This report aims to critically analyse the three common sources of banking risk (Interest risk, Liquidity risk and Operational risk) with a cohesive concentration towards the regulatory infrastructure of sources, measurements and management, that control, mitigate and cause these risks. The study will use HSBC Holdings PLC as the prime expletory focus adopting these risks in their work-place banking activities. Part B of this study will take into consideration all three risks and associate them with fraud risk (specific to HSBC) in order to forecast (or identify) three fraud scenarios that are assumed to have a higher likelihood of fraud risk exposure through the use of a fraud risk assessment framework.
Interest Rate Risk (IRR) is linked to fluctuations in interest-carrying assets (e.g. loans, bonds, asset’s option features, etc..). The tendency to develop and enhance a bank’s competitive-edge has led to the advancement of various complex products purchased and offered by the banking industry. Therefore, causing variable risk towards capital and earnings through the variance in the period of changing interest rate and actual cash flow (Comptroller of the Currency, 1997).
Based on IFCI (2004) diverse movement in interest rate has exposed international banks, such as HSBC, to accept, operate and mitigate IRR as a normal part of the regulatory banking activity for a preferred approach to maintaining and maximising shareholder value. HSBC’s IRR (with consideration to the banking book) is observed in non-traded and traded assets and liabilities (e.g. deposits, loans and financial instruments held for trading and non-trading intent) (HSBC, 2019).
Considering a BIS (2004) report, four primary sources of IRR exist, those of which banks are commonly exposed to. These primary forms of IRR are mentioned in detail in the below table and are directly relevant to HSBC’s IRR sources
The repricing model, (a.k.a. Funding gap) is the most frequently sought-after form of measurement, due to its simplicity and value-added results. Analytically showcasing the different price assumptions in a specific period of time (BIS, 2001).
As briefly referred to above, the repricing model strengths are regularly noticed in its simplicity to calculate (assuming the required information is available) and the value of information brought forth. However, limitations of this measurement tool are noticed in the market-value-effect, comprehensively indicating that the adverse effect of constantly changing interest rates can result in major FI (Financial institutions) net worth to significantly shift (Håkansson and Aberg, 2012). Hence, this places consideration that the repricing model is only a partial measurement of IRR. Another limited observation of the model is the runoff factor. The ability of reinvesting assets of long-term nature, places the assumption that the principle and the interest on cashflow play major key roles on amortization payments that can be invested elsewhere (demonstrating how runoff factor is rate-sensitive). (BIS, 1993)
As shown in the table above, HSBC demonstrates an overall positive repricing gap, which is considered to be a favorable outcome. However, all short-term horizons display a negative cumulative gap. Hence, HSBC is at exposure of rising interest, which could result in an increase in liabilities cost, which in return could provide an overall negative net return. Thus, reinforcing the limitations previously mentioned, and placing a plausible gap in HSBC’s interest rate (inherent risk), (HSBC, 2019).
In order to clarify the maturity measurement model, it must be noted that the funding gap model does not reflect on current market-values. However, the maturity model specifically incorporates current market-value influences. Therefore, it is argued that the maturity measurement brings forth a more recent assessment of interest rate risk when referring to HSBC’s IRR (Concha, et al., 2012).
In reference to the below table, it is evident that HSBC’s maturity gap presents a positive outcome. Nevertheless, a high percentile is exhibited in 5 year plus maturities, and once these are excluded, the maturity gap heavily falls close-to zero. This demonstrates high dependency on future maturities, and thus, exposing HSBC to higher future uncertainties. Furthermore, it should be mentioned that the maturity model does suffer from limitations. The mentioned model does take into account the timing of cashflow over the exhibited life-span of assets or liabilities. In addition, the model excludes balance-sheet level of leverage (Avery, et al., 1988).
As a side-by-side comparison, Macauley Duration model is considered to be most comprehensive measurement model among the previously mentioned forms. This is due to the model’s extent of scope and aptitude to cover maturity and timing of cashflow. In addition to syndicating the variance between maturity and coupon rates it is a preferred method of use by BIS (Mishkin, 2009)
Based on the calculations in table 1.5, HSBC will require ~4.6-years to recover the true cost of the bond; this signifies a more favorable result when the considered maturity date is in 5-years. However, it is to be noted that the duration model (similar to the previous measurements) has its own limitations, such as the ambiguity of floating rates, the inadequate use of off-balance sheet material, and the unaccounted-for conflict between shareholders and regulators (L. Beck, et al., 2000).
Due to the ongoing cycle of fluctuating interest rates, HSBC depends on over-the-counter derivatives, such as, Interest-rate-swaps, Swaptions, Cap, Future Contracts and Future-rate-agreements. Which are contracts devised to provide financial leverage among counterparties (FI’s), see figure 1.1. This is a common approach for all banks (Rivas, et al., 2011). However, HSBC’s reported financial statement (2018) displays a highly negative exposure of ~$1,488 Mn (see figure 1.2). This is irregular considering that the past four years of operation demonstrates a positive outcome of over $1,000 Mn. This is presumed to be the reflected cause of the 62% drop in profits, which had occurred in 2016.
situated split between variable and fixed loans. This in return minimises the FI’s exposure when an economic recession occurs, and maximises profits when the economy is strong, whilst maintaining collateral (Liu and Ryan, 2006).
On the other hand, by linking aims to closely maintain the same interest rates between both assets and liabilities, the object of the tactic is to get the two variables as close as possible (Gebhardt and Novotny, 2011).
The table indicates that the key objective of the ALM is to stabilise NII whilst maintaining interest exposure. ALM aims to maximise shareholders’ wealth by maintaining long-term value as well as ensuring regulatory compliance and mitigating liquid risk. All three gap measurements (Funding, Maturity and Duration) are conducted by ALM and supervised by the asset-liability management committee (ALCO) (Charumathi, 2008). ALCO (Asset-Liability Committee) oversee ALM’s collection of interest-rate impact scenarios in order to develop a scenario simulation test (SST). The SST provides a keen understanding on the typical types and levels of IRR exposure, and augment the risk-return trade-off. The simulation process requires the following (Choudhry, 2011):
• A comprehensive selection of target variables
• Classification of IIR scenarios
• Keeping into consideration the time path of interest rate calculation
• Preparation of future-balance-sheets based on the model outcome
• Forecast net income and margins based on developed model scenario
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