ALM Implementation in Banks – an approach paper Fundamentals of ALM3 Overview3 Structural Liquidity Risk3 Interest Rate Risk3 Inadequacy of balance sheet4 Non-term products4 Probabilistic cash flow products4 Options, Futures and derivatives4 Profitability4 Bank ALM policy5 Product5 Structural Liquidity5 Gap Measurement6 Cost to close gap6 Maximum Cumulative Outflow6 Scenario Analysis7 Interest rate risk7 Interest rate Gap7 Duration Gap7 A model for implementation9 ALM implementation – problems in banks9 Case study of ALM implementation in a large bank in Western Africa9 Fundamentals of ALM Overview
ALM techniques are used to manage assets and liabilities by timeframe. Objectives of ALM are: • Maximize profitability • Minimize use of capital • Ensure structural liquidity • Ensure robustness in market risk management • ‘Just in time’ money Risks addressed by ALM are described below. Structural Liquidity Risk Liquidity has often been defined as ‘Ability to raise money that is not required’ in a humorous vien, the argument being that the day you need this money, no one will be willing to lend to you. Liquidity risk is simple mathematics but complex finance. Structural Liquidity risk is measured in multiple ways.
Gap between inflows and outflows by timeframe is a measure. Cost to close gap may be used as a measure of liquidity risk. 7-day Maximum cumulative outflow is another method. One may use all of the above. Interestingly, many trading strategies involving complex models make an assumption of infinite liquidity. Reality is liquidity is finite and this can only be ignored at one’s own peril. Interest Rate Risk Gap between interest rate sensitive assets and liabilities, spread over time is a measurement of market risk. This is a simplistic measure, a minimum that is required.
Sensitivity of Net Interest Income (NII) to interest rate change is another view. Basel recommends sensitivity to a 200 basis points parallel shift in yield curve as a standard measure. 200 basis points is a Basel guideline. Central banks of individual countries may impose different measures. This measure, when used over multiple scenarios can give a reasonable picture of sensitivity of interest rate income to movements in interest rates. Traditionally, banks have a trading book and a banking book. For purposes of determining interest rate sensitivity, both books are mapped to zero coupon bonds, preserving market risk.
Combined book represents bank’s interest rate risk profile. Traditional methods like modified or dollar duration gap and convexity gap analysis enable risk measurement of interest rate sensitivity. Inadequacy of balance sheet ALM techniques are not meant to replace balance sheet techniques in any shape or form. It is a completely different technique. First of all, ALM addresses time bucket concept, whereas balance sheet ignores time element completely. Secondly, ALM demands inclusion of off-balance sheet items that have potential impact on ALM sheet – for example unutilized portion of cash credit i. . options given to customers. Non-term products This is the complex finance part. Certain products, example savings bank have no contracted terms. Thus, they present conceptual difficulty in being mapped to zero coupon bonds as it is not possible to determine date when cash flows occur. Thus, such products are generally split into two or more Zero coupon bonds, maturing on different dates. These parts are termed volatile and core. Core is expected to mature in later time buckets. Volatile portion is expected to be in first bucket. This may change by nature of account and other dimensions.
This is a study in itself. Probabilistic cash flow products Savings bank and current account are examples of banking book transactions of probabilistic cash flow behaviour. Banks are net sellers of options, both explicit and embedded. On trading book, probabilistic cash flows define instruments. Thus, complex models based on sophistication are required to map derivative type of instruments into the cash flow model. Options, Futures and derivatives Bank uses these instruments to hedge positions. To offer a customer a long position in USD at a certain rate, bank has to hedge by taking a corresponding short position.
