final project

CAMELSC FRAMEWORK

During an on-site bank exam, supervisors gather private information, such as details onproblem loans, with which to evaluate a bank's financial condition and to monitor itscompliance with laws and regulatory policies. A key product of such an exam is a supervisory rating of the bank's overall condition, commonly referred to as a CAMELSCrating. The acronym "CAMELSC" refers to the five components of a bank's condition that are assessed: Capital adequacy, Asset quality, Management, Earnings, and Liquidity. A sixthcomponent, a bank's System and control was added; hence the acronym was changed to CAMELSC. CAMELSC is basically a ratio-based model for evaluating the performance of banks. Various ratios forming this model are explained below:

C- Capital Adequacy:

Capital base of financial institutions facilitates depositors in forming their risk perceptionabout the institutions. Also, it is the key parameter for financial managers to maintainadequate levels of capitalization. Moreover, besides absorbing unanticipated shocks, itsignals that the institution will continue to honor its obligations. The most widely usedindicator of capital adequacy is capital to risk-weighted assets ratio (CRWA). According toBank Supervision Regulation Committee (The Basle Committee) of Bank for InternationalSettlements, a minimum 9 percent CRWA is required.

Capital adequacy ultimately determines how well financial institutions can cope withshocks to their balance sheets. Thus, it is useful to track capital-adequacy ratios that takeinto account the most important financial risks—foreign exchange, credit, and interest raterisks—by assigning risk weightings to the institution’s assets.

A sound capital base strengthens confidence of depositors. This ratio is used to protectdepositors and promote the stability and efficiency of financial systems around the world.The following ratios measure capital adequacy:

1) Capital Risk Adequacy Ratio:

CRAR is a ratio of Capital Fund to Risk Weighted Assets. Reserve Bank of India prescribesBanks to maintain a minimum Capital to risk-weighted Assets Ratio (CRAR) of 9 % withregard to credit risk, market risk and operational risk on an ongoing basis, as against 8 %prescribed in Basel documents.

Total capital includes tier-I capital and Tier-II capital. Tier-I capital includes paid up equitycapital, free reserves, intangible assets etc. Tier-II capital includes long term unsecuredloans, loss reserves, hybrid debt capital instruments etc. The higher the CRAR, the strongeris considered a bank, as it ensures high safety against bankruptcy.

CRAR = Capital/ Total Risk Weighted Credit Exposure

TOLANI INSTITUTE OF MANAGEMENT STUDIES

2) Debt Equity Ratio:

This ratio indicates the degree of leverage of a bank. It indicates how much of the bankbusiness is financed through debt and how much through equity. This is calculated as theproportion of total asset liability to net worth. ‘Outside liability’ includes total borrowing,deposits and other liabilities. ‘Net worth’ includes equity capital and reserve and surplus.Higher the ratio indicates less protection for the creditors and depositors in the bankingsystem.Borrowings/ (Share Capital + reserves)

3) Total Advance to Total Asset Ratio:

This is the ratio of the total advanced to total asset. This ratio indicates banksaggressiveness in lending which ultimately results in better profitability. Higher ratio ofan advance of bank deposits (assets) is preferred to a lower one. Total advances also includereceivables. The value of total assets is excluding the revolution of all the assets.Total Advances/ Total Asset

A – Asset Quality:

Asset quality determines the healthiness of financial institutions against loss of value in theassets. The weakening value of assets, being prime source of banking problems, directlypour into other areas, as losses are eventually written-off against capital, which ultimatelyexpose the earning capacity of the institution. With this backdrop, the asset quality isgauged in relation to the level and severity of non-performing assets, adequacy ofprovisions, recoveries, distribution of assets etc. Popular indicators include nonperformingloans to advances, loan default to total advances, and recoveries to loan default ratios.

The solvency of financial institutions typically is at risk when their assets become impaired,so it is important to monitor indicators of the quality of their assets in terms of overexposureto specific risks, trends in nonperforming loans, and the health and profitability of bankborrowers— especially the corporate sector. Share of bank assets in the aggregate financialsector assets: In most emerging markets, banking sector assets comprise well over 80 percent of total financial sector assets, whereas these figures are much lower in the developedeconomies.

Furthermore, deposits as a share of total bank liabilities have declined since 1990 in many developed countries, while in developing countries public deposits continue to be dominant in banks. In India, the share of banking assets in total financial sector assets is around 75 per cent, as of end-March 2008. There is, no doubt, merit in recognizing the importance of diversification in the institutional and instrument-specific aspects of financial intermediation in the interests of wider choice, competition and stability. However, the dominant role of banks in financial intermediation in emerging economies and particularly in India will continue in the medium-term; and the banks will continue to be “special” for a long time.

