ResearchPDF Available

Abstract

The Paper Talks about the chief cause of the subprime mortgage crisis is the United States housing bubble burst after reaching its peak in the year 2006.
Dipak Kumar Singh
Sampath Kora
School of Management and Entrepreneurship
Gautam Budh Nagar, U.P., 201314
Research Report
HSBC Lending Decisions
and Sub Prime Crisis
1
HSBC Lending Decisions and Sub Prime Crisis
Contents
Problem .................................................................................................................... 2
Objective ................................................................................................................... 3
Introduction .............................................................................................................. 3
Risk Transfer Strategy............................................................................................4
Architecture of the New System ............................................................................. 5
Working of New System .......................................................................................... 6
Structure of Databases ............................................................................................ 7
Dashboard ................................................................................................................. 9
Pointer 1 .................................................................................................................. 10
Pointer 2 .................................................................................................................. 12
Pointer 3..................................................................................................................13
Pointer 4..................................................................................................................14
References...............................................................................................................16
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HSBC Lending Decisions and Sub Prime Crisis
Problem:
Let us look what us subprime loan, subprime does not mean “lower than prime.”.
Subprime lenders charge rates that are higher than prime, the rate offered by the
bank to its most creditworthy customers sometimes the subprime rates are much
higher. Subprime borrowers are generally people with poor credit record who may
have a recently defaulted.
The chief cause of the subprime mortgage crisis is the United States housing
bubble burst after reaching its peak in the year 2006. The rate of defaults on
adjustable-rate mortgages increased many fold leading to crises.
HSBC also invested heavily in the subprime loan and the Real estate prices did not
rise, as was expected, and the adjustable-rate mortgages were reset on a higher
level. The prices of houses fell so drastically that, at one point of time, they were
lower than the loan amount itself. This forced people to opt for foreclosures and
that is when the huge default resulted leading to bankruptcy of many financial
institute.
When HSBC started writing off large chunks of its subprime mortgage loans many
attributed the fault of bad loans to HSBC’s faulty IT support systems as they failed
to identify the defaulter borrower. HSBC used to use FICO score to check the
credit score of the borrowers and did not have tool of its own to check the same,
HSBC overlooked the factor that FICO score doesn’t take risk of loan being
second-lien or stated income loan. Neglecting these risk factors, and falling of
house prices lead to subprime crises. Most of the borrowers failed to repay the
loans when interest rates are suddenly bloated by the end of 2006. The system did
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not had any tools for managing customer relationships and improving risk
management decisions. It failed in assessing each applicant, verify their credit
score and providing them with a customized loan that would suit borrowers need
and minimize the business risk.
Objectives:
Develop a system that will be robust enough to check the borrower's credit score,
suggest customized the loan as per the user requirement as per borrower's paying
capacity and help is minimizing the defaulter for the loan.
Introduction:
By the start of 2007, HSBC started to realize that most of its subprime mortgage
loan borrowers who are mostly stated and second lien loan seekers are defaulting.
The underlying factors which led to this were
1. People were unable repay the loan due to increased interest rates
2. People are not willing to repay the loans due to the mortgaged house price fall.
3. The price of the house felled even below the loan amount
So there is need to develop new system which will take care of all this in the future
and will be robust.
The new integrated system is designed keeping in mind that the market is volatile
and the market trends changes rather too quickly, we have taken the inflation and
deflation in consideration as it determines the interest rate. We have also make the
system robust to make adjustment based on the current information. The system alos
has database which takes the current input from the user and based on the input,
generates the output, this is the risk score, credit score, interest rate to be charged
and the repayment duration.
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The dashboard will display all these output in the single screen which will make the
decision making easier for the manager.
Risk-Transfer Strategy:
As for what sort of alternative hedging or risk-transfer strategy could HSBC have
used in the situation under consideration?
There are several ways to provide layers of protection or risk transfer for the assets
the company can choose from , these are mainly as listed below:
• Certificates of insurance.
• Additional insured status.
• Indemnification provisions in contracts and leases.
