Global financial supply chain modeling

Global Financial Supply Chain Model
Parasuram Balasubramanian,
Founder & CEO, Theme Work Analytics, Bangalore
& Entrepreneur in Residence at Purdue University, USA
balasubp@gmail.com
A Research Initiative of
Oct 2008

Retail
Bank
Prime
Mortgage
Subprime
Mortgage
Personal
loans
Credit
Card
Auto
Loans
Insurance
Firm
Investment
Bank
CDO
Loan default
cover

•  The Melt down of financial institutions during 2008 in USA started as a
subprime crisis in the mortgage banks and spread to the investment
banks in no time. Its impact was felt in the retail banking sector as a
credit squeeze and in the international banking system as a crisis of
confidence in credit worthiness.
•  Both manufacturing and services industries have been adversely
affected in USA and in other countries with export dependency. It is felt
that the global economy would need two years to come out of this crisis.
•  Global markets and experts have been caught unaware. None of the
tools , techniques and models developed in the past has helped to
predict the occurrence of this crisis nor to project its magnitude. Models
dealing with international trade, money supply and balances, input
output evaluators etc have failed to issue any forewarning.
•  The Supply Chain Management [SCM] approach is an attractive
alternative to model this scenario for future use.
Background

SCM models deal with
•  Flows of goods, funds and information [can be extended to include other
factors]
•  Multidimensional Flows.
•  Interdependency of stakeholders.
•  Supply and demand side impacts. [can cascade them either way]
•  Flow constraints and delays.
•  Risk related issues as well.
They can be used to explain past behavior, to predict trends and/or to
determine the impact of control variables. Hence the Global Financial
crisis can be studied by modeling it using the SCM concepts.
Background

•  To Show the linkages in the financial chain across assets and risk
categories within a firm and its industry
•  To show the linkages between related industries ( Banks, Insurance
companies)
•  To show linkages to the industrial/manufacturing sector
•  To show the impact on general economy and public at large
•  To analyze the growth of firms” too big to fail”
•  To show the anomaly of large institutions becoming more risky and not
vice versa
•  To show the relationship of funds flow to Asset titles flow
•  To show the globalization impact
•  To reveal the causal mechanisms
•  To show the development of crisis of confidence
General Objectives

•  To study factors of vulnerability within an industry ( debt/equity
structure, product mix, legal binds)
•  To study regulatory mechanisms and policies as they differ from one
country to another( why has India survived the disaster)
•  To know the weakest links in the chain
•  To understand the consequences of a break in a link
•  To evolve a framework for analyzing the effectiveness of legislation
such as SOX
General Objectives

•  Traditional models explore flows of Goods and NF Services, Funds and
Information. We intend to explore the flow of Obligations/Commitments
explicitly.
•  Flows occur between a firm and its customers, between firms in an
industry, across industries in an economy ( or nation) and across
nations.
•  We intend to study these flows using a Four Layer Model,viz
Between countries
Between industries in a country
within firms in an industry
Between a firm and its customer segments
•  Customer segments represent varying risk classes
•  It is our belief that all other types of risks can be reduced or converted
to equivalent financial risks.
•  Financial risks are loss of earnings, erosion of capital, cash crunch and
inability or unwillingness to borrow/lend
The Four Layer Model

•  Funds flow at any given time occurs due to two reasons; viz (a) to pay
for goods and NF services or (b) to repay loans taken in an earlier
period.
•  Hence Financial Supply chains can be constructed recognizing the role
of exchange of goods and time value of money.
•  Flow of funds can be directly constrained or indirectly restricted
through constraints on flow of goods and NF services.
•  These Money flow constraints can arise out of legislation or market
forces.
•  The flow restrictions can result in reduced quantum of flow or delayed
flows.
•  Growth in money supply is centrally controlled.
•  Velocity of circulation can be significantly affected by developing the
money supply markets.
The notion of a Supply chain

Single Country Model
Supplier of
Goods and
NF Services
Buyer of
Goods and
NF Services
Money
Supplier
Flow of
Goods &
Services
Money
Flow
Current
payment
Future
payments
Federal
Reserve
Bank
Depositors Investors
Retail
Bank
Investment
BankCDS
Model 1.1
Model 1.2
Retail
Bank

