Analyzing and making accurate forecasts of future interest rates can limit the risks of interest rate changes by creating appropriate sensitivity gaps that match the predictions of future interest rates. Furthermore, banks that actively manage RRLS can gain profits when interest rates change in line with their predictions.
1.2.4. Factors affecting the management of interest rates at commercial banks
1.2.4.1. Technology level, professional staff capacity
The first step in the RRLS control process is to gather data to describe the current financial situation of the bank. Every measurement system, whether a gap report or an economic value simulation model, requires information on the RRLS. The bank should have a comprehensive management information system (MIS) to allow for timely and accurate access to information.
To describe the RRLS associated with a bank's business, a bank needs information for each type of financial instrument or investment portfolio on:
- Current balances and interest rate covenants related to the portfolio.
- The contractual or expected terms of the instrument or portfolio relating to principal amounts, interest rate adjustment dates and maturity dates.
- For adjustable rate terms, the interest rate portfolio used for re-pricing, as well as instruments with caps or floors....
Along with the level of technology, the awareness of RRLS is also a factor affecting the process of RRLS management. Banks need to have specialized training courses for risk management officers to improve their professional qualifications. The level of staff in QTRRLS is also an important factor affecting the Bank's QTRRLS.
1.2.4.2. Legal environment and development of financial markets
The development of a financial market affects the management of interest rates in that when the financial market develops, new tools will be created to hedge interest rates. Furthermore, when the financial market develops, interest rates will fluctuate more and therefore the need for management of interest rates will also become more diverse.
As the State Bank pays much attention to various types of risks in the banking system, risk management and supervision as well as the legal environment also greatly affect the management of interest rate risks at commercial banks.
1.2.4.3. Forecasting information system on market situation and interest rates
As presented in the above section, with a system of information and accurate forecasts of interest rate fluctuations, commercial banks will be very proactive in managing interest rate risks.
1.3. EXPERIENCE IN LOSS MANAGEMENT AT SOME FOREIGN BANK BRANCHES IN VIETNAM
1.3.1. At HSBC bank branch, Vietnam
This HSBC bank branch uses the value-to-loss (VaR) and P&L (Profit and Loss) methods to manage RRLS, VaR tells HSBC what the worst case scenario of RRLS is and VaR measures the magnitude of P&L movements on the worst days.
For example: VaR at HSBC: HSBC Singapore's VaR is $7 million
More precisely, with a 99% probability, the 10-day VaR value of the bank's Trading Book is $7 million, which means that HSBC Singapore, all of its trading positions cannot lose more than $7 million in the next 10 days, with a 99% probability. However, on the other hand, with a 1% probability, HSBC can lose more than $7 million.
This VaR figure can increase or decrease on a daily basis based on the effects of:
- Trading Positions at HSBC Singapore
- Changes in interest rates (Market Volatility)
- Performance of portfolios and other positions in Singapore.
VaR is a market volatility applied to capital positions. VaR assumes that we are stuck in today's position. The change in VaR value is caused by changes in market interest rates on the capital positions that the bank holds. VaR value uses past data to predict the near future.
How does HSBC calculate VaR?
HSBC does not use the change in Profit and Loss (P&L) to calculate VaR because P/L does not explain what will happen and how to hedge the risk, but HSBC uses P&L for Back Testing purposes.
VaR is calculated as = PVBP* market volatility
VaR = Risk (Position) * Volatility (Market)
= PVBP position/market* [ market/day * (t day/250)* 1/2* confidence]
So to calculate VaR we have to use PVBPs, this will separate VaR and P&L values into two parts, based on market states and changes (Market Volatility).
How Banks Use VaR in Risk Management
The bank has calculated the relationship between VaR and regulatory capital.