In this regard, it is useful to emphasize the dominance of banks in the developing countries in promoting non-bank financial intermediaries and services including in development of debt-markets. Even where role of banks is apparently diminishing in emerging markets, substantively, they continue to play a leading role in non-banking financing activities, including the development of financial markets. One of the indicators for asset quality is the


ratio of non-performing loans to total loans. Higher ratio is indicative of poor credit decision-making.

NPA: Non-Performing Assets:

Advances are classified into performing and non-performing advances (NPAs) as per RBIguidelines. NPAs are further classified into sub-standard, doubtful and loss assets based onthe criteria stipulated by RBI. An asset, including a leased asset, becomes nonperformingwhen it ceases to generate income for the Bank.

An NPA is a loan or an advance where:

1. Interest and/or installment of principal remains overdue for a period of more than 90days in respect of a term loan;2. The account remains "out-of-order'' in respect of an Overdraft or Cash Credit(OD/CC);3. The bill remains overdue for a period of more than 90 days in case of bills purchasedand discounted;4. A loan granted for short duration crops will be treated as an NPA if the installmentsof principal or interest thereon remain overdue for two crop seasons; and5. A loan granted for long duration crops will be treated as an NPA if the installmentsof principal or interest thereon remain overdue for one crop season.

The Bank classifies an account as an NPA only if the interest imposed during any quarter isnot fully repaid within 90 days from the end of the relevant quarter. This is a key to thestability of the banking sector. There should be no hesitation in stating that Indian bankshave done a remarkable job in containment of non-performing loans (NPL) considering theoverhang issues and overall difficult environment.

The following ratio is necessary to assess the asset quality.

1)Net NPA ratio:

Net NPAs reflect the performance of banks. A high level of NPAs suggests high probabilityof a large number of credit defaults that affect the profitability and net-worth of banks andalso wear down the value of the asset.

Loans and advances usually represent the largest asset of most of the banks. It monitors thequality of the Bank’s loan portfolio. The higher the ratio, the higher the credits risk.

Net NPA/ Total Loan


M – Management:

Management of financial institution is generally evaluated in terms of capital adequacy,asset quality, earnings and profitability, liquidity and risk sensitivity ratings. In addition,performance evaluation includes compliance with set norms, ability to plan and react tochanging circumstances, technical competence, leadership and administrative ability.

Sound management is one of the most important factors behind financial institutions’performance. Indicators of quality of management, however, are primarily applicable toindividual institutions, and cannot be easily aggregated across the sector. Furthermore,given the qualitative nature of management, it is difficult to judge its soundness just bylooking at financial accounts of the banks.

Nevertheless, total advance to total deposit, business per employee and profit per employeehelps in gauging the management quality of the banking institutions. Several indicators,however, can jointly serve—as, for instance, efficiency measures do—as an indicator of management soundness. The ratios used to evaluate management efficiency are described as under:

1) Total Advance to Total Deposit Ratio:

This ratio measures the efficiency and ability of the banks management in converting thedeposits available with the banks (excluding other funds like equity capital, etc.) into highearning advances. Total deposits include demand deposits, saving deposits, term deposit anddeposit of other bank. Total advances also include the receivables.

Total Advance/ Total Deposit

2) Business per Employee:

Revenue per employee is a measure of how efficiently a particular bank is utilizing its employees. Ideally, a bank wants the highest business per employee possible, as it denoteshigher productivity. In general, rising revenue per employee is a positive sign that suggeststhe bank is finding ways to squeeze more sales/revenues out of each of its employee.

Total Income/ No. of Employees.

3) Profit per Employee:

This ratio shows the surplus earned per employee. It is arrived at by dividing profit after taxearned by the bank by the total number of employee. The higher the ratio shows goodefficiency of the management.

Profit after Tax/ No. of Employees


E – Earning & Profitability:

Earnings and profitability, the prime source of increase in capital base, is examined withregards to interest rate policies and adequacy of provisioning. In addition, it also helps tosupport present and future operations of the institutions. The single best indicator used togauge earning is the Return on Assets (ROA), which is net income after taxes to total assetratio.

Strong earnings and profitability profile of banks reflects the ability to support present andfuture operations. More specifically, this determines the capacity to absorb losses, financeits expansion, pay dividends to its shareholders, and build up an adequate level of capital.Being front line of defense against erosion of capital base from losses, the need for highearnings and profitability can hardly be overemphasized. Although different indicators areused to serve the purpose, the best and most widely used indicator is Return on Assets(ROA).