Single Country Model : Notes
•  Three flow streams are identified ,viz (1) flow of Goods and Non
Financial Services (2) Money Flow and (3) Collaterals Flow
•  A firm ( or a citizen) can be both a Buyer and a Supplier at
different instances.
•  Retail Banks (including the Merchant Banks) are the Money
Suppliers in Model 1.1
•  Depositors are both citizens and institutions seeking primarily safe
custody of funds
•  Investors are both citizens and institutions seeking capital growth
•  CDS stands for Collateralized Debt Securities
•  Transactions between Retail Banks represent the Call Money
transactions needed to meet SLR and CRR
•  Expansion of Money Supply emanates from the Federal Reserve
Bank inputs to the system

Two Countries Model ( using same currency)
Country A Country BMoney Flow
(current)
Flow of Goods
& NF Services
Money Flow
(Future)
Flow of Titles to
Physical Assets
Model 2.1

Two Countries Model ( using same currency) : Notes
•  Trade imbalances can arise but are addressed by money flows in
required direction
•  Money flows can occur independent of Trade
•  One country funds can be used to hold titles to assets in other
country

Two Countries Model ( using different but hard currencies)
Country A Country BMoney Flow
(current)
Flow of Goods
& NF Services
Money Flow
(Future)
Flow of Titles to
Physical Assets
Model 2.2
Currency
Exchange
Market
Money Flow
(current)
Money Flow
(Future)

Flow linkages within a country
Country’s
Economy
Financial
Services
Money Flow
(current)
Flow of Goods
& NF Services
Flow of
(Product)
Liabilities
Model 2.3
Money Flow
(current)
Money Flow
(Future)
Maufacturing
and NF
Services
Money Flow
(current)
Money Flow
(Future)
Flow of
(Insurance)
Liabilities

Input Output Model
Country’
s
Economy
Financial
Services
Model 2.3
Maufacturing
and NF
Services
Other
Country’s
Economy

•  Trade imbalances can arise but are addressed by money flows in
required direction
•  Money flows can occur independent of Trade
•  One country funds can be used to hold titles to assets in other
country
•  Exchange rate setting mechanism can be either controlled or
uncontrolled
•  Relative strength of economies of the countries impacts on the
exchange rate
Two Countries Model ( using different but hard currencies): Notes

•  Model gets complicated in many ways
•  Country B ( with soft currency) may not be able to procure all the
Goods and NF Services it seeks/needs.
•  Government of Country B has a major role in controlling the
exchange rate. It further brings many import restrictions.
•  Sometimes through Development Grants, Aids and Loans obtained
through a Development Bank/Entity of Country A, Country B can get
access to hard currency to procure goods and NF Services from
Country A
Two Countries Model ( using different One hard and the other soft
currencies): Notes

•  Traditional models focus on flow of revenues and expenses as they occur
or are likely to occur in multiple time periods.
•  The net income ( or Profit after tax) figure is derived from the above. It
is a notional figure since it is derived based on assumptions about
depreciation and some anticipated revenues and liabilities.
•  It could differ vastly from the cash position of the company at any given
time. But should be reconciled based on sound accounting concepts.
•  Cash flow imbalances are of major concern to any enterprise. Even
profitable firms can find themselves in a cash crunch scenario.
•  It is likely that a profitable firm finds itself short of cash to pay dues in
a given week since the outflows can be irregular in time periods and vary
significantly in quantum from one period to another.
•  The worst scenario is when liabilities of extraordinary proportions fall
on the firm. This can be a product liability event in a manufacturing firm,
run on the deposits of a bank or need for enmass settlement of claims
for an insurer.
Modeling flows within a firm (1)

•  Firms typically resort to short term funding arrangements with banks to
tide over such difficulties.
•  The arrangement with banks can be either
1.  Within the prearranged cash credit/overdraft facility
2.  Specially negotiated for a given situation; usually at a higher cost or
additional collaterals
•  But the bank can also refuse to entertain the request when it perceives
a higher level of risk for getting back the principal.
•  The firm gets into a severe liquidity crunch then. It faces a severe crisis
of confidence in the lenders’ space.
•  Either the firm has to bring in additional equity at this stage or face the
consequnces of defaulting on its payments.
•  Major defaults or potential defaults will push the firm towards
bankcruptcy.
Modeling flows within a firm (2)