Capital = VaR (10 – days)*Regulatory Factor
Example: 99% probability , 10 days, VaR of HSBC Singapore is $7 million Assuming Regulatory Factor = 3.8 HSBC Singapore needs at least: $26.6 million capital = $7 million*3.8
If the bank does not have sufficient capital, it needs to report the above exceptional case to the Hong Kong Head Office or reduce its holding position. This will automatically reduce the VaR value and at the same time reduce the capital requirement.
The responsibility for RRLS lies with the Treasury Head, the Risk Management Director and the CFO. They need to manage it more closely and need to recognize RRLS earlier.
1.3.2. At Calyon Bank branch, Ho Chi Minh City
This bank (name withheld) manages RRLS using Head Office software, based on the following 3 methods:
a. Cash Flow Gap-Mismatch
b. Interest rate sensitivity method (Sensitivities)
c. Value at risk (VaR)
The interest rate basis used to quantify bank interest rates in Vietnamese Dong (VND) is the widely published interest rates including VNIBOR interest rates for terms up to 1 year and Government Bonds interest rates for terms greater than 1 year.
For USD, it is the interest rate on the Vietnamese market on REUTER news agency. For EUR, it is the interest rate of this currency's terms on the Vietnamese market.
a. Cash Flow Gap-Mismatch limit within 1 week, i.e. the limit that the capital department can be Negative or Positive per maturity for each currency. This limit is used to manage both interest rate risk and liquidity risk.
The purpose of this limit is to ensure that the bank can maintain continuous operations for a minimum of 1 week if a crisis occurs that seriously affects the bank's capital and during this 1 week the bank will take measures to handle the crisis. The bank has a sensitive interest rate gap limit for terms from O/N to 5 years.
To manage liquidity risk, banks have the following types of cash flow limits: 7-day limit (Long/Short), 1-month limit, general limit (in general) including Cook Weighted Assets (Basel 1) and Risk Weighted Assets (Basel 2)
Specifically, the bank stipulates the maximum cash in/out limit (Cash IN/OUT) in the next 7 days, cash IN/OUT in the next 30 days.
b. The interest rate sensitivity limit per interest rate point (Basic Point=bp), which shows how much the bank will gain or lose on its existing positions when interest rates change by 0.01%. The sensitivity limit is calculated by software based on parameters such as cash flow gap and overnight interest rates of each currency.
The sensitivity limit is valid for only the next business day and represents the profit/loss difference when interest rates change by 1 basis point for the entire balance sheet of the bank.
Banks set these interest rate sensitivity limits
c. Value-to-loss (VaR) limits: a measure of the risk of loss on individual and all items in a bank's balance sheet. These limits will be used to compare losses against market prices (Mark-to-Market).
VaR value is calculated on the software system and VaR has 5 functions: risk management, quantitative management, financial management, financial reporting and calculating the amount of capital required. VaR is extremely important because it will help save capital (Economic Capital), test the sensitivity of the market (stress testing), test and predict the level of withdrawal (back-testing), predict the level of deficit (expected shortfall).
Interest rate sensitivity limits (VaR) are calculated for each foreign currency, for example, the limits for VND and other foreign currencies are as follows:
Limit for VND
EUR100,000 | |
Limit with USD | EUR 200,000 |
Limit with EUR | EUR300,000 |
Limit with JPY | EUR100,000 |
Total VaR limit | 300,000 EUR |
Maybe you are interested!
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Identify Rating Levels and Rating Scales
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of the islanders. Therefore, this indicator will be divided into two sub-indicators:
a1. Natural tourism attractiveness a2. Cultural tourism attractiveness
b. Tourist capacity
The two island communes in Quan Lan have different capacities to receive tourists. Minh Chau Commune is home to many standard hotels and resorts, attracting high-income domestic and international tourists. Meanwhile, Quan Lan Commune has many motels mainly built and operated by local people, so the scale and quality are not high, and will be suitable for ordinary tourists such as students.
c. Time of exploitation of Quan Lan Island Commune:
Quan Lan tourism is seasonal due to weather and climate conditions and festivals only take place on certain days of the year, specifically in spring. In Quan Lan commune, the period from April to June and from September to November is considered the best time to visit Quan Lan because the cultural tourism activities are mainly associated with festivals taking place during this time.
