Financial Fragility
Financial Stability
Property Market
Bank lending
* Stress testing 30% for in property prices
Executive summary
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1997 crisis was interplay between the property market, bank
lending and the economy.
Assess the degree of financial fragility associated with bank
lending and the property market
Attention to impacts of interest rate increase and banks’ mortgage
portfolios.
Questions
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How long will bank’s mortgage portfolios be able to withstand the
upturn in the interest rate cycle without having to ask borrowers
for additional payment contributions?
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What would be the impact on banks’ capital positions if there were
a collapse in property prices?
(Section2)
Thailand’s property market:
navigating through boom and bust cycles
First cycle
Since 1970, Government housing market and Established the
National Housing Authority
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(decree provided credibility to both developers and consumers in the purchase and sale of
housing)
1973, boom – Oil shock
•
Caused prices of building material up
•
Accompanied rise in labor cost and slowing economy
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Demand for housing fell
----------------
caused BUST
2nd Boom
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1976- 80 boom
Financial institutions provided low interest rates to homebuyer
Townhouses began to emerge in Bangkok
Boom ended by the oil shock
BOT limited only 18% credit growth
Many projects became incomplete and new projects were shelved
----------------------- caused BUST
3rd Boom
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1986, transformation from an agricultural-based economy to an
industrial-based economy
Too many FDI (foreign direct investment)
Housing project increased prices as the no. of housing unit soared
Housing and townhouses boom, rising prices and strong demand
------ better speculation
Real estate market slowed down in 1990 due to the Gulf War
---------------- caused BUST
Private residential and nonresidential construction, 1980-2002
and Permitted construction area, 1984-2003
4th Boom
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1993, Board of investment (BOI) offered 5 years income tax
exemption to developers who developed low income housing
units.
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1995, found that half of 300,000 units in BMR which were
purchased were unoccupied condominium.
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1997, while the growth of the Thai economy had initially
enhanced, the downfall of the housing market impacted other
sectors in economy.
Developers didn’t lower prices due to the rising construction
prices. Price of property dropped
Property crisis ----------- Bank crisis*
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The crisis
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BIBF (Bangkok International Banking Facilities)
Foreign loan come easy with lower rate
Loan to developer at lower rate
Speculation on price
Loan reached 800 billion baht in 1996
28% of GDP, but no productivity
Leading crisis
Outstanding property loans percent of GDP
and NPLs of real estate loans
The new beginning
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2002, Houses and townhouses recovered
GHB, provided long term fixed rate mortgage
Reduction of special business tax from 3.3% to 0.11%
Transferred fees from 2% to 0.1%
Economic recovery and low interest rate, raised consumer’s ability
to purchase housing by increase ability to service debt.
Families have also increased demand for living.
Result, demand for mortgage loans had ballooned.
CONT’
Extended mortgages to reduce excess liquidity.
 Mortgage is less risky and firm is collateral.
 Small to medium sized developers focused on one development at
a time before new project.
* The renewed confidence in the market brings questions whether the
sector may be exposed another crisis again?
- Economic cycle and the growth depends on demand
•
Driving force
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- Low interest rate
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- Bank competition
Any risk overinvestment---YES!, DEPEND ON BANK LENDING
BEHAVIOR
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(Section 3)
The interconnection between the property secter
and commercial bank
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Pre versus Post financing (supply side/ demand side)
Pre financing - for property developer as source of fund.
Post financing - for purchasers of housing as source of fund.
Before crisis
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Bank and financiers are major players.
After crisis
Bank as major player, most of financial companies closed down.
•
So, developer go to capital market SET, raise fund from the
market rather than rely on the bank.
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After the collapse of the fixed exchange rate regime, banks
learned a painful lesson. (exchange rate from 25 to 57 baht)
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Many foreign debentures were default or not rolled over.
Index and market capitalization of the
property sector
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no more BIBF , BIBF paid off their loan and avoid borrowing from foreign
sources.
Breakdown of post financing, 1991-2003
CB-Commercial Bank
GHB-ธ.อาคารสงเคราะห์
GSB- ธ.ออมสิ น
FC- financial company
Bank played a major role
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From the structures of pre and post financing, bank are the most
important sources of funds of the property sector.
Commercial bank lending is important to both supply and demand
of the property market.
Loose credit policy and low interest rate generated real demand,
but also lead to speculative demand and excessive supply.
Watch closely for speculative bubble!
Section4 Impact of monetary policy on property
prices (SVAR)
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Monetary policy movement
Changes in repurchase rate
Affect property price by altering bank lending and macro
economy
An increase in policy rate
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Cause in short term interest rate to rise.
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In turn increase the cost of loans.
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Reduce demand for credit by both developer and consumers.