In my opinion HBSC should have used the Certificate of insurance to transfer the
risk of mortgage .
This could have transfer the risk to the insurance company and in the case of
default , HSBC could have claimed the money from the insurance company.
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Architecture of the New System:
The designed system will be a consisting of multiple Databases and DSSs.
The databases which has the previous credit score are the FICO score database,
bank’s interest rate database, expected inflation database and the mortgaged house
prices databases which also have information about house price inflation and
deflation may have in future as per the region and the location of house location.
These information will be manually entered in the databases, for example like if
Second-Lien
Loans
FICO Score
application
Stated Income
Loans
User Sub Prime Loan
Score Generated
Third party
connect for Data
Third party
connect for Data
Central DSS System
with What-IF analysis
Bank’s Interest
Rate Charter
DSS System - Risk
Factor Generated
Bank Loan
to be repaid
Final Interest with User Profile
Inflation
If score > 10
No
Loan Rejected
Yes
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the loan is second-lien or not, if the loan is a stated income loan or not, loan
amount to be repaid and loan scheduling period (duration of repayment of loan).
Along with the 8 databases there will be two DSS’s system. The first DSS will be
used to find the risk of loan default due to chance of house prices falling or going
below the loan amount. The Second DSS system will be used for deciding the
interest rates based to be charged on the HSBC score generated. The application
will also have integrated dashboard system which will display all the required
information for its managers to take decisions.
Working of the new system:
The complete system can be classified into two parts. The first part is all about
generating the user loan score, checking the previous credit record of the borrower,
housing price, market trend, inflation or deflation in the near future and the second
part will be used to decide whether bank will give the loan or not and if yes at what
lending rate based on credit score generated and loan scheduling. So now coming
to the first part of the system will start functioning when an applicant approaches
the bank for loan, once the application is received by the bank, bank will start
collecting the information like FICO score for seeing previous credit record, if the
purchase of house is by second-lien loan or partly funded by loan seeker, if the
loan is a stated income loan or not, amount of loan required, locality and price of
the house.
Based on the house and the location details, the price of the house will be predicted
for mortgaging house in the next five years, this information taken from the third
party database. Comparing the loan amount left to be repaid, expected inflation
(taken for checking the risk involved with rising interest rates), the current price of
house and the future price of house, the risk value or the score will be generated by
the DSS system. This generated risk value or the score will be added to the FICO
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score along with risk value or the score of loan being stated income and second-
lien. This will give us the final loan risk score of the user , we can call these credit
score.
The second part of the integrated system will act as customer support system that
will take the generated loan risk score and interest rate charter and will help the
bank front desk personal to suggest the loan scheduling period to the customer, the
front desk personal can also customized the loan to fit the customer need. Once the
loan scheduling period is finalized then a central DSS system will take inputs of
loan risk score, loan scheduling period and interest rates from charter and will
finally generate the interest rate at which bank will issue the loan to the borrower.
This way the customer will get the loan customized for him and bank will
minimize the default risk.
If the customer makes regular payment of every installments (EMIs) user risk
score will decrease and hence the customer interest rate will vary according to the
new risk score generated by the integrated system. Usually the proper payments of
installments should reduce the interest rate for borrower and will benefit the
borrower. But in conditions like high inflation risk score will increase despite
user’s timely repayment of installments and thus it will lead to increase interest
rates.
Structure of the Databases:
The database contains 4 table, these tables are:
1. FICO Score Table
2. Expected Inflation Table
3. Loan Amount Table
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4. Interest Rate Table:
These table has fields whose value have to manually entered that are needed as
input , the DSS will analyze these input and give the output.
FICO Score Table:
FICO Score
SSN ID (PK)
FICO Score
Second-Lien
Loans
Stated Income
Bank AC No (FK)
Expected Inflation Table:
Expected Inflation
Expected Inflation
Expected
House Price
Bank AC No (PK)
Driving License(FK)
Loan Amount Table:
Loan Amount
Bank Loan Due
Risk Score
Driving License (PK)
Loan ID (FK)
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Interest Rate Table:
Interest Rate
Loan ID (PK)
Interest Rate
Risk Score
SSN ID (FK)
Repayment
Duration
The database contains all the data which are required by the new integrated system
to calculate the credit score of the borrower to determine the rate of interest and the
duration of the repayment.