However, for in-depth analysis, another indicator Interest Income to Total Income andOther income to Total Income is also in used. Compared with most other indicators, trendsin profitability can be more difficult to interpret—for instance, unusually high profitabilitycan reflect excessive risk taking. The following ratios try to assess the quality of income interms of income generated by core activity – income from landing operations.

1) Dividend Payout Ratio:

Dividend payout ratio shows the percentage of profit shared with the shareholders. Themore the ratio will increase the goodwill of the bank in the share market.

Dividend/ Net profit

2) Return on Asset:

Net profit to total asset indicates the efficiency of the banks in utilizing their assets ingenerating profits. A higher ratio indicates the better income generating capacity of theassets and better efficiency of management in future.

Net Profit/ Total Asset

Interest Income to Total Income:

Interest income is a basic source of revenue for banks. The interest income total incomeindicates the ability of the bank in generating income from its lending. In other words, thisratio measures the income from lending operations as a percentage of the total incomegenerated by the bank in a year. Interest income includes income on advances, interest ondeposits with the RBI, and dividend income.

Interest Income/ Total Income


3) Other Income to Total Income:

Fee based income account for a major portion of the bank’s other income. The bankgenerates higher fee income through innovative products and adapting the technology forsustained service levels. The higher ratio indicates increasing proportion of fee-basedincome. The ratio is also influenced by gains on government securities, which fluctuatesdepending on interest rate movement in the economy.

Other Income/ Total Income.

L – Liquidity:

An adequate liquidity position refers to a situation, where institution can obtain sufficientfunds, either by increasing liabilities or by converting its assets quickly at a reasonable cost.It is, therefore, generally assessed in terms of overall assets and liability management, asmismatching gives rise to liquidity risk. Efficient fund management refers to a situationwhere a spread between rate sensitive assets (RSA) and rate sensitive liabilities (RSL) ismaintained. The most commonly used tool to evaluate interest rate exposure is the Gapbetween RSA and RSL, while liquidity is gauged by liquid to total asset ratio.

Initially solvent financial institutions may be driven toward closure by poor management ofshort-term liquidity. Indicators should cover funding sources and capture large maturitymismatches. The term liquidity is used in various ways, all relating to availability of, accessto, or convertibility into cash. An institution is said to have liquidity if it can easily meet itsneeds for cash either because it has cash on hand or can otherwise raise or borrow cash. Amarket is said to be liquid if the instruments it trades can easily be bought or sold inquantity with little impact on market prices. An asset is said to be liquid if the market forthat asset is liquid.

The common theme in all three contexts is cash. A corporation is liquid if it has readyaccess to cash. A market is liquid if participants can easily convert positions into cash— orconversely. An asset is liquid if it can easily be converted to cash.

The liquidity of an institution depends on:1) The institution's short-term need for cash;2) Cash on hand;3) Available lines of credit;4) The liquidity of the institution's assets;5) The institution's reputation in the marketplace—how willing will counterparty is totransact trades with or lend to the institution.

The ratios suggested to measure liquidity under CAMELSC Model are as follows:


1) Liquidity Asset to Total Asset:

Liquidity for a bank means the ability to meet its financial obligations as they comedue. Bank lending finances investments in relatively illiquid assets, but it fund its loanswith mostly short term liabilities. Thus one of the main challenges to a bank is ensuring itsown liquidity under all reasonable conditions. Liquid assets include cash in hand, balancewith the RBI, balance with other banks (both in India and abroad), and money at call andshort notice. Total asset include the revaluations of all the assets. The proportion of liquidasset to total asset indicates the overall liquidity position of the bank.

Liquidity Asset/ Total Asset

Liquidity Asset to Demand Deposit:

This ratio measures the ability of a bank to meet the demand from deposits in a particularyear. Demand deposits offer high liquidity to the depositor and hence banks have to investthese assets in a highly liquid form.

Liquidity Asset/ demand Deposit

Liquidity Asset to Total Deposit:

This ratio measures the liquidity available to the deposits of a bank. Total deposits includedemand deposits, savings deposits, term deposits and deposits of other financial institutions.Liquid assets include cash in hand, balance with the RBI, balance with other banks (both inIndia and abroad), and money at call and short notice.

Liquidity Asset/ Total Deposit

S and C- System and control

Every business especially banks have to undergo internal control and general audit from time to time. It is the responsibility of the banking entity and its directors to ensure that it has complete and true accounting and related records. The fundamentals of internal control and audit are needed for the well-being of the banking organization, safeguarding its assets, to prepare financial statements and to comply with legislation. In this article we will hence deal with the basic of internal control and audit for banks:

It is a known fact that your accounting system will be rendered useless and inadequate if it does not have a system of appropriate internal controls. The fundamental objective of a business also makes it the responsibility of the management to implement proper control system. The management has to make sure that all important transactions of the banks are properly recorded. Errors and irregularities which become apparent while processing information should be thus easily removed due to the control and audit system. It also helps


to make sure that the assets and liabilities which are shown in the books, actually exists and are correctly recorded.