Minh Chau island commune:
Tourism exploitation time is all year round, because this is a place with a number of tourist attractions with diverse ecosystems such as Bai Tu Long National Park Research Center, Tram forest, Turtle Laying Beach, so besides coming to the beach for tourism and vacation in the summer, Minh Chau will attract research groups to come for tourism combined with research at other times of the year.
d. Sustainability
The sustainability of ecotourism sites in Quan Lan and Minh Chau communes depends on the sensitivity of the ecosystems to climate changes.
landscape. In general, these tourist destinations have a fairly high level of sustainability, because they are natural ecosystems, planned and protected. However, if a large number of tourists gather at certain times, it can exceed the carrying capacity and affect the sustainability of the environment (polluted beaches, damaged trees, animals moving away from their habitats, etc.), then the sustainability of the above ecosystems (natural ecosystems, human ecosystems) will also be affected and become less sustainable.
e. Location and accessibility
Both island communes have ports to take tourists to visit from Van Don wharf:
- Quan Lan – Van Don traffic route:
Phuc Thinh – Viet Anh high-speed boat and Quang Minh high-speed boat, depart at 8am and 2pm from Van Don to Quan Lan, and at 7am and 1pm from Quan Lan to Van Don. There are also wooden boats departing at 7am and 1pm.
- Van Don - Minh Chau traffic route:
Chung Huong high-speed train, Minh Chau train, morning 7:30 and afternoon 13:30 from Van Don to Minh Chau, morning 6:30 and afternoon 13:00 from Minh Chau to Van Don.
f. Infrastructure
Despite receiving investment attention, the issue of infrastructure and technical facilities for tourism on Quan Lan Island is still an issue that needs to be resolved because it has a direct impact on the implementation of ecotourism activities. The minimum conditions for serving tourists such as accommodation, electricity, water, communication, especially medical services, and security work need to be given top priority. Ecotourism spots in Minh Chau commune are assessed to have better infrastructure and technical facilities for tourism because there are quite complete and synchronous conditions for serving tourists, meeting many needs of domestic and foreign tourists.
3.2.1.4. Determine assessment levels and assessment scales
Corresponding to the levels of each criterion, the index is the score of those levels in the order of 4, 3, 2, 1 decreasing according to the standard of each level: very attractive (4), attractive (3), average (2), less attractive (1).
3.2.1.5. Determining the coefficients of the criteria
For the assessment of DLST in the two communes of Quan Lan and Minh Chau islands, the students added evaluation coefficients to show the importance of the criteria and indicators as follows:
Coefficient 3 with criteria: Attractiveness, Exploitation time. These are the 2 most important criteria for attracting tourists to tourism in general and eco-tourism in particular, so they have the highest coefficient.
Coefficient 2 with criteria: Capacity, Infrastructure, Location and accessibility . Because the assessment area is an island commune of Van Don district, the above criteria are selected by the author with appropriate coefficients at the average level.
Coefficient 1 with criteria: Sustainability. Quan Lan has natural and human-made ecotourism sites, with high biodiversity and little impact from local human factors. Most of the ecotourism sites are still wild, so they are highly sustainable.
3.2.1.6. Results of DLST assessment on Quan Lan island
a. Assessment of the potential for natural tourism development
For Minh Chau commune:
+ Natural tourism attractiveness is determined to be very attractive (4 points) and the most important coefficient (coefficient 3), so the score of the Attractiveness criterion is 4 x 3 = 12.
+ Capacity is determined as average (2 points) and the coefficient is quite important (coefficient 2), then the score of Capacity criterion is 2 x 2 = 4.
+ Exploitation time is long (4 points), the most important coefficient (coefficient 3) so the score of the Exploitation time criterion is 4 x 3 = 12.
