to react to the
U.S. crash. Today, markets react instantaneously.
This poses challenges – as well as opportunities –
for banks.
Recommendations
Leverage the Power of Predictive Analytics
Banks must always be prepared for the multiplier
effect of any downward spiral. With the availability of big data and ever-increasing computing
power at their disposal, firms need to institutionalize predictive analytics to identify the next big
source of risk.
For example, it would be easy to carry out a cluster analysis to predict the mortgage default rates
of a certain neighborhood or a certain company
where many people have been laid off, then keep
a close watch on mortgage lenders that have significant exposure to these mortgage holders and
take appropriate actions as necessary. It is equally
Challenges Banks Face in Managing Liquidity Risk
Data
Sourcing and aggregation of accurate data involving cash flows, collaterals position and
transaction data from different businesses and geographies to create a global, real-time data
structure to manage liquidity risk.
Calculations
Supporting complex, advanced analytics, scenario analyses and predictive analytics at a
granular level.
Reporting
Regulatory requirements involving public disclosure, senior management responsibility and
supervisory assessment lead to complications of multiple reporting. This makes responding
quickly to frequently changing regulatory requirements across jurisdictions challenging.
Evolving
Landscape and
Moving Targets
Rapid and continuous changes are required to existing risk operations and risk technology
platforms due to evolving business requirements.
Figure 2
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5. important – and possible – to deploy predictive
analytics at asset-class levels. And it is possible to
triangulate factors that led to Detroit’s bankruptcy,
for example, and extrapolate the data to predict
what other municipalities may face a similar fate.
Predictive analytics will play a seminal role
in helping banks mitigate risk going forward.
Testament to this fact is the emergence of the
Chief Analytics Officer (CAO) – an increasingly
important position for institutions that approach
their information as a corporate asset that can
lessen risk, increase trust and add more value.
Banks will also need to beef up their risk-monitoring systems to keep up with the advancing
speed of information spread. For example, it is not
difficult to imagine a scenario where local
economic trouble at the city level in a European
country threatens a European bank that in turn
threatens its counterparties, which could be a
U.S. bank’s European subsidiary – putting the
U.S. bank’s capital adequacy at risk. A vigilant,
quick-to-respond risk-monitoring system that can
spot such risks early on and ensure banks’ speedy
response will help institutions mitigate the
challenge of information spread.
Leverage Social Media to Improve RiskMonitoring
Strengthen Internal Guidelines on Asset Quality
and Stress Testing
Today’s banks need to constantly monitor their
assets and the online “chatter” that surrounds
these resources both on and off the street.
For example, using consumers’ feedback on
social media, it is possible to track their level of
satisfaction with utilities such as toll roads and
airports, which are revenue sources for revenue
obligation bonds. This information can then be
used to predict the revenue potential of a municipality’s revenue bonds and its ultimate credit
rating. Similarly, a company’s stock performance
can be predicted based on consumers’ responses
on social media.
Banks need to establish robust internal guidelines
to identify and ascertain the true quality of their
assets – and not just because the Dodd Frank Act
mandates this. Conducting periodic stress tests
and simulating scenarios of unexpected events
will be critical to avoiding future shocks like the
recent financial crisis. If scenarios involving world
recession and sharp oil price rises had been simulated, Latin American countries would probably
have issued less debt. Banks and developed countries would have surely loaned them less money.
The financial crisis of 2008 could have been
averted if simulation of “fat tail” events had been
carried out.
Our Recommendations
Comprehensive
Rather than adopting a piecemeal approach, financial institutions must conduct a
Evaluation of
holistic evaluation of their processes, platforms and assets to optimally leverage them for
Operational and
developing liquidity risk solutions.
Technology Assets
Data Consolidation and Data
Quality
Firms require a centralized liquidity warehouse solution that creates a virtual layer for
aggregating disparate data sources. Additionally, firms need to address data-quality
issues, including data accuracy, completeness and consistency.
Collaboration
Across Groups
and Integration with Other
Platforms (Risk,
Transfer Pricing)
Firms need operations and technology teams supporting treasury, finance, credit, market
and liquidity risks to work closely with one another to identify process reusability and
leverage best practices.
Flexible Reporting
Reporting must be flexible to enable different jurisdictions, legal entities and branches to
define their respective reporting requirements within an overall framework of firm-wide
reporting.
Model Governance
Firms need to develop advanced analytical models with superior model governance,
testing and model risk management. Also critical is to ensure that all models are up-todate, that clear linkages between data, models and reports exist, and that all models are
tested with requisite scenarios.