Thus, regardless of USD rate, bank is fully protected, offering customer protection as well. Thus, options, futures and derivatives may be used to take positions, apart from hedging. Difference needs to be identified as Basel II norms specify different treatments for the same. Profitability Profitability by business units, as given out by simple balance sheet is distorted. A business unit or a branch located in a residential area is by definition a deposit-taking branch. Thus, its profitability should be measured by efficiency of deposit collection i. e. eighted average interest rates of deposit collection by time buckets compared to a standard yield curve. Thus, concept of funds transfer pricing has emerged strongly in the past few years and is in itself a separate subject. Bank ALM policy ALM policy is drafted and updated by bank’s ALCO. ALM policy demands that board of directors, Asset Liability committee follow a formal procedure. ALM Policy covers bank’s position on all risks – credit risk, market risk, liquidity risk etc. Banking keeps emerging as a practice and in times will change even further. Thus, policies must be reviewed every now and then.
This ensures that practices are current, though business itself does not change. In India, for example, for a large number of years, it was liability creation that was the prime driver. Once bank gathered enough funds, there were multiple asset creation avenues. However, of late, it is asset creation that comes first, followed by liability creation. Product Section Both assets and liabilities are considered products and parameters defined for both. For example, deposits may have various characteristics and structures for interest rates. Even plain vanilla deposits need to be priced and priced by timeframe.
Competition may introduce new products based on ALM positions. Banks may have to price based on their ALM positions. Thus, this section of ALM policy defines products that bank may deal in – both assets and liabilities. Complexities are introduced by options – both explicit and embedded. Savings bank and cash credit is a classic case of embedded options. Thus, ALCO needs to understand impact of probabilistic cash flows before approving such products. Before being offered, product creation needs to go through a proper introduction and approval mechanisms through ALCO.
Thus, policy should address parameters that should never be crossed. Structural Liquidity Structural liquidity policies must be defined for measurement and implementation of liquidity controls in any financial institution. Individuals practice structural liquidity measurement and control for personal portfolios. Thus, it stands to reason that these are even more essential for banks. Gap Measurement Time buckets are defined as bands. 1-14 days, 15-days to 1 month, 1 month to 2 months etc. is an example. This organisation is termed a maturity bucket scheme. All cash flows are mapped to corresponding buckets.
Thus, entire portfolio of cash flows is now reduced to a bucket representation, thus making it easier to analyse. Since all products are mapped, assets represent all inflows and liabilities represent all outflows. Thus gaps in each time bucket is analysed. Regulators specify use of percentage of tolerance for gaps. Practical bankers use an absolute amount. Thus, as long as gap remains within tolerance, then it is deemed zero. Thus, the statement in the beginning that zero gap is impractical and not desired either. Bank’s funding or lending gaps may be very deliberate. Cost to close gap
This is another measurement for structural liquidity. The last bucket is closed first using market interest rate for that bucket. Some implementations divide all buckets to months internally and calculate cost to close at month level. Cost to close of the last bucket is them taken as an outflow in the previous bucket and that closed and so on all the way till the first bucket is closed. That gives the total cost to close gap. The other way is to simply calculate cost to close gap for each bucket based on interest rate and assuming that all cash flows occur at the gap median.
Tolerance to limits of cost to close is defined as a measure of structural liquidity risk and this is used for control. Maximum Cumulative Outflow Maximum cumulative outflow analysis is measured in number of days. 7 day or 15 day MCO is used as a practical measure. This simply adds up all cumulative outflows. No inflows are considered. Thus, this measure indicates a sum of all possible cash outflows in seven day period. Tolerance to MCO may be another measure to improve structural liquidity control. Scenario Analysis Liquidity analysis scenarios are generated. A typical measure would involve worst case (MCO analysis), best case and likely. This may be used to commit money in money markets et. Al. ). These scenarios are scrutinized and their impact approved by ALCO as a matter of routine. All analysis referred to above provide measures enabled by these scenarios. Many banks, as a matter of routine, create scenarios on top of native cash flows. They alter nature of native cash flows based on their prior knowledge. Derived cash flows are indeed scenarios that have been pre-defined. Interest rate risk Interest rate risk is measured using traditional techniques for measurement of market risk. Market risk exists due to volatility of interest rates.