+ Sustainability is determined as sustainable (4 points), the important coefficient is the average coefficient (coefficient 1), so the score of the Sustainability criterion is 4 x 1 = 4 points
+ Location and accessibility are determined to be quite favorable (2 points), the coefficient is quite important (coefficient 2), the criterion score is 2 x 2 = 4 points.
+ Infrastructure is assessed as good (3 points), the coefficient is quite important (coefficient 2), then the score of the Infrastructure criterion is 3 x 2 = 6 points.
The total score for evaluating DLST in Minh Chau commune according to 6 evaluation criteria is determined as: 12 + 4 + 12 + 4 + 4 + 6 = 42 points
Similar assessment for Quan Lan commune, we have the following table:
Table 3.3: Assessment of the potential for natural ecotourism development in Quan Lan and Minh Chau communes
Attractiveness of self-tourismof course
Capacity
Mining time
Sustainability
Location and accessibility
Infrastructure
Result
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
CommuneMinh Chau
12
12
4
8
12
12
4
4
4
8
6
8
42/52
Quan CommuneLan
6
12
6
8
9
12
4
4
4
8
4
8
33/52
b. Assessment of the potential for humanistic tourism development
For Quan Lan commune:
+ The attractiveness of human tourism is determined to be very attractive (4 points) and the most important coefficient (coefficient 3), so the score of the Attractiveness criterion is 4 x 3 = 12.
+ Capacity is determined to be large (3 points) and the coefficient is quite important (coefficient 2), then the score of the Capacity criterion is 3 x 2 = 6.
+ Mining time is average (3 points), the most important coefficient (coefficient 3) so the score of the Mining time criterion is 3 x 3 = 9.
+ Sustainability is determined as sustainable (4 points), the important coefficient is the average coefficient (coefficient 1), so the score of the Sustainability criterion is 4 x 1 = 4 points.
+ Location and accessibility are determined to be quite favorable (2 points), the coefficient is quite important (coefficient 2), the criterion score is 2 x 2 = 4 points.
+ Infrastructure is rated as average (2 points), the coefficient is quite important (coefficient 2), then the score of the Infrastructure criterion is 2 x 2 = 4 points.
The total score for evaluating DLST in Quan Lan commune according to 6 evaluation criteria is determined as: 12 + 6 + 6 + 4 + 4 + 4 = 36 points.
Similar assessment with Minh Chau commune we have the following table:
Table 3.4: Assessment of the potential for developing humanistic eco-tourism in Quan Lan and Minh Chau communes
Attractiveness of human tourismliterature
Capacity
Mining time
Sustainability
Location and accessibility
Infrastructure
Result
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Quan CommuneLan
12
12
6
8
9
12
4
4
4
8
4
8
39/52
Minh CommuneChau
6
12
4
8
12
12
4
4
4
8
6
8
36/52
Basically, both Minh Chau and Quan Lan localities have quite favorable conditions for developing ecotourism. However, Quan Lan commune has more advantages to develop ecotourism in a humanistic direction, because this is an area with many famous historical relics such as Quan Lan Communal House, Quan Lan Pagoda, Temple worshiping the hero Tran Khanh Du, ... along with local festivals held annually such as the wind praying ceremony (March 15), Quan Lan festival (June 10-19); due to its location near the port and long exploitation time, the beaches in Quan Lan commune (especially Quan Lan beach) are no longer hygienic and clean to ensure the needs of tourists coming to relax and swim; this is also an area with many beautiful landscapes such as Got Beo wind pass, Ong Phong head, Voi Voi cave, but the ability to access these places is still very limited (dirt hill road, lots of gravel and rocks), especially during rainy and windy times; In addition, other natural resources such as mangrove forests and sea worms have not been really exploited for tourism purposes and ecotourism development. On the contrary, Minh Chau commune has more advantages in developing ecotourism in the direction of natural tourism, this is an area with diverse ecosystems such as at Rua De Beach, Bai Tu Long National Park Conservation Center...; Minh Chau beach is highly appreciated for its natural beauty and cleanliness, ranked in the top ten most beautiful beaches in Vietnam; Minh Chau commune is also home to Tram forest with a large area and a purity of up to 90%, suitable for building bridges through the forest (a very effective type of natural ecotourism currently applied by many countries) for tourists to sightsee, as well as for the purpose of studying and researching.