•  The consequences of a firm declaring bankruptcy can be devastating on
all its creditors.
•  Creditors ( be they are other firms or financial entities like a bank) may
be able to survive this calamity if they have a strong balance sheet with
sufficient reserves or assets with them.
•  But a creditor who is highly leveraged can find itself in dire straits as it
would face its own cash flow crunch at this time.
•  A masssive failure of one or more firms in an industry can first lead to a
scenario where banks refuse to lend to any of them to start with. Soon
the banks may refuse rto lend to any firm in that industry.
•  The worst scenario is when banks refuse to lend to each other. It leads
to a liquidity crunch scene across the entire financial sector.
•  Such a crunch can now impact on other sectors of the economy as well.
Credit flow to other industries is severely curtailed thus leading to a
capacity constraint across the economy as a whole.
•  With reduction in available capital comes reduced output and economic
contraction. Recession then is not far away.
Modeling flows within a financial network (1)

•  Models of financial firms in a network then has to necessarily
recognize the possibility of a crisis of confidence.
•  How does one model the crisis of confidence ?
•  Can empirical analysis of data help us to identify the road map leading to
it ?
•  If yes, what data needs to be gathered and from where ?
My approach :
The Black Swans here are the Liabilities. The extreme
points of Liabilities which are usually ignored ( because of
assumptions) in most cash flow analyses.
If flow of liabilities is recognized along with the flow of
expenses it can be modeled.

My approach :
• For example wherever insurance of any kind is involved
them total sum assured has to be the flow of liabilities.
• Modeling liabilites in all aspects has to be integral to the
funds flow modeling exercise.
• Sometimes quantification of liabilities can be a challenge
( example: product liabilities)
• Then the modeler has to come up with robust
methodologies ( stochastic if needed) to take care of this
challenge.

My approach :
• The second modeling challenge is to identify the points of
inflexion.
• It is where a firm moves from the position of being able
to get a loan or arrange for funds at a high cost to “can’t
get funds at any cost” scenario.
• For a set of lenders it is the point at which the crisis of
confidence develops. Lenders with short term lending
arrangements in place on an ongoing basis, refuse to lend
to each other.
• It is the point at which no lender is willing to lend to
another in a network, even though many have lendable
surplus funds.

Cash
Principal
Repayment
Dividend
paid
Interest
paid
DebtEquity
Vendor
Payments
Accounts
Receivable
Salary &
Benefits
Tax
Inventory
Sales
Cash Flow Model of a Manufacturing Firm
Investment

Cash
Principal
Repayment
Dividend
paid
Interest
paid
DebtEquity
Vendor
Payments
Principal
return
Salary &
Benefits Tax
Loan
Disbursal
Loan
repayment
Cash Flow Model of a Retail Bank (1)
Investment
Deposits &
Withdrawals
Interest
income

Cash
Investment
Bank
Inter Bank
Transactions
CDO
Loan
repayment
Insurance
Firm

Cash
Loan
Disbursal
Loan
repayment
Auto
Loans
Home
mortgage
Subprime
Loans
Credit
Cards
Personal
Loans
Business
Loans

WaMu
Prime
Mortgage
Subprime
Mortgage
Personal
loans
Credit
Card
loans
Equity
Loans
Insurance
Firms
Investment
Banks
Loan default
cover
Washingtom Mutual Bank
WaMu
shareholders
Other
Lenders
DepositorsDeposits
Guaran-
tors in
Europe
and AsiaMBS
Term
Loans
Equity

Cash
Principal
Repayment
Dividend
paid
Interest
paid
DebtEquity
Vendor
Payments
Premium
Income
Salary &
Benefits Tax
Claim
settlement
Claim
reimbursed
Cash Flow Model of an Insurance Firm (1)
Investment
Re/Co
insurance
Premium paid
Reserves

Cash Flow Model of an Insurance Firm (2)
Cash
Premium
Income
Claim
Settlement
Auto
Loans
Home
mortgage
Subprime
Loans
Credit
Cards
Personal
Loans
Business
Loans