A liquidity risk framework must be integrated with Fund Transfer Pricing capabilities for
liquidity cost attribution and collateral management platforms to account for the impact of
increasing demand for collaterals, and for prospective liquidity pressures from margin calls.
Figure 3
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6. Conclusion
Liquidity risk has been and will continue to
be an important factor in all financial crises.
The traditional challenges that banks face in
building liquidity risk operations, platforms
and infrastructure can be effectively managed
by making a holistic assessment of existing
operational and technology assets, consolidating
existing information, and building a flexible and
robust architecture.
In addition to traditional challenges, banks face
the added complexities of the multiplier effect
caused by increased globalization, the velocity
of information and changes in regulatory oversight. In preparing for future crises, banks need to
employ the power of predictive analytics, leverage
social media, and establish comprehensive internal guidelines on asset quality and stress testing.
Currently, different banks are at different
stages of adopting these measures; some have
deployed short-term remedies. Over the long
term, institutions would do well to adopt a
proactive approach and devise an appropriate
overall risk-management strategy.
Footnotes
1
Bernanke, Ben. Excerpt adapted from “Non-monetary Effects of the Financial Crisis in the Propagation
of the Great Depression.” http://www.nber.org/papers/w1054.pdf?new_window=1.
“Market Liquidity and Funding Liquidity,” by Markus Brunnermeier and Lasse H. Pederson.
http://pages.stern.nyu.edu/~lpederse/papers/Mkt_Fun_Liquidity.pdf.
2
Ibid.
3
“Broad Facts of USA Crisis.” The Daily News (Perth, WA: 1882 - 1950). November, 1929. p. 6 Edition:
HOME FINAL EDITION. http://trove.nla.gov.au/ndp/del/article/85141129.
4
Lambert, Richard. “Crashes, Bangs, and Wallops.” Financial Times. http://www.ft.com/intl/cms/
s/0/7173bb6a-552a-11dd-ae9c-000077b07658.html#axzz2huDIa15i.
5
“Savings and Loan Industry, U.S.”, EH.net Encyclopedia, edited by Robert Whaples. http://eh.net/ency
clopedia/article/mason.savings.loan.industry.us.
6
“Financial Audit: Resolution Trust Corporation's 1995 and 1994 Financial Statements.” U.S. General
Accounting Office. http://www.gao.gov/archive/1996/ai96123.pdf.
7
Schaeffer, Robert. “Understanding Globalization: The Social Consequences of Political, Economic,
and Environmental Change.” Rowman & Littlefield Publishers. January, 2009.
8
References
www.wikipedia.org.
Gladwell, Malcolm. “Blink: The Power of Thinking Without Thinking.” Back Bay Books; Little, Brown.
January, 2005.
Shakespeare, William. “The Merchant of Venice.”
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7. About the Authors
Mrugesh Kulkarni is a Senior Manager – Consulting in the capital markets domain at Cognizant
Business Consulting. With over 12 years of experience in capital markets, consulting and technology,
Mrugesh has worked in areas such as business/IT strategy, project roadmaps, portfolio analysis, and
requirements management for large investment banking clients and has supported multiple sales and
business development initiatives. He has an MBA from the Indian Institute of Management, Lucknow and
a BE from Mumbai University. Mrugesh is a member of the Global Association of Risk Professionals and
has completed the FRM certification. He can be reached at Mrugesh.Kulkarni@cognizant.com.
Hrishit Pandit is a Senior Consultant in Cognizant Business Consulting’s Banking and Financial Services
practice. He has over 10 years of experience in banking, asset management, and wealth advisory and
has held various positions at Goldman Sachs, ICICI Bank, and HSBC Bank in the US, Middle East, South
Asia, and Africa. Hrishit has an MBA from Kelley School of Business, Indiana University, a PGDBA from
Narsee Monjee Institute, Mumbai, and a Bachelor of Engineering from MS University of Baroda, India.
He can be reached at Hrishit.Pandit@cognizant.com.
About Cognizant
Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process
outsourcing services, dedicated to helping the world’s leading companies build stronger businesses. Headquartered
in Teaneck, New Jersey (U.S.), Cognizant combines a passion for client satisfaction, technology innovation, deep
industry and business process expertise, and a global, collaborative workforce that embodies the future of work.
With over 50 delivery centers worldwide and approximately 166,400 employees as of September 30, 2013, Cognizant
is a member of the NASDAQ-100, the S&P 500, the Forbes Global 2000, and the Fortune 500 and is ranked among
the top performing and fastest growing companies in the world.
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