Figure 3.1: Thenmala Forest Bridge (India) Source: https://www.thenmalaecotourism.com/(August 21, 2019)
3.2.2. Using SWOT matrix to evaluate Quan Lan island tourism
General assessment of current tourism activities of Quan Lan island is shown through the following SWOT matrix:
Table 3.5: SWOT matrix evaluating tourism activities on Quan Lan island
Internal agent
Strengths- There is a lot of potential for tourism development, especially natural ecotourism and humanistic ecotourism.- The unskilled labor force is relatively abundant.- resource environmentunpolluted, still
Weaknesses- Poorly developed infrastructure, especially traffic routes to tourist destinations on the island.- The team of professional staff is still weak.- Tourism products in general
quite wild, originalintact
general and DLST in particularalone is monotonous.
External agents
Opportunity- Tourism is a key industry in the socio-economic development strategy of the province and Van Don economic zone.- Quan Lan was selected as a pilot area for eco-tourism development within the framework of the green growth project between Quang Ninh province and the Japanese organization JICA.- The flow of tourists and especially ecotourism in the world tends toincreasing
Challenge- Weather and climate change abnormally.- Competition in tourism products is increasingly fierce, especially with other localities in the province such as Ha Long, Mong Cai...- Awareness of tourists, especially domestic tourists, about ecotourism and nature conservation is not high.
Through summary analysis using SWOT matrix we see that:
To exploit strengths and take advantage of opportunities, it is necessary to:
- Diversify products and service types (build more tourism routes aimed at specific needs of tourists: experiential tourism immersed in nature, spiritual cultural tourism...)
- Effective exploitation of resources and differentiated products (natural resources and human resources)
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Current Status of Control, Monitoring and Reporting of Interest Rate Risk -
Interest rate risk management at Vietnam Joint Stock Commercial Bank for Industry and Trade - 32 -
Basic Theory of Interest Rate Risk Management of Commercial Banks -
Average Interest Rate Level at Certain Points in 2010
When the VaR limit exceeds the allowable limit, the QTRR software will generate warnings to inform the transaction staff as well as the management staff. At this time, the bank needs to close its capital positions so that the VaR value is within the allowable limit. When closing these capital positions, the interest rate sensitivity gaps of the maturities automatically decrease.
Profit centers at the Branch such as: FX Desk, MM Desk, Forward Desk, Derivatives all sell positions to each other and do not hold positions (Internal Squaring). For example: FX sells USD for VND, it will send VND to the MM department and must borrow USD from the MM department.
The bank's software system is called: GCE=Global Central Exposure. The system allows tellers to know at any time how much credit limit any customer has left. At any time, dealers can know how much credit limit a customer has used and how much credit limit is left.
The risk management system is located at the Paris headquarters and is always online, updating data continuously. This system is rented by the headquarters and is used for the entire system of branches of the Bank worldwide. The rental cost is quite high, about several million EUR/1 month.
1.3.3. Comments on RRLS management at the two bank branches above
The application of the method of managing RRLS using the loss value method is the newest method in the world today, other methods such as the interest rate sensitivity gap method (Repricing Gap), PVBP, Economic Duration Gap are previous methods, however, they all have different advantages and disadvantages. In the second case, a foreign bank branch in Ho Chi Minh City has applied many other methods at the same time to manage RRLS. Reality has proven that the above branches manage RRLS quite effectively using the most modern methods today. However, it must also be recognized that in the financial statements of banks, the base currency is the US dollar (different from commercial banks in Vietnam, which use the Vietnamese dong), the interest rate fluctuations are different between the two currencies and these are branches and headquarters of these banks located in other countries, so the application of RRLS management is also somewhat different for Vietnamese commercial banks.