Individual
& Families
Travel
Insurance
Health
insurance
Life
Insurance
Auto &
Motor
Vehicles
Insurance
AIG (1) Insurance and financial Services
Identity
Theft
Home &
Property
High
Networth
Financial
Services
Investment
Services
Banking
Annuity
Retirement
Services
Mutual
Funds
Loans &
Credits

Businesses
Profession
al
Liability
Internatio
nal
coverage
Accident
& Health
Executive
Liability
Commercial
auto
Insurance
AIG (2) Businesses
Workers
Compensa
tion
Property
Casuality
Financial
Services
Investment
Services
Annuity
Retirement
Services
Mutual
Funds
Loans &
Credits
Life
Insurance
Speciality

Investment
bank
Research
&
Advisory
Brokerage
Services
Portfolio
management
Client
focused
Investment Bank
M& A
services
Capital
market
Services
Own
account
Derivative
trades
Forex &
Commodity
tradesCapital
market
trades
Risk
management
Services
Forex &
commodity

Lehman
BrothersClient
focused
Lehman Brothers
Capital
market
Services
Own
account
Derivative
trades
Forex &
Commodity
trades
Capital
market
trades
Mortgage
Origination
Investment
banking
Investment
Management
Securit
ies
Fixed
Income
Real
Estate
•  Treasury Bonds
•  Interest rate
and credit
products
•  Currencies
•  Commodities
•  Derivatives
•  Brokerage
Services
•  Equities
•  Derivatives
•  Brokerage
Services
•  Research &
Advisory
•  Investmen
t Mgt
(HNI)
•  Capital
market
Execution
s
•  Raising Global
Finance
(Private
Placement,
Underwriting)
•  Advisory
Services ( M &
A, Divestment )

Cash Flow Model of an Investment Bank (1)
Assets link to cash flow
Cash
Cash Segregated
under Regulations
Securities
(1.1)
Securities
Segregated under
Regulations
Financial
Instruments
(1.2)
Purchase of
Fixed Assets
Interest
Receivable
Business
Receivables
(1.3)
Purchase of
Other Assets
Good
Will

Cash Flow Model of an Investment Bank (1.1,1.2 & 1.3)
Assets link to cash flow
Securities(
1.1)
Financial
Instruments
(1.2)
Business
Receivables
(1.3)
Securities
Borrowed
Securities
received as
collateral
Securities
purchased
under resale
agreements
Financial
Instruments
Owned
Financial
Instruments
pledged to
counterparties
Receivables from
noncustomers
Receivables from
customers
Receivables from
brokers , dealers &
clearing orgs.

Cash Flow Model of an Investment Bank (2)
Liabilities link to cash flow
Cash
Securities
(2.1)
Borrowings
Financial
Instruments
(2.2)
Subordinated
Liabilities
Interest
Payable
Business
Payables
(2.3)
Other Liabilities &
accrued expenses
Loan
(principal)
repayment
Equity
Dividend
paid
Salary &
Benefits
Tax

Cash Flow Model of an Investment Bank (2.1, 2.2 & 2.3)
Liabilities link to cash flow
Securities(
2.1)
Financial
Instruments
(2.2)
Business
Payables
(2.3)
Securities
Sold under
Repurchase
Agreements
Securities
Lent
Obligation to
return
Securities
received as
collaterals
Financial
Instruments
Sold , not yet
purchased
Payables to
brokers,
dealers and
clearing orgs.
Payables to
customers

Cascading Failures
Mortgage
Bank
Investment
Bank
Debt
Insurer
Deposit
Insurer
NFServices
firm
Manufact
Firm
Country
Iceland
GMC
AIG
Lehman Brothers
Washington Mutual

Flows between financial institutions
Investment
Bank
Mortgage
Bank
MBS ?
Investment
Bank
Money

Historic Events causing major impacts
The subprime financial crisis of 2007-2008 and its impact on the US, global financial services and economies.
9/11 attacks and their impact on the US Airline industry
The external debt crisis of Greece in 2009-2010
The 1973 oil crisis and its impact on the global auto industry.
The monetary crisis in Jamaica 1995 and its impact on the tourism industry

Business failures classification
Level 0 : Short term Cash crunch of a profitable firm
Level 1 : Zero Profit and hence no return on investment
to shareholders
Level 2 : Loss to the extent of depreciation charges not
covered
Level 3 : Loss to the extent of defaulting on ( long term) debt
repayments
Level 4 : Insufficient assets to cover all liabilities;
Bankruptcy
We assume that a profitable firm would be able to arrange for
short term loans to tide over