Financial institutions make money as they take market risk. For example, if a bank provides a 10 year housing loan, then it is has to locate 10 year assets to minimize market risk for that loan. Both traded and non-traded assets and liabilities carry market risk and any technique should address this. All products carry market risk and this needs to be addressed as well. It must be understood that all statistical techniques are forecasting algorithms based on history in some form or the other. There is no guarantee that history will repeat itself and new paths and patterns may emerge.
Statistical techniques help make judgments. They are not replacements for flesh and blood managers. Interest rate Gap Interest rate gap of a bucket is calculated in a manner similar to liquidity gap. Tolerance of gap in terms of percentage, absolute values is a risk control measure. Tolerance provides control point as well. Buckets may be determined carefully. Making buckets too small leaves a large number of buckets. Making them too large may hide some sensitivity issues. Especially in volatile buckets (1-90 days), definitions must be small and in larger buckets (3 years to 30 years), bucket size may be larger.
As with liquidity, an absolute value of gap may be used to measure this risk. Duration Gap Duration gap measures sensitivity of portfolio to interest rate changes. Dollar duration is a measurement of drop in market value of (bank as) portfolio for a weighted average change of interest of 1%. Modified duration is a measure perfected by bond traders is a measure of sensitivity of market value of (bank as) portfolio to interest rate changes. Thus, in this analysis, bank’s transactions are mapped as zero coupon bonds and their market value determined using yield curves for discounting. Then duration is calculated for the same.
However, a point to note is that usage of a yield curve may not be correct for some products. A more realistic discounting measure would be the product’s own interest rate. NII Sensitivity analysis Sensitivity of Net Interest Income to movement in interest rates may be determined by changing interest receivable and payable. It is assumed that 100% of assets and liabilities will get re-priced. This may not be realistic and re-pricing % is a parameter that must be determined by bank’s behaviour. Thus, sensitivity of NII to interest rate movement and interest rate shocks are a interest rate risk measure that may be used.
Unlike duration, this is more simplistic and will not carry the concept of ‘time value of money’. Scenario Analysis Interest rate sensitivity analysis scenarios are generated. A typical measure would involve worst case drop in NII – rate shock of x% on cost and y% on yield, best case and likely. These scenarios are scrutinized and their impact approved by ALCO as a matter of routine. All analysis referred to above may be measured for above scenarios. Many banks, as a matter of routine, create scenarios on top of native cash flows. They alter nature of native cash flows based on their prior knowledge.
Derived cash flows are indeed scenarios that have been pre-defined. A model for implementation For any risk measurement in finance, all complex instruments are reduced to simple instrument in an artificial manner, preserving market value and market risk. Then, simple instruments are analysed for risks. The simplest financial instrument is a zero coupon bond. BALM implements all above functions by reducing banking transactions to a simple zero coupon bond. Mapping of term products to zero coupon bonds is very straightforward. Maturity date is known and principal is expected back on the cash flow date.
Interest however, is put into another item called interest receivable as another zero coupon bond as this is required for re-pricing effect on NII and interest bears zero interest rate. However, mapping of non-term products is slightly more complex. They have to be synthetically split into multiple zero coupon bonds. Splitting rules vary for each maturity bucket. BALM supports multiple concurrent bucketing schemes. Thus, for example, in scheme 1, savings bank may be split into 5% on 1-14 day bucket, 10% on 15-1 month, and 85% in over 30 years. In scheme 2, however, split may be 10% in 1day – 1 month bucket and 90% in over 30 years.
Derivation of these percentages to split by is outside the system. Models for determining this may be quite complex as these contain options and cash flows of these options have different valuation algorithms. These must be available to have evaluated options in the first place. Thus, problem reduces to determing cash flows emanating from embedded options, where no deliberate evaluation has been made, exemplified by savings bank. Here, historical behaviour of rate of change is assumed to be in a log-normal distribution and hence volatile portion determined. Non-volatile portion is determined by subtracting volatile portion from the total.