*Consequently
 Decreases house buying, planned fixed investment and two
component of real output.
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In turn contributes to fall in property price.
Structural identification estimate 14 day purchase rate
(RP14)
Each variations:
r is the 14-day RP rate
i is the nominal MLR
l is mortgage lending by commercial banks
y is the log of GDP measured at 1988 prices
p is the condominium value index.
RP14 (Shock1)
For the shock to reach maximum effect on each variable, it takes:
 1 quarter of MLR
 half year of GDP
 2.5 years for mortgage lending
 1.25 years for property prices
Full impact of one standard or 150 basis point increase in RP14 imply
a 23 basis point increase in MLR
 1 billion baht decrease in mortgage lending
 1 billion baht reduction in real GDP
 1.2% fall in property prices
Response to an RP14 shock with short run and long run
Short run
Shock dissipate over time, the
effect of monetary policy
shock is transitory.
Long run
Property price variance decomposition (%)
SVAR model’s result shows:
• 40% of variation in property price explained by variation in MLR
• 30% by variation in RP14
• bank mortgage loan explained less than 5% of variation in property price.
Overall impact of monetary policy on property price
Monetary policy plays and important role in:
 Bank lending
 The economy
 Property price
So, applying monetary policy to deal with property prices
Effect other sectors of the economy
(Section5) Assessment of financial fragility in
the current market environment
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Measuring sensitivity of mortgage plans to interest rate increase
In the past, fixed rate (high rate)
Now float exchange rate
Mortgage loan
Example of mortgage payment plan
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If the interest rate is 3.75% for the first two years
Fixed minimum payment 7,020 baht and assumed MLR remain at
5.75% and payment contract over the 20 year contract term.
Float at MLR or MLR+
salary 20,000 baht/month x 60 times = Max loan
loan 1,000,000 baht at MLR 5.75, 30-35% of salary
repayment 20 years.
Pay per month 7,020 baht
MLR + 60 base point
MLR+, 8.25% = additional 1,020 baht, = 5% of salary
So, pay per month 8,040 baht, = 40% of salary
Payment profile of a hypothetical mortgage
contract when MLR remains at 5.75%
Stress testing, banks’ capital
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1.
2.
3.
4.
5.
To assess the impact of a property price collapse on banks’
capital positions
Increase in required loan-loss provision
Loss of interest income
Increase in NPL resource costs
Losses on impairment of properties foreclosed
Losses from bank-owned AMCs
Schematic representation of the stress test model
(Section6) Implication for policy
1.
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Monetary policy
Interest rate MLR
Provision requirement
Mortgage insurance
Preemptive strike
2. Effective monitoring and early warning system
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1.
2.
3.
4.
5.
6.
7.
Real estate information center (REIC) at GHB
Index
Land housing permit
Housing start
Housing competition
Home sale
Housing transfer
Housing price index
Housing finance
Lists of selected indicators used by other countries in
their monitoring system that relevant in Thai context.
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Experiences from other countries that have gone through similar
property boom and bust cycle.
1.
Affordability index (A rise in the index represent deterioration on households’
capacity to afford a mortgage)
2.
Buy and rental gap (which compare the cost of purchasing and maintaining a
residential unit to a cost of renting )
3.
Cancellation of future project
Lending behavior of bank and their risk exposures
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LTV profile
In some countries, bank lending practice (must check every 3
months)
Bank are loosening or tightening credit policy.
Look at D/E ratio
3. Sound credit risk management practices by banks
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Sound credit risk management keep financial imbalances in check.
Move from collateral-based lending to risk-based lending
practice.
Risk based lending emphasizes a borrower’s future cash flow.
RADOC, bank’s risk-adjusted return on capital
Credit risk models for property loan portfolio (data on LTV, loan
age, loan size and loan type)
Pool database
DIA (FDIC in USA) the institution of deposit insurance to be
more careful when making loan for Thailand
4. Prudential regulation and supervision
Primary instrument for financial stability
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Extend to information disclosure and corporate governance
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Provide safeguard to measure for financial institution system
Three major prudential measures
1.
Loan classification standards and tightening of provisioning
requirements.
2.
Restriction on the maximum LTV 70%for mortgage loans larger
than 10 million baht.
3.
Mandatory disclose requirement for houses valued more than
100 million baht.
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Concluding remark
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Property market and banking sector are two sectors in the
economy that matter to financial stability.
Banking sector is no cause for undue alarm.
Thai bank have enough capital and loan loss reserves to withstand
the impact of isolated 30% decline in property prices.
No banks would fail under the stress scenario.
Need authorities to closely monitor developments in the property
market and banks’ lending practice.
Lastly, protect themselves from fluctuations in the property
market.