We assume that a profitable firm would be able to arrange for short term loans to tide over the cash crunch
scenario. The borrowing rate will be as dictated by the market place and the credit rating of the borrowing firm.
Any volatility seen in its income or perceived increase in liabilities
Will result in its credit rating being lowered. The consequence of which would be to increase the cost of borrowing
to the firm.
A firm with zero profit is perceived to be at a higher level of challenges. It is able to meet all its obligations
except giving a fair return on investment to its shareholders. The disgruntled shareholders will work with the
management for a while before pulling the plug.
The firm faces complex issues when it has not earned enough to cover the depreciation charges. It means that the
firm would not be in a position to replace aging or obsolete machinery. Hence its losses are bound to increase
over the years due to higher maintenance charges for capital equipment. In general it is a clear indication of an
unviable business model. If the situation continues, the firm is likely to go out of business soon.
The issues are severely compounded when the unprofitable firm can not meet its loan repayment obligations. It
has to either find lenders who are likely to charge more , sell some assets or raise more equity. A distress sale of
assets always fetches a lower price. Even equity investors would bargain hard.
When the liabilites exceed the firm’s assets, it results in complete loss of confidence of all lenders and
investors. The firm can not raise additional capital and it would declare bankruptcy.

Level 0
Level 4
Level 3
Level 2
Level 1
A firm can jump levels
quickly if its long term
assets loose value or
liabilities gain value
in short time periods.
A networth positive
firm can survive many
years of unprofitable
scenario.

There are inherent differences between Manufacturing / Non financial Services firms[ MSF] and Financial
Services firms[ FSF]. The former usually have a lower Debt to Equity ratio compared to the latter. Hence the latter
are known as highly leveraged firms. It is also likely that the former are highly capital intensive.
MSF have high depreciation charges compared to loan servicing costs and it is vice versa for the FSF.
Consequently MSFs , if they are adequately capitalized can survive for a long period.
FSFSs on the other hand will jump from State 1 to State 3 quickly.
FSFs have much higher level of volatility in their earnings, value of assets and liabilities.
MSFs are in a Supply Chain scenario with closer ties between vendors while the FSFs are in a Supply Network
Scenario with arms length relationship between many of them.

The weakest link in the Network

v  Each circle represents a financial entity and each
link connects two entities.
v  The strength of relationship between two entities
can be represented by the strength of the link.
v  The Financial Supply Chain is not a chain at all but
it is a Network of interconnected entities
v  In a chain one weak link, when it breaks, can
make the whole chain ineffective
v  In a network that won’t be the case. The network
can survive the break up of a link here or there.

v  It is however possible that when a link breaks and
its impact on a major object is intense, number of
other entities can fail.
v  Loss of profit and cash flow crunches that lead to
higher borrowing rates or even one entity denied
credit by others are situations similar to the above.
v  The most critical scenario is when many of the
linkages are paralyzed and they are frozen. Then
there is no flow between the set of entities.
v  This is akin to the crisis of confidence that
develops amongst a set of banks.

v  Even though many amongst them have investible
funds, no transaction takes place in the entire sub
system due to lack of confidence.
v  The entities need not be confined to one country.
Then the impact can be multinational.
v  Non financial entities are also affected by the funds
freeze as they depend on borrowed funds for day to
day working capital requirements as well as for
medium and long term capacity expansion.
v  They may also end up handicapped from growing
further.

v  If the financial and non financial entities are
global then the impact spreads to many nations
quickly.
v  National economies are crippled and run into
recession.
v  Hence the need to ensure that the financial supply
network is well oiled and keeps running
continuously.

MBS, CMO.CDO,CDS,SIV etal
Mortgages
Synthetic
CDO
SIV
CDO
(Cash
Flow
based)
MBO,
MBS
Complex financial
products have been
constructed out of
simple mortgages and
other financial assets
such as Home Equity
and Business
Receivables
MBO: Mortgage backed Obligation
MBS : Mortgage backed Securities
CMO : Collateralized Mortgage Obligation
CDO : Collateralized Debt Obligation
CDS : Credit Default Swaps
SIV : Structured Investment Vehicle
CDS
CMO

Mortgage
Year 0 1 2 5 10 15 20 25 30
Each mortgage
generates multi
year payments to
the bank from the
borrower.
Each payment has
an Interest
component.
Each payment has
a Principal
component.
Interest component is
larger than the
Principal component
in earlier years and
vice versa.