Internal control for a bank is broadly classified into two: primary control and secondary control. Primary control is related to the prevention of errors and irregularities. Now if an error and irregularity is evident, primary control has to detect the same. Primary controls are thus very important for banking activities. Secondary control on the other hand is related to management’s review and scrutiny of budgets, accounts and other financial information. It deals also with transactions and balances and the use of analytical techniques. Secondary control activities are very similar to that used by auditors and inspectors in business.

Apart from control, another activity which is important for a business is the – Internal audit. Internal audit or simply inspections are important part of banking system. They form a part of the control, system used in banks. Internal audit usually deal with operational elements such as granting of loans, checking loan procedures etc. These days internal audit also cover all transactions and review of internal control. How frequent internal audit should be done, depends on the management. If they think that the business deals with sufficient risky activities, internal audits become a usual activity.


LITERATURE REVIEW

1) EVALUATING PERFORMANCE OF BANKS THROUGH CAMEL MODEL:- A CASE STUDY OF SBI AND ICICI(B S Bodla and Richa Verma)

The objectives of the study were To describe the CAMEL Model of rating banking institutions so as to catch up the comparative performance of various banks and To study the performance of these 2 banks (SBI and ICICI) and to move in direction with the Indian banking association report “Banking industry vision 2010” that some of the Indian banks would become the global players in coming years.

And the study shows that the investment policy of SBI is more conservative in comparison to ICICI bank. Also, ICICI has succeeded in maintaining higher level of management efficiency then SBI. On the whole, ICICI bank has performed better than SBI.

2) A CAMEL Model assessment of old private sector banks in India(Roji George)

The objective of the study was to examine performance and financial health of old sector private banks of India in the context of new regulation and stiff competition.

And the result of overall ranks of the selected banks indicate that Federal bank is the best bank, followed by Karur vysya bank ltd(KVB), South Indian bank, Jammu and Kashmir bankand ING vysya bank in order.

3) PERFORMANCE ASSESSMENT OF BANKS USING CAMELS FRAMEWORK (Vipin Benry & Thomas Paul Kattokaran)

The objective of the study was to understand the relevance of CAMELs model in assessing performance of banks.

And by analyzing the data, it was found that both the banks are fundamentally sound but with moderate weakness in regard to one or more component of CAMELS’. the Dhanalakshmi Bank leads in capital adequacy, asset quality, liquidity whereas south Indian bank leads in rest of the parameters. Overall the performance of Dhanalakshmi Bank is comparatively better than that of south Indian bank.

4) AWARENESS AND PERCEPTION OF CAMEL RATING ACROSS BANKS: SOME SURVEY EVIDENCE(Manish Mittal And Arun Dave)

The objective of the study was to find out the awareness level as well as perception among bank employees about CAMEL rating and the efforts made by them for improving the ratings of their banks.


And the study reveals that there are significant differences among the employees of the banks belonging to the different sector, regarding their awareness and perception about the camel rating. The foreign bank employees are highly aware of the rating system and so they have positive perception for the same. on the contrary private sector bank employees are least aware of the rating system and the public bank lie in between.

5) CAMEL analysis, prudential regulation and banking system soundness in Nigeria (Adolphus j toby)The objectives of the study were to select financial indicators and their prudential implication for banking system soundness in Nigeria and to study a preference for highly profitable money and capital market instruments and thereby curtailing credit to the economy.

And the empirical evidence in this study shows that the Nigerian banks preference for improved liquidity does not actually enhance the loan to deposit ratio. The weak and insignificant correlation between the ratio of loan-to-total assets and bank profitability measures confirm the declining impact of the bank loans portfolio. Although positive and significant relationship between capital adequacy and bank solvency justifies current regulatory intervention in the form of increase capital requirement.

6) FINANCIAL SOUNDNESS OF OLD PRIVATE SECTOR BANKS (OPBS) IN INDIA AND BENCHMARKING THE KERALA BASED (OPBS): A ‘CAMEL’ APPROACH (Manoj P K)

The objectives of the study were to make a comparative analysis of the financial soundness of old private sector banks(OPBs) in India for the ten years period (FY 2000 to 2009) using CAMEL model, to benchmark the relative position of Kerala based OPBs (KOPBs) in respect of financial soundness with other OPBs in India and to draw broad conclusions regarding the relative financial position of individual KOPBs and accordingly to suggest appropriate strategies for their enhanced competitiveness.