Dashboard Design/Layout:
SSN ID FICO Score Second Lien
Loan
Stated
Income Risk Score Interest Rate
Last Instalemt
Paid
Instalment
Due
Bank Loan
Due
10
Sample Dashboard:
The dashboard will display the output that will generated by the DDS system, the
manager can use the dashboard to deter the creditability of the borrower, it will
also show the stated loan, default (if any), risk score etc.
The dashboard will be very helpful as it will display all the information needed by
the manager to make correct decision.
Pointer 1
When you build the case resolution and prepare your final report, focus on the
following points:
1. What problem did HSBC face in this case?
NC7834667431 6.3 Second-Lien Loan
Not a Stated
Income Loan 12.6%
7.4
14th Feburary 14th March 1.1 Lakh $
11
Let us look what us subprime loan, subprime does not mean “lower than prime.”.
Subprime lenders charge rates that are higher than prime, the rate offered by the
bank to its most creditworthy customers sometimes the subprime rates are much
higher. Subprime borrowers are generally people with poor credit record who may
have a recently defaulted.
The chief cause of the subprime mortgage crisis is the United States housing
bubble burst after reaching its peak in the year 2006. The rate of defaults on
adjustable-rate mortgages increased many fold leading to crises.
HSBC also invested heavily in the subprime loan and the Real estate prices did
nott rise, as was expected, and the adjustable-rate mortgages were reset on a higher
level. The prices of houses fell so drastically that, at one point of time, they were
lower than the loan amount itself. This forced people to opt for foreclosures and
that is when the huge default resulted leading to bankruptcy of many financial
institute.
2. What management, technology, and organizational factors were responsible for
the problem?
The banks used to provide huge credit to the government of American, HSBC was
also one of these bank. While providing the credit, the bank took huge loan
recovery burdens upon themselves and did not possess the financial cushion
required to take the impact of loan defaults and mortgage-backed security losses.
This resulted in an economic slowdown as the banks lost their potential to lend
more. So the management failed to foresee this on their part. HSBC used to use
FICO score which was not so reliable it was failure of the technology also to some
extent.
12
Technology: Using a third party FICO score which was not fool proof technology
which doesn’t take into consideration the probability of loan being a falsely stated
loan or the risk being involved due to the loan being second-lien loan or the impact
interest rate increase.
Organizational Factors: Hike and promotions that are linked on the basis of
performance made the manager to ignore or liberalize rules for granting loans.
3. Did HSBC management correctly identify the problem?
Yes HSBC management did identify the problem when they in early February
2007, HSBC announced a much higher percentage of its subprime loans defaulted
than it had anticipated. It would have to make provisions for $10.6 billion in bad
debt stemming from loan delinquencies in 2006
4. Whose problem was it?
The Problem was if Management who trusted fully trusted technology and bonus
and promotion made manager to ignore the credit rating scores to gain greater
returns on interest.
5. Identify some externalities in the problem.
One of the Major externality in this case was the American Federal Bank which
increased the interest rates without thinking about consequences that this will have
in long run. Others were FICO score and second lien or stated loan.
Pointer 2
1. HSBC had sophisticated IS and analytical tools for predicting the risk presented
by subprime mortgage applicants. Why did HSBC still run into trouble?
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HSBC has sophisticated IS and analytical tools, but they did not consider some of
the risk factors like risk of second-lien and stated income loans. The IS is as
sophisticated as the person using it.
2. If HSBC had a solution to the problem all along, why was the right solution not
used before the crisis?
The HSBC hoped to keep getting the revenue from the interest they generated
from the subprime loan, hopping that the borrowers will make payment of their
due loan. If the borrowers fell behind or defaulted, HSBC suffered the losses. In its
quest for higher revenue, HSBC began buying more subprime loans from other
sources. In 2005 and 2006,with the housing boom in its final stages, HSBC bought
billions of dollars of subprime loans from as many as 250 wholesale mortgage
companies, which had acquired the loans from independent brokers and banks.