BALM Architecture ALM implementation – problems in banks Policy Lack of a coherent, documented and practical policy is a big hindrance to ALM implementation. Most often, ALCO membership itself may not be aware of implications of risks being measured and impact. Policies should address all issues concerning the bank, all policies should be clearly explained to all members of board, apart from ALCO and these must be documented. Proper revisions to this document, a quarterly review needs to be organized as well as parameters may be changing due to change in situations.
Understanding of complexities Many people in a bank need to understand risk measurements and risk mitigation procedures. Measurement of risk is a fairly simple phenomenon and does go on regardless. Formalisation of understanding, especially at a top level is very essential. Failures inevitably occur due to lack of understanding, coupled with a feeling that top management knows all that there is in banking. Organisation and culture Risk organization in banks generally land up reporting to treasury, as they are people who come closest to understanding complex financial instruments.
The fact that they are a business unit, in charge of ‘risk taking’ is overlooked. ‘Risk Taking’ and ‘Risk management’ are generally two distinct parts of any organization and both must report to a board completely independently. Openness and transparency are essential to a proper risk organization. Most organizations react badly to positions going wrong by taking more risks and enter a vicious cycle of risks. Thus, it is required that banks follow policy in both letter and spirit. This policy was derived when situation was not volatile and hence must have merit.
Most dramatic failures in the last decade have not been because of market risk or credit risk but bad risk management organizations. This must be a big pointer to boards and ALCOs on avoidance of such issues. Data and models Data may not be available at all times in requisite format. It must be remembered that many data items are assumptions and gaps must be measured in perspective. There was a case of a manual branch of a bank that was closed for 6 months in a year due to inclement weather and was largely inaccessible. As data may not be obtained from this branch for 6 months, appropriate assumptions have to be made in any event.
The argument is that for all other purposes, assumptions are being made. Sensible options need to be chosen and manual branch without computer was an example. However, in modern banking, it is mapping of models to zero coupon bonds that are an issue. Once again, arguments are that this should exist within the bank. Based on sophistication required, multiple models may be used to validate this conversion. This is strictly outside ALM framework but integrates into ALM framework. Unrealistic goals An ALCO secretary was seen desperately trying to tweak with parameters to ‘show’ less gaps in liquidity reports.
A zero gap is not practical. Returns are expected for taking risks. Banks assume market and credit risk and hence they make returns. ALCO’s job is to correctly determine positions and put in place appropriate remedial measures using appropriate risks. It is not to show things as good when they are not. In any event, market risks and credit risks are not the only causes for failure, as evidenced by failures in the last decade. Case study of ALM implementation in a large bank in Western Africa BALM implementation in the largest bank in Western Africa is being discussed.
Following diagram depicts deployment scenario of core banking system. A DIAGRAM OF CORE BANKING Specifics 165 branches were planned to be under core banking, 200+ were under BankMaster – distributed TBA (Total Branch Automation system). Bank had decided to leave some branches in manual mode and was not willing to computerize them as they were very small and returns on investment for computerization was not justifiable. Being the largest bank in the territory, its actions could move the market. Thus, any measures on liquidity control etc.. had to be carefully exercised.
Any panic in this bank would plunge that country into chaos. Bank had desired to do install ALM systems, without regulatory pressure from central bank. Thus, top management were very keen. There was no problem in risk organization. However, people were used to everyday transaction banking and needed time to get used to centralized systems. ALCO policy statement was in place and needed a review. Top management did not relate to the policy, as it was an external document, created by a consultant. ALCO meetings were not specific technical meetings. They were like EXCO meetings.
All issues except ALM were discussed. ALM statistics were produced in a very elementary manner and ALCO did not raise many expected issues. Treasury were not clear on the concept of ‘Held for trading’ and ‘Hold to Maturity’ type of marking on transactions. Hedges were not clearly marked and it was not possible to recognize hedges from positions. There were no logical explanations for some positions or hedges. Data organisation Core banking was being rolled out during ALM implementation. Thus, data from branches could be coming from TBA one day and be replaced by core banking the next day.