And It is quite clear from the conclusion that all the KOPBs are lagging behind the ‘Best in Class’ in financial soundness. Only one KOPB has got financial soundness that is comparable with even the national average. This indicates that the other three KOPBs have to struggle hard for their survival and growth.


INTRODUCTION TO BANKS

State Bank of India

Founded- 1st July 1955

Headquarters- Mumbai, Maharashtra, India

Products - Investment Banking Consumer Banking Commercial Banking Retail Banking Private Banking Asset Management Pensions Mortgages Credit Cards

State Bank of India (SBI) is the largest state-owned banking and financial services company in India. The bank traces its ancestry to British India, through the Imperial Bank of India, to the founding in 1806 of the Bank of Calcutta, making it the oldest commercial bank in the Indian Subcontinent. Bank of Madras merged into the other two presidency banks, Bank of Calcutta and Bank of Bombay to form Imperial Bank of India, which in turn became State Bank of India. The government of India nationalized the Imperial Bank of India in 1955, with the Reserve Bank of India taking a 60% stake, and renamed it the State Bank of India. In 2008, the government took over the stake held by the Reserve Bank of India.

SBI provides a range of banking products through its vast network of branches in India and overseas, including products aimed at non-resident Indians (NRIs). The State Bank Group, with over 16,000 branches, has the largest banking branch network in India. It’s also considered as the best bank even abroad ,having around 130 branches overseas [including 1 ADB]and one of the largest financial institution in the world . With an asset base of $352 billion and $285 billion in deposits, it is a regional banking behemoth. It has a market share among Indian commercial banks of about 20% in deposits and advances, and SBI accounts for almost one-fifth of the nation's loans.

The State Bank of India is the 29th most reputed company in the world according to Forbes. Also SBI is the only bank to get featured in the coveted "top 10 brands of India" list in an annual survey conducted by Brand Finance and The Economic Times in 2010.

The State Bank of India is the largest of the Big Four Banks of India, along with ICICI Bank, Punjab National Bank and Canara Bank — its main competitors. and" GUINNESS BOOK OF WORLD RECORD " that 56 million transactions happening per day all over the world is definitely an achievement


http://en.wikipedia.org/wiki/Canara_Bank

http://en.wikipedia.org/wiki/Punjab_National_Bank

http://en.wikipedia.org/wiki/ICICI_Bank

http://en.wikipedia.org/wiki/Big_four_banks

http://en.wikipedia.org/wiki/Forbes

http://en.wikipedia.org/wiki/Non-resident_Indian

http://en.wikipedia.org/wiki/Reserve_Bank_of_India

http://en.wikipedia.org/wiki/Government_of_India

http://en.wikipedia.org/wiki/Indian_Subcontinent

http://en.wikipedia.org/wiki/Bank_of_Calcutta

http://en.wikipedia.org/wiki/Imperial_Bank_of_India

http://en.wikipedia.org/wiki/Imperial_Bank_of_India

http://en.wikipedia.org/wiki/British_Raj

http://en.wikipedia.org/wiki/India

http://en.wikipedia.org/wiki/Financial_service

http://en.wikipedia.org/wiki/Bank

http://en.wikipedia.org/wiki/Government-owned_corporation

IDBI Bank

Founded- July 1964

Headquarters- Mumbai, India

Products- Finance and insurance

The Industrial Development Bank of India Limited (IDBI) is one of India's leading public sector banks and 4th largest Bank in overall ratings. RBI categorized IDBI as an "other public sector bank". It was established in 1964 by an Act of Parliament to provide credit and other facilities for the development of the fledgling Indian industry.[2] It is currently 10th largest development bank in the world in terms of reach with 1300 ATMs, 758 branches and 513 centers.[3] Some of the institutions built by IDBI are the National Stock Exchange of India (NSE), the National Securities Depository Services Ltd (NSDL), the Stock Holding Corporation of India (SHCIL), the Credit Analysis & Research Ltd, the Export-Import Bank of India(Exim Bank), the Small Industries Development Bank of India(SIDBI), the Entrepreneurship Development Institute of India, and IDBI BANK, which today is owned by the Indian Government, though for a brief period it was a private scheduled bank.