Mortgage
Year 0 1 2 5 10 15 20 25 30
Prepayment Risk
Mortgage getting closed
earlier than the planned
period either due to
refinancing of the loan or
its foreclosure. No loss in
Principal.
Each payment has
an Interest
component.
Each payment has
a Principal
component.
Default Risk
Inability to recover the
dues pertaining to
Interest or Principal or
both.

Collection
of
mortgages
0-5 Years
5-10 Years
10-15 Years
15-25 Years
25-30 Years
Interest
Payments
Interest
PaymentsInterest
Payments
Interest
Payments
Interest
Payments
Principal
Payments
Principal
Payments
Principal
Payments
Principal
Payments
Principal
Payments
Group 1
Mortgages can be
grouped by way of
similar maturity period
and interest rates etc
Group 3Group 2 Group 5Group 4

Collection of
mortgages
Group X
Interest
Payments
Principal
repayment
Tranch 1
Year 1
Tranch 2
Tranch 3
Equity
Year 3Year 2 Year N
Interest
Payments
Interest
Payments
Dividend
Mortgage
Receipts
Principal
repayment
Principal
repayment
Capitall
repayment
Tranches can be constructed in many ways. The
waterfall method stipulates a hierarchy of
payments. Interest obligations of Tranch 2 are paid
only after Tranch 1 is fully paid etc. Tranches need
not be equal in size. They could also be
constructed by segmenting the mortgages into
prime and subprime further. Tranches carry
different levels of risk and commensurate returns.
Reserves

Collection of
mortgages
Group X
Interest
Payments
Principal
repayment
Tranch 1
Year 1
Tranch 2
Tranch 3
Equity
Year 3Year 2 Year N
Interest
Payments
Interest
Payments
Dividend
Mortgage
Receipts
Principal
repayment
Principal
repayment
Capitall
repayment
Reserves
Even subprime mortgages can be tranched.
Some tranches will carry lower risk than
the underlying assets while others will
carry higher risk. Usually the highest risk
tranches are retained as equity.

MBS :: A Bond created by securitizing a pool of mortgages
CMO :: A tranched MBS
CDO :: ( Cash Flow Based) :: A tranched Asset Backed Security
where the asset can be an
Home Equity Loan or Credit Card
Dues etc.
CDO :: ( Synthetic) :: No Asset backing exists but is based on a
pool of Credit Default Swap (CDS)
CDS :: Credit Default Swap :: Protection against a loss or
default, like insurance

CMO is tranched based on the returns ( interest and principal
repayment) from underlying mortgage assets.CMO can be a
protection against the Prepayment risk inherent in mortgages.
(Superior tranches get this benefit at the cost of inferior tranches)
CDO ( Cash flow based) is tranched on the pool of loans or other
assets such as credit card receivables. Superior tranches offer
protection against the credit risk while the inferior tranches
exacerbate the risk.
CDO (synthetic) is created from a pool of securities ( like Credit
Default Swaps) that are contingent upon the occurrence of a
default event. The are a form of protection against the default risk.

The Macro details ( new slide Oct 21 2010)
v  The flows within a firm are modeled using cash flow simulation models that look
at both the demand and supply sides of the firm. The intent is to predict when a
cash crunch will occur. The required level of details, however, would be available
only with the firm. SEC filings may contain only summary data, insufficient to
develop these models.
v  Modeling the flows within an industry ( particularly financial services) is the
mission critical task. It can help to detect the development of Loss of Confidence
among a set of players and assess its strength. I am yet to figure out how this
model can be developed.
v  Flows between industries are best modeled using the Leontiff Input Output
models. Add on models on top of this would help to determine the impact of crisis
in the Financial Services industry on to other sectors of the economy.
v  Country to country flows can be modeled using macro economic concepts.
Similar models exist from IMF and other sources. They may need to be further
developed to serve our intended purpose.
v  The final task consists of linking the four layers by developing appropriate links.