HSBC found the high interest rates of these loans to be very alluring. Many of
these loans were second-lien, or piggyback loans, which allow home owners who
were unable to come up with a down payment for a house to qualify for a mortgage
by borrowing the down payment amount, so they actually borrow the entire
purchase price of a home.
3. What solutions is HSBC relying on to deal with its problem going forward? Will
these solutions be sufficient to turn the subprime mortgage business around?
HSBC stated it had a process for forecasting how many of the subprime loans it
had purchased from wholesalers were likely to default. First, the bank would tell
the wholesaler what types of loans it was interested in, based on the income and
credit scores of the borrowers. Once the wholesaler offered a pool of mortgages,
HSBC analysts evaluated the lot to determine whether it met HSBC standards.
14
HSBC made changes in both personnel as well as the policy, doubled the number
of customer representatives, adopted the business analytics software from
Experian-Scorex to support the decision making of its credit application processing
staff.
4. Are there additional factors for which HSBC has not accounted? If so, what are
they?
HSBC system failed to take into account the risks involved with loans being the
second-lien or stated income. HSBC also ignored the borrower’s capacity to repay
the loan in case there is some changes in Interest rates.
Pointer 3
1. What are the possible consequences of HSBC's changing its approach to
subprime lending?
The changes which HBSC bring in will allow borrowers to have loan customizes to
their needs. The loan will be fitted for the borrower by using decision- making, risk
management, and the business analytics tool HSBC implemented. This will make
the borrowing such safer.
2. How might these changes affect the business?
As the effects of various changes implemented by the HSBC aftermath subprime
crises will make taking the loan much harder which will affect the customer.
Harder loan process might affect the financial of the customer who are in need of
finances.
3. How might these changes affect the US economy?
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As the loan process is made harder, this will also increase the interest rate of the
bank , since it will be now harder to quality for the loan and will lower the housing
market.
4. Points to ponder: If a similar situation happened in India today, how might it
affect India's economy? (This is a very challenging question and requires a lot of
very deep thought - take up the challenge)
I don't see this situation happening in India as the RBI keeps strict check on the
market speculation and the rule for getting loan is very strict. Through check and
verification is done in order to give loan. India is developing economy and the
demand of houses is still high as compared to the supply. Even in the case if this
happens in India RBI will able to Bail the came from its cash reserve.
Pointer 4
1. HSBC made a decision to pursue subprime as a segment of its business. What
sort of decision was this? Structured, unstructured, or semi-structured? Justify your
view.
This was Semi-structured decision as not clear cut solution was there to predict the
fall in housing price that led to the subprime crises.
2. Formulate and establish your opinion about where in the decision-making
process HSBC went wrong. Build a strong case in support of your claim.
The Decision-making process did go wrong at the strategy planning of higher level
management , the management failed to foresee the consequences of falling house
price if the interest rate rises and the FICO score is not reliable even then HSBC
went ahead to buy more mortgage from the market lured by the high interest rate.
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3. Apply the decision quality concepts of accuracy and comprehensiveness that
we've studied in the class to this case.
• Accuracy: Is the value added by the system processes that assure error-free
transfer of data and information.
The integrated system that we have designed will be error and there will be no loss
that of data, in case there is loss of data same will retransmitted again fully.
Comprehensiveness: Is the value added by the completeness of coverage of a
particular subject or discipline (e.g. chemistry) or of a particular form of
information (e.g. patents).
We have taken the previous credit score of the borrower, any inflation or deflation
in the market, next 5 year price of the house as well as FICO score to generate
fully comprehensive credit score and based on these score the interest rate and
amount will be decided for the loan.
References:
http://banking.about.com/od/mortgages/a/mortgagecrisis.htm
http://www.investopedia.com/terms/s/subprime-meltdown.asp
http://www.publicintegrity.org/2009/05/06/5449/roots-financial-crisis-who-blame
www.Investopedia.com
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