IDBI has played a pioneering role, particularly in the pre-reform era (1964–91),in catalyzing broad based industrial development in the country in keeping with its Government-ordained ‘development banking’ charter. In pursuance of this mandate, IDBI’s activities transcended the confines of pure long-term lending to industry and encompassed, among others, balanced industrial growth through development of backward areas, modernization of specific industries, employment generation, entrepreneurship development along with support services for creating a deep and vibrant domestic capital market, including development of apposite institutional framework.


http://en.wikipedia.org/wiki/Entrepreneurship_Development_Institute_of_India

http://en.wikipedia.org/wiki/Small_Industries_Development_Bank_of_India

http://en.wikipedia.org/w/index.php?title=Export-Import_Bank_of_India&action=edit&redlink=1

http://en.wikipedia.org/w/index.php?title=Export-Import_Bank_of_India&action=edit&redlink=1

http://en.wikipedia.org/w/index.php?title=Credit_Analysis_%26_Research_Ltd&action=edit&redlink=1

http://en.wikipedia.org/w/index.php?title=Stock_Holding_Corporation_of_India&action=edit&redlink=1

http://en.wikipedia.org/w/index.php?title=Stock_Holding_Corporation_of_India&action=edit&redlink=1

http://en.wikipedia.org/w/index.php?title=National_Securities_Depository_Services_Ltd&action=edit&redlink=1

http://en.wikipedia.org/wiki/National_Stock_Exchange_of_India

http://en.wikipedia.org/wiki/Act_of_Parliament


Punjab National Bank

Founded-Lahore (1895)

Headquarters-New Delhi, India

Products-Investment Banking Consumer Banking Commercial Banking Retail Banking Private Banking Asset Management Pensions Mortgage loans Credit Cards Life insurance

Punjab National Bank (PNB) is the third largest bank in India. It was registered on May 19, 1894 under the Indian Companies Act with its office in Anarkali Bazaar Lahore. Today, the Bank is the second largest state owned commercial bank in India with about 5000 branches across 764 cities. It serves over 37 million customers. The bank has been ranked 248th biggest bank in the world by the Bankers Almanac, London. The bank's total assets for financial year 2007 were about US$60 billion. PNB has a banking subsidiary in the UK, as well as branches in Hong Kong, Dubai and Kabul, and representative offices in Almaty, Dubai, Oslo, and Shanghai.

Punjab National Bank is one of the Big Four Banks of India, along with ICICI Bank, State Bank of India and Canara Bank .


http://en.wikipedia.org/wiki/Canara_Bank

http://en.wikipedia.org/wiki/State_Bank_of_India



http://en.wikipedia.org/wiki/Big_four_banks

http://en.wikipedia.org/wiki/Shanghai

http://en.wikipedia.org/wiki/Oslo

http://en.wikipedia.org/wiki/Dubai

http://en.wikipedia.org/wiki/Almaty

http://en.wikipedia.org/wiki/Kabul

http://en.wikipedia.org/wiki/Hong_Kong


http://en.wikipedia.org/wiki/Lahore


Bank of Baroda

Founded-1908

Headquarters- Bank of Baroda,Baroda Corporate Centre,Plot No - C-26, G - Block,Bandra Kurla Complex,Mumbai India

Products-Finance and insurance Consumer banking Corporate banking Investment banking Investment management Private banking Private equity Mortgages Credit cards

Bank of Baroda (BOB) is the third largest bank in India, after the State Bank of India and the Punjab National Bank and ahead of ICICI Bank. BOB has total assets in excess of Rs. 2.27 lakh crores, or Rs. 2,274 billion, a network of over 3,000 branches and offices, and about 1,100 ATMs. IT plans to open 400 new branches in the coming year. It offers a wide range of banking products and financial services to corporate and retail customers through a variety of delivery channels and through its specialized subsidiaries and affiliates in the areas of investment banking, credit cards and asset management. Its total business was Rs. 4,402 billion as of June 30.

As of August 2010, the bank has 78 branches abroad and by the end of FY11 this number should climb to 90. In 2010, BOB opened a branch in Auckland, New Zealand, and its tenth branch in the United Kingdom. The bank also plans to open five branches in Africa. Besides branches, BOB plans to open three outlets in the Persian Gulf region that will consist of ATMs with a couple of people.

The Maharajah of Baroda, Sir Sayajirao Gaekwad III, founded the bank on 20 July 1908 in the princely state of Baroda, in Gujarat. The bank, along with 13 other major commercial banks of India, was nationalized on 19 July 1969, by the government of India.


http://en.wikipedia.org/wiki/Government_of_India

http://en.wikipedia.org/wiki/Gujarat

http://en.wikipedia.org/wiki/Baroda_State

http://en.wikipedia.org/wiki/Princely_state

http://en.wikipedia.org/wiki/Sayajirao_Gaekwad_III

http://en.wikipedia.org/wiki/Crores

http://en.wikipedia.org/wiki/Lakh




Bank of India

Founded-1906

Headquarters-Mumbai, India

Products-Commercial Banking Retail Banking Private Banking Asset Management Mortgages Credit Cards