The Macro details ( new slide Oct 21 2010)
v  Most loan facilitates are granted not only after assessing the repayment capability of the borrower
but also when the borrower is in a position to provide a collateral of comparable value. Hence any
cash flow model of a firm has to recognize the collateral aspects comprehensively.
v  Once collaterals are provided they are to be constantly monitored for value preservation. Any time
their value falls below the liability under concern the borrower is compelled to make good the loss by
providing additional collaterals. In the extreme case when the borrower is unable to do so, the
lender can recall the loan ahead of schedule thus pushing the borrower into a cash crunch scenario.
v  When market conditions are such that the revenue streams that affect the borrower are positively
correlated with the collateral values, the borrower faces a double whammy. The firm has to struggle
to meet its loan repayment obligations as well as to find additional collaterals.

v  The borrower firm has to raise additional capital or sell of other assets to come out of this problem.
Else it may default on the loan and be pushed into bankruptcy.
v  If the failure of a firm is an isolated incident without cascading to other firms, then there would not
be a financial crisis spreading. But there are many instances where the failure can have a cascading
impact on many related firms. An indicator of this precarious condition is the freezing of credit flows
among the firms that borrow and settle almost on a daily basis within the network.
v  This is the event termed as Loss of Confidence and it has to be modeled.

The modeling challenges ( new slide Oct 26 2010)
v  There is currently no reliable and robust model for valuation of assets floating as securities of various
forms ( in particular the derivatives) and method to track the variation in their value on an ongoing
basis. A new class of models that recognize the contingent liability ( however low the probability is)
is needed.
v  Models are needed to determine the point of inflexion regarding loss of confidence with an entity.
v  Additional models are needed to detect the occurrence of loss of confidence across many entities in a
network and the conditions that can trigger such events. This event is called a network freeze.
v  Models are needed to figure out when and how related networks would be affected when a network
freeze occurs.

•  Differ significantly from the (physical )product supply chains
•  Most sourcing relationships are at arms length ; driven by best
opportunity of the day. Long term contracts that define quantity and
price ( interest rate) are rare.
•  Even though what is procured is an undistinguishable item called money,
the sources are differentiated based on long term ( equity, Debt),
medium term( working capital) and short term funding (cash flow).There
is a segmentation.
•  Supply chains are truly global and more a network than a chain.
•  Expertise to define and offer a ( financial) product are concentrated in
certain urban locations. More sophisticated the product is, limited are
the supply centers in the world. However the actual risk or liability can
be carried by any entity located globally.
•  Product quality ( as defined by its value at a moment) can change
substantially due to externalities.
Financial Supply Chain Characteristics

•  Have the added complexity of collaterals whose value can also change
moment to moment.
•  In LT funding scenario the risks assumed by the suppliers are enormous.
•  There is a severe cascading effect that can impact on unrelated entities
too.
•  Valuation is many a time a complex task. It is based on the ratings
obtained from third party agencies. Value fluctuates widely from time to
time.
•  Suppliers often tend to aggregate and share the risk. ( unlike the
product supply chains where suppliers do not wish to relate to
competitors)
Financial Supply Chain Characteristics

•  Asset Valuation Models for Bonds, Stocks, Derivatives etc
•  CAPM ( Capital Asset Pricing Model) determines the price of a stock in
relation to the market based on its risk characteristics.
•  Black Scholes Model is for valuation of derivatives
•  Gaussian Copula Model for complex derivatives such as CDOs
•  Stochastic models for predicting the value of a stock, interest and
exchange rates etc
•  Cash flow models( usually simulation based) are used for determining
cash surpluses and shortfalls within a firm
•  Insufficient models for predicting the failure of a firm or loss of
confidence in its ability to meet all its debt obligations
•  No model for determining the freezing point of a financial network
where members are unwilling to lend to one another
Models in Financial Supply Chain

•  Lack of models to predict the impact of issues in one sector ( such as
mortgage financial sector) on another ( say on housing or auto or
consumer goods).
•  Inter country models to understand flow of funds or flow of goods
•  Interplay between funds flow and goods flow and asset ownership
between countries
Models in Financial Supply Chain

Global financial supply chain modeling

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Global financial supply chain modeling