Risk management in financial banks involves a number of performance measures to identify, monitor and control risk exposure, profitability and expenses. Performance measures, such as the use of financial ratios analysis have direct links with the shareholders’ added-value or wealth (Heffernan 2010: 103) as this essay will explain. The process of ratio analysis brings together several of the important factors taking place within a company to analyse whether its performance is improving or deteriorating (Rones 2007: 409).
Hall et al. defines ratio analysis as “a numerical approach to investigating accounts by comparing two related figures”, and for an accounting ratio to be constructive, the two components used must be connected, for instance profit is related to the amount of capital a firm uses. Also, the main rationale for ratios is that they are used as comparative tools on interbank and intrabank level (2004: 391, 401).
This essay will initially explain five commonly exploited ratios and how they inter-relate. It then proceeds to demonstrate how they contribute to good practice in banking financial management yet do so with great limitation. Finally it concludes by positioning the role they play in good financial management across various banking models.
Financial ratios for profitability analysis assess how successful a firm has been in generating profits, showing the capital employed and turnover (ibid 2004: 401). Two indicators that highlight operating profitability are Return on Equity (ROE), measuring the return on shareholders’ investment; and Return on Assets (ROA), expressing how effectively the firm’s assets are being used to generate profit (Koch & MacDonald 2010: 97-98).
· ROE = Net Income/Ave. Total Equity
· ROA = Net Income/Ave. Total Assets
High ROE or ROA exhibits a high performance, in turn influences share prices which can increase investors confidence.
ROE and ROA are linked by the Equity Multiplier ratio, EM.
· EM = Ave. Total Assets/Ave. Total Equity
The equity multiplier (EM) acts as a measurement tool for financial leverage, showing a firm’s total assets per dollar of stockholder’s equity. A high EM indicates higher leverage, meaning the firm’s assets are heavily financed by long term debt; EM also measures risk, reflecting how many assets can go into default before a bank becomes insolvent (Koch & MacDonald 2010: 96, 101). Banks might increase their gearing to improve shareholders’ wealth; however, a healthy financial firm ought to have a good balance between assets provided through debt and assets provided by the company’s owners. A well capitalized bank should have a risk assets ratio of 8%, as set by the Basel 2 Accord (Heffernan 2010: 195), and continued by Basel 3 (Basel 3 2010). The EM link can be seen in the equation below:
· ROE = ROA x EM (Gearing or Equity multiplier)
In most cases higher ROE targets can be met by increasing ROA or increasing financial leverage, EM. A large EM can work to the firm’s benefit when earnings are positive; however, it can bring catastrophic losses impact if earnings are negative (Koch ; MacDonald 2010: 98-99). For that reason creditors like the EM number to be low, giving a firm greater chance to ride out rough times.
As stated, profitability analysis ratios have great advantages in showing a firm’s ability to operate efficiently; however, these ratios do have their limitations. Ratio analysis is a retrospective, not prospective examination. Choudhry et al. draw our attention to the fact that financial ratios are based on accounting not economic data records which represent an historical view of the bank’s performance. Bank managers have been under the assumption that the past is a good representation of the future, which is unrealistic for companies undergoing considerable changes or companies that are operating in fast changing, developing or turbulent markets (2010: 443).
Bank managers, eager to prioritize profit maximisation, might conceal bad performance by manipulating figures on the balance sheet to inflate profitability – ‘window dressing’. Banks competing on size and fast growth might increase assets by offering short-term funds to customers, or by giving customers incentives for increasing their deposit balances (Koch ; MacDonald 2010: 141).
Also, operating performance can be hiked by elements like non-recurring extraordinary transactions or selling non-conventional assets for one-time profits (ibid: 143). The proceeds of the fixed assets sold would be used to repay debt, such as loans, which in return would reduce the amount of money raised from loans relative to the amount raised from shareholders; this will improve the gearing ratio (Hall et al. 2004: 407). Those extraordinary gains should be excluded from any comparison with the bank’s own performance over time or with external counterparts, as the trend behaviour will be biased (Koch ; MacDonald 2010: 143).
Another form of data manipulation comes in the form of non-performing loan classification. Loans are given non-accrual status when its terms are considerably altered in a restructuring. That means all interest on loans that was recorded but not collected must be deducted. This practice impacts the financial statements by first understating the non-performing loans, concealing the magnitude of credit risk, secondly uncollected accrued interest increases net interest income, as a result overstating ROA and ROE respectively (ibid: 142).
We can perceive here that inflating profitability to give the impression of ‘bigness‘ or being a ‘high performer’ has a direct link to the leverage ratio, which in return increases ROE. Yet the higher the leverage, the higher the risk associated with it. De Hulster sees risk from manipulated data to have contributed enormously to the recent financial crisis (2009).