Data from manual branches came in only once a month rather than everyday. Thus, on each data load, an option had to be provided to duplicate last known data. The following diagram depicts data organization. INTERFACE CONTROL Hardware and system software Representatives who sold ALM software were also representatives for hardware and system software. Thus, timings were a non-issue. Procurement processes in many banks may be long and after that vendors have to deliver requisite pieces. Thus, planning for delivery of hardware and system software is a very important step and needs to be planned up-front.
Implementation steps Establishing requirements ALM policy states company’s requirements of system implicitly. Interviews with senior management to understand bank’s direction are used in addition to policy document statements. In this particular instance, implementation manager was invited to an ALCO meeting and understood existing ALCO proceedings. System review and parameterisation System is demonstrated to key people including ALCO secretariat. A second demonstration the day after first is necessary to establish parameters for the system for existing functions.
Many banks for example want to create a set of derived cash flows as a default. All such items are discussed here. System study Report and Gap analysis At the end of study, system study conclusions are reported. In addition, gaps recorded and how to address these gaps is recorded as well. In this particular case, all policy requirements were clearly addressed and there were no gaps. If there are gaps, then implementation plan must address them through customization or change in expectations from implementation. Create ALM Sheet items ALM sheet looks suspiciously like a balance sheet.
However, it is not. This sheet is also ‘As-on’. There similarity ends. There is no need for multiple balance sheets at all. Time value of money concept handled by ALM is not handled in balance sheet techniques. ALM sheet is strictly cash flows as given to system. A big difference is treatment of off-balance sheet items. As we are considering liquidity, market and credit risks, all contingent items that do not find a place in balance sheet need to be considered as well. This is a very important aspect to be considered. Interviews with all aspects of banks dealing in cash flows of any sort are necessary.
If a subsidiary is given an option of taking funds from the bank, those need to be considered as well. Employee stock and other options need to be taken into account. Data sources For each ALM sheet item, data source is identified. Data may be sourced from transactions or warehouses where items refer to term products. Synthetic cash flow rules are created where products are non-term products like savings bank. Any analysis to determine volatility is in-built into this system at this point. Data flows and verification Data flow and integrity is established in this step. Data from all sources are gathered and loaded into system.
Data is verified by whatever means are available to establish integrity, for example summing up with transaction systems or warehouses or G/L systems at total level. Once verified, all systems are go! Go Live This signals sign-off on data and methods by ALCO and start of use of system. From this point onwards, support and maintenance of roadmap are issues to consider. Do’s and Don’t;s • Do involve all ALCO members in decisions. Some functional heads may not be interested. It is best to have someone as a salesman for ALCO to sell ideas, how important these ideas are to implement central systems for better benefits for bank. Have a younger person, enthusiastic in nature as ALCO secretary. This person is responsible for all pre-ALCO analysis and distribution of ALM reports to relevant people. • Do not deliberate a lot over non-term product distribution. It is anyway a probabilistic cash flow. Worry more about systems in place to constantly review this. • ALM sheet item granularity depends on distribution for non-term products. For example, ‘savings bank’ may be one heading or ‘savings bank – salaries’ could be the level at which distribution of volatility differs. Thus, discuss these items beforehand. Do not be afraid to get it wrong. It may go wrong the first time. Thing to do is not panic, but start all over again quickly and not make same mistakes again • Do not be tempted to use ALM as a balance sheet manager. For those who have not had central systems before, this may be the first time centralized data is visible. Do not use it as a central repository. • Define functional objectives completely before starting this project. Do not keep tampering with it. • Senior management may refer to well known books on this subject to get a quick revision. Do not over-engineer your ALM sheet. Let it evolve. • Results of ALM are visible over a couple of years. Keep measuring what is required. ———————– Trading SLR BALM Model Cash Flows in terms of Amount, Cash flow Date, Currency, Interest Rate FTP ALCO Support Trends Ratio Analysis VaR …. …….. Term Deposits Term Loans Letters of Credit Current Account Savings Bank Transaction Interface Objects NII sensitivity ….. ….. Reg. Reports Scenario Analysis Cost to Close Duration Gap Interest Rate Gap Liquidity Gap BALM Applications