The advantages in the QLRRLS method of these 2 foreign bank branches are: (1) Applying advanced QTRR methods, (2) Having very modern software with very high costs, having been tested at the Head Office so the reliability is quite high, (3) Having a systematic and standardized QTRRLS process, (4) Managing RRLS by VaR is the most modern method today, (5) has proven its effectiveness in the Vietnamese market.
The experience that Vietnamese commercial banks can apply is that in the current situation of Vietnamese commercial banks when the charter capital is not high, RRLS will have a huge impact on the bank's profits and equity, so the application of modern management methods is very necessary. However, the investment cost for software is relatively high (if purchased) and also requires a team of highly qualified technical and professional experts to be able to write this software themselves (if writing the software themselves).
CHAPTER 2
CURRENT STATE OF INTEREST RATE RISK MANAGEMENT IN
VIETNAM COMMERCIAL BANKS 2007-2009 PERIOD
2.1. OVERVIEW OF BANKING SYSTEM IN VIETNAM
2.1.1. Structure of the Vietnamese Banking System
The Vietnamese banking system in 1988 consisted of four state banks: the Bank for Foreign Trade of Vietnam - VCB, the Bank for Investment and Development of Vietnam (BIDV), the Industrial and Commercial Bank and the Agricultural Bank, which were separated from the State Bank to carry out commercial activities. In May 1989, the Council of Ministers passed two decisions: 1- The State Bank of Vietnam continued to carry out its traditional functions and manage the entire banking system in Vietnam and 2- banks, credit funds and financial companies in Vietnam carried out banking activities. The State Bank of Vietnam had a very close relationship with the Ministry of Finance.
Along with the open economic policy starting in 1986 and policies to attract investment in Vietnam, the number of credit institutions has increased rapidly. Currently, the Vietnamese banking system includes the following credit institutions: 03- State-owned commercial banks (Agricultural Bank, BIDV, Mekong Housing Development Bank), 02 partially joint-stock commercial banks (VietcomBank, Vietinbank), 01 Vietnam Bank for Social Policies, 01 development bank, 38 Vietnamese joint-stock commercial banks, 05 joint-venture banks, 05 foreign-owned banks (HSBC, SCB, Shinhan, ANZ, Calyon), 45-branches of foreign banks in Vietnam, 16-finance companies, 13-financial leasing companies, 47-representative offices of foreign banks in Vietnam, 01 People's Credit Fund and 1029 People's Credit Funds.
2.1.2. Business environment of Vietnam's banking system
Currently, state-owned banks hold a position in the banking system and the Government always holds a controlling percentage. The equitization of
The state-owned banks have been slow to take off. For example, after equitization, the government still holds 91% of the capital at Vietcombank and 89% at the Industrial and Commercial Bank. The four state-owned commercial banks still account for about 60% of the total assets of the entire banking system. Meanwhile, joint stock banks, joint venture banks, finance companies, leasing companies and People's Credit Funds account for only about 20, 11, 7, and 2% respectively.

Chart 2.1. Market share of Vietnamese banks
Source: Reuters
In addition to state-owned commercial banks, joint stock commercial banks in Vietnam have affirmed their position in the Vietnamese banking system. From 2001 to 2008, the rate of increase in legal capital was 64%/year, the largest figure in the whole system. Total assets of joint stock commercial banks also increased on average by about 56%/year. Joint stock commercial banks have also received attention from foreign investors. The number of foreign investors holding shares in joint stock commercial banks has increased. However, Vietnam still limits the maximum holding rate of foreign partners for