In meeting equity capital requirements imposed by regulators, banks might issue preferred stock, serving as a factor known to overstate profitability measures such as ROE, ROA, Net Income (NI) and Net Interest Margin (NIM). Interest is not paid on preferred stock instead banks pay dividends out of profit to stockholders (Koch ; MacDonald 2010: 141-142).
A further concern on ROE and ROA ratios is their failure to consider the amount of debt a company has. A firm could have excessive debt and still appear profitable in the ratio calculation (Choudhry et al. 2010: 448). Hefferman states that ROE and ROA are not adjusted for the variation in level of risk for correlated activities within the bank (2010: 142).
Asset Utilization and Expense Ratio
Returning to the components of ratios, we examine Expense Ratio (ER) and Asset Utilization (AU) or income earning ratio, and their impact on ROA.
· ROA also = AU – ER – TAX
AU = Asset Utilisation = Total Revenue/Ave. Total Assets
ER = Expense Ratio = Total Operating Expense/Ave. Total Assets
TAX = Applicable Income Taxes/Ave. Total Assets
Asset Utilization measures how well a firm is utilizing its assets in order to generate revenue. Total Revenue (TR) is the sum of interest income, non-interest income, and securities gains or losses (Koch ; MacDonald 2010: 102,104). The asset utilization ratios is essential for internal monitoring of performance over multiple reporting periods, providing warning signals or benchmarks from which imperative conclusions may be reached on operational issues. The greater the AU, the greater the bank’s ability to generate income from its assets, and in other words the lower ER and TAX, and the higher ROA (ibid: 102). Nonetheless, the AU ratio is non-conclusive; as noted previously, distressed bank managers might resort to window-dressing by posting a non-recurring sales of assets, to boost or to meet expected revenues, leading to a biased view of a firm’s performance.
Banks may have different Interest Income which is influenced by interest rates affects, realising different interest yields. This is due to disparity in composition (mix) of assets earning interest. Also, the timing of the banks’ purchases differ in relation to the interest rate cycle, and lastly banks’ investments have diverse maturities leading to using different rates on the yield curve. This would make a bank less comparable with its peers.
The non-interest income on the other hand can be understated by the absence of high fees generated from off-balance sheet activities, including derivative contracts, long-term loan commitments, guaranty offers, securitisation and swap contracts. Moreover, the enormous risk attached to these off-balance sheet activities is completely out of the ratio analysis range (Heffernan 2010: 42).
In examining the Expense Ratio (ER), total operating expenses is the sum of interest expense, non-interest expense and provisions for loan and lease losses. The lower the ER, the higher the AU, or the better the bank is controlling expenses, and working their assets to become more profitable (Koch ; MacDonald 2010: 102). Similar to interest profits discussed, the interest expenses can make the comparison of the expense ratio between banks unreliable due to interest rate effects, or the interest cost per liability. This can be caused by risk premiums that a firm pays on how risky its assets are perceived by the market. This differs from one bank to another (Jones 2007: 159). Also, the timing of the banks’ borrowings differ in relation to the interest rate cycle, and the impact of banks’ deposits diverse maturities in relation to its peers’. Interest expenses are also affected by the volume of liabilities paying interest and the composition of liabilities each firm has. For instance firms with a considerable amount of demand deposits would pay much less interest since these deposits are non-interest bearing. Like interest expenses, non-interest expenses can also differ in comparability due to each firm’s composition of liabilities (Koch ; MacDonald 2010: 102-104).
Finally ROA and thus ROE can be also be manipulated through the ER by the discretionary timing of reported loan and lease losses. This is a non-cash expense taken out of the company’s net interest income. By minimizing the provision, the ‘reserve for losses’ is understated, thus overstating earnings (ibid: 142).
Good practice in bank financial management
In order to reap the benefits of ratio analysis, bank financial managers must apply great caution to their limitations and only use them as part of a greater risk analysis based on current financial data with the integration of off-balance sheet activities. Risk can adversely affect profit-maximising. As a result good bank managers must decide on an acceptable level of risk-profit mix. The use of financial ratios has been known to assist some bank managers to evaluate this mix based on a firm’s trends, growth and troubled areas by measuring earnings, liquidity, efficiency, and gearing (Koch ; MacDonald 2010: 102-108).
Since the 1980s, the banking sector has changed enormously thanks to product innovations and the internationalization of financial payments. Progress in technology and deregulation have provided new prospects and increased competitiveness among both banks and non-banks (Greuning ; Bratanovic 2009: 1). This has added to the challenges bank managers face in order to optimise the value of the firm, yet maintaining an acceptable risk level. Bank managers are under constant scrutiny and have come under increased regulatory pressure towards greater transparency.
An effective banking supervision system should contain both off-site surveillance and on-site examination. The objective of off-site surveillance’s is to monitor the state of individual banks, peer groups, and the banking system as a whole (ibid: 369-370). This process provides an early warning of an individual bank’s problems as well as systemic concerns. Regulators and examiners spend vast effort in evaluating a firm’s asset quality, management, and market risk and this has been done through the use of composite scores from the CAMELS system. Banks are scored on the scale of 1 (best) to 5 (worst), with Koch ; MacDonald 2010 defining these criteria as:
· Capital adequacy
· Asset quality
· Management quality
· Earnings quality
· Sensitivity to market risk (2010: 36)
These are also used in on-site examinations through Asset and Liability Management (ALM). Having the right techniques in ALM assists in establishing a diagnosis and identifying causes of the troubled areas in a bank’s assets and liabilities, through the control processes that affect volume, product mix, maturity, interest rate sensitivity. These components are greatly inter-reliant (Heffernan 2010: 101). On-site examinations also help managers assess the accuracy of reports, overall operations, internal controls, quality of management and competency of risk management systems. Furthermore, banks should have statistical models in place to detect the probability of future performance based on indicators using a sample of failed or distressed banks to provide measures as ratings downgrades, failure-of-survival predictions and expected-loss likelihood (Greuning ; Bratanovic 2009: 369-371).
Bank behaviour models
Nonetheless, the measurements and examinations mentioned vary in their results and applications from one financial firm to another. In order to apply this essay’s analysis, it is necessary to briefly examine structure and size of bank behaviour models.
Such firms differ in size, the way they offer products and services, the geographical area served, customer focus and service delivery channels. The fundamental purpose of a bank is that it provided core banking features, essentially serving as an intermediary between lenders and borrowers and offering a liquidity and payments service (Heffernan 2010: 1).
Commercial banks are the first of three main banking structures. They offer wholesale banking, providing the core features to large businesses and governments, and also offering retail banking to individuals and smaller businesses.
Secondly investment banks deal with bigger corporations and governments globally by acting as intermediaries between issuers and investors. They are more diverse in the products they offer, including the off-balance sheet activities discussed. They help in mergers and acquisitions, the design and sale of securities in the primary market, while operating simultaneously in the secondary markets; they also offer consultancy and fund management (Heffernan 2010: 20).
Finally universal banks are large firms operating globally, offering a wide range of products combined from commercial and investment banking, in addition to services such as insurance (ibid: 19).
Within the existence of bank types, emerge two major financial business models, Transactions Banking and Relationship Banking. Transactions banking caters to services occurring in high frequency with standardised features that can be performed electronically. These transactions can potentially lead to less satisfactory credit ratings checks being performed (Koch ; MacDonald 2010: 20). Relationship banking, however, focuses on the banker-customer personal relationship, offering more personalized services. In reality most banks will offer a version of relationship banking to some customers or to some products, while offering transactional to others (Heffernan 2010: 24-25).
Due to regulatory regimes, often separating commercial banking from investment banking as in The Glass Steagall Act 1933-1999 (ibid: 246), the banking structure differs between countries, yet all focusing on the core banking features (Koch ; MacDonald 2010: 1, 7).
The size of a bank highly influences its operating attributes thus its ratio analysis. For instance smaller community or commercial banks generally acquire less risk leading to lower loan-to-deposit ratio. This decreases loan charge-offs and loans provisions and loss reserves, increasing their ROA. They also operate with fewer volatile liabilities than larger banks. In contrast, larger firms with substantial asset size would decrease their equity capital ratio, due to their heavy borrowing, increasing their leverage which in turn would increase the ROE. Additionally, smaller banks generate lower net interest margin, sequentially leading to a reduced noninterest income and higher noninterest expense generating a lower asset utilization fraction (ibid: 138-140).
This essay has shed light on the links among commonly exploited ratios in good (and poor) practice in banking financial management and applied it to banking models. Ultimately, financial institutions come in varying types and sizes, offering different products and services to diverse clients. Innovation, the expansion of off-balance sheet activities and the selling of risk have all made the analysis of financial accounts and the management of banks more complex (Greuning ; Bratanovic 2009: 63). Recent transformation in international banking in the wake of the crisis have shown that transferring risk has not eliminated it from the market. A bank’s reputation, performance and robustness depend on a firm’s top-level strategic positioning, and its ability to use the performance measuring tools available to them prudently and wisely.
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