Bank of India (BOI) is a state-owned commercial bank with headquarters in Mumbai. Government-owned since nationalization in 1969, it is India's 4th largest bank, after State Bank of India, Punjab National Bank and Bank of Baroda. It has 3374 branches, including 27 branches outside India. BOI is a founder member of SWIFT (Society for Worldwide Inter Bank Financial Telecommunications), which facilitates provision of cost-effective financial processing and communication services. The Bank completed its first one hundred years of operations on 7 September 2006.


http://en.wikipedia.org/wiki/SWIFT

http://en.wikipedia.org/wiki/Bank_of_Baroda





http://en.wikipedia.org/wiki/Mumbai

http://en.wikipedia.org/wiki/Commercial_bank

OBJECTIVE OF THE PROJECT

Primary objective

To study the strength of using CAMELSC model framework as a tool of performance evaluation for banking institutions.

Secondary objective: -

1) To evaluate financial performance of the banks.2) To describe CAMELSC model of ranking, banking institutions, so as to analyze the

comparison of various banks.


METHODOLOGY

DATA COLLECTION

Primary Data:- Performance indicators of banks

Source: - Banks

Data collection: - Face to face interaction with employees of the bank.

Secondary Data: - Literature review, ratio analysis and interpretation.

Source: -Journals, internet, banks annual reports and banks prospectus.


DATA INTER PRETATION

1) Capital Adequacy:

Capital Risk Adequacy Ratio:

CRAR =Capital/Total Risk Weighted Credit Exposure

Year SBI BOB BOI PNB IDBI AVG2006 11.88 13.65 10.75 11.95 14.8 12.6062007 12.34 11.8 11.75 12.29 13.73 12.3822008 13.47 12.94 12.04 13.46 11.95 12.7722009 14.25 14.05 13.01 14.03 11.57 13.3822010 13.39 14.36 12.94 14.16 11.31 13.232

AVG 13.066 13.36 12.098 13.178 12.672 12.8748RANK 3 1 5 2 4

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

0 2 4 6 8 10 12 14 16

IDBIPNBBOIBOBSBI


Debt-Equity Ratio:

Debt-Equity Ratio =Borrowings/Share Capital + Reserves

Year SBI BOB BOI PNB IDBI AVg2006 111 61.22 118.26 71.32 74.59 87.2782007 127 13.21 112.31 18.68 510.9 156.422008 105 35.56 67.74 44.22 437.6 138.0242009 93 43.91 70.3 29.86 471.3 141.6742010 156 88.37 157.41 108.67 469.4 195.97

AVG 118.4 48.454 105.204 54.55 392.758143.873

2RANK 2 5 3 4 1

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

0 100 200 300 400 500 600

IDBIPNBBOIBOBSBI


Total Advance to Total Asset Ratio:

Total Advance to Total Asset Ratio =Total Advance/Total Asset

Year SBI BOB BOI PNB IDBI Avg2006 53 52.84 58.05 51.37 59.55 54.9622007 60 58.42 59.97 59.47 60.16 59.6042008 58 59.41 63.45 60 62.9 60.7522009 56 63.32 63.37 62.65 60 61.0682010 60 62.89 61.28 62.9 59.17 61.248

AVG 57.4 59.376 61.224 59.278 60.356 59.5268RANK 5 3 1 4 2

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

0 10 20 30 40 50 60 70

IDBIPNBBOIBOBSBI


6.1.2)

Net NPA ratio:

Net NPA= Net NPA/Total Loan


AVG 1.746 0.518 0.856 0.454 1.074 0.9296 1 4 3 5 2

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

IDBIPNBBOIBOBSBI


Management Quality

Total Advance to Total Deposit Ratio:

Total Advance to Total Deposit = Total Advance/Total Deposit

Year SBI BOB BOI PNB IDBI Avg2006 68.84 63.97 69.38 62.35 59.55 64.8182007 77.45 66.94 71 69.01 60.16 68.9122008 77.55 70.18 75.64 71.79 62.9 71.6122009 73.11 74.84 75.33 73.75 59.17 71.242010 78.58 72.62 73.33 74.84 60 71.874

AVG 75.106 69.71 72.936 70.348 60.356 69.6912RANK 1 4 2 3 5

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

0 10 20 30 40 50 60 70 80 90

IDBIPNBBOIBOBSBI

Business per Employee:


Business per Employee = Total Income/No. of Employees


AVG 4.608 7.112 6.75 5.404 18.722 8.5192RANK 5 2 3 4 1

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

0 5 10 15 20 25 30

IDBIPNBBOIBOBSBI

Profit per Employee:


Profit per Employee = Net Profit/No. of Employees

Year SBI BOB BOI PNB IDBI AVG2006 2.17 2.13 1.66 2.48 12.45 4.1782007 2.37 2.73 2.71 2.68 8.44 3.7862008 3.73 3.94 4.95 3.66 8.86 5.0282009 4.74 6.05 7.49 5.64 8.42 6.4682010 4.46 8 4.39 7.31 8.44 6.52

AVG 3.494 4.57 4.24 4.354 9.322 5.196RANK 5 2 4 3 1

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

0 2 4 6 8 10 12 14

IDBIPNBBOIBOBSBI


Earnings Quality:

Dividend Payout Ratio:

Dividend Payout Ratio= Dividend/Net Profit

Year SBI BOB BOI PNB IDBI Avg2006 19.06 25.11 23.76 14.98 22.07 20.9962007 18.98 24.59 17.51 30.71 20.16 22.392008 22.64 23.75 12.23 23.4 22.92 20.9882009 22.9 17.22 16.34 23.86 24.69 21.0022010 23.36 20.9 24.61 20.74 24.14 22.75

AVG 21.388 22.314 18.89 22.738 22.796 21.6252RANK 4 3 5 2 1

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

0 5 10 15 20 25 30 35

IDBIPNBBOIBOBSBI

Return on Asset:


Return on Asset = Net Profit/Total Asset


AVG 4.66 4.78 5.03 6.1 3.17 4.748RANK 4 3 2 1 5

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

IDBIPNBBOIBOBSBI

Interest Income to Total Income:


Interest Income to Total Income = Interest Income/Total Income

Year SBI BOB BOI PNB IDBI AVG2006 83 85.63 86 87 80.78 84.4822007 84 86.96 85 90 85.84 86.362008 84 85.21 85 88 82.08 84.8582009 83 84.55 84 87 88.74 85.4582010 83 85.61 87 86 86.7 85.662

AVG 83.4 85.592 85.4 87.6 84.828 85.364RANK 5 2 3 1 4

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

76 78 80 82 84 86 88 90 92

IDBIPNBBOIBOBSBI

Other Income to Total Income:


Other Income to Total Income = Other than Interest Income/Total Income

Year SBI BOB BOI PNB IDBI AVG2006 36 14.37 14.42 13.3 19.22 19.4622007 22.5 13.04 15 15.2 14.16 15.982008 15.6 14.79 15 14.3 17.92 15.5222009 11.18 15.45 16 24.6 11.26 15.6982010 12.1 14.39 13 17.5 13.3 14.058

AVG 19.476 14.408 14.684 16.98 15.172 16.144RANK 1 5 4 2 3

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

0 5 10 15 20 25 30 35 40

IDBIPNBBOIBOBSBI

6.1.5) Liquidity:


Liquidity Asset to Total Asset: Liquidity Asset/Total Asset

Year SBI BOB BOI PNB IDBI AVG2006 9.02 11.87 10.9 17 6.05 10.9682007 9.17 12.77 12.27 9 6.66 9.9742008 9.35 12.42 9.9 9 6.7 9.4742009 10.83 10.59 9.65 11.38 6.51 9.7922010 9.13 12.74 11.36 8 6.24 9.494

AVG 9.5 12.078 10.816 10.876 6.432 9.9404RANK 4 1 3 2 5

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

0 2 4 6 8 10 12 14 16 18

IDBIPNBBOIBOBSBI

Liquidity Asset to Total Deposit:


Liquidity Asset to Total Deposit =Liquidity Asset/Total Deposit

Year SBI BOB BOI PNB IDBI AVG2006 12 14.37 12 20 20.63 15.82007 20 14.63 15 11.2 15.94 15.3542008 13 14.67 12 11.3 11.2 12.4342009 14 12.52 11 10.2 9.98 11.542010 12 14.71 14 9.41 8.7 11.764

AVG 14.2 14.18 12.8 12.422 13.29 13.3784RANK 1 2 4 5 3

2005-2006

2006-2007

2007-2008

2008-2009

2009-2010

0 5 10 15 20 25

IDBIPNBBOIBOBSBI


Analysis

H1- The financial performance of SBI is slightly greater than other 4 banksH2- The financial performance of each of the 4 banks (other than SBI) is greater than the average performance of top 5 banksH3- The financial performance of SBI is slightly greater than average performance of top 5 nationalized banks in India.

CRARt-Test: Paired Two Sample for Means

SBI BOBMean 13.066 13.36Variance 0.90093 1.04255Observations 5 5Pearson Correlation 0.453977187Hypothesized Mean Difference 0df 4t Stat -0.637466637P(T<=t) one-tail 0.279240937t Critical one-tail 2.131846782P(T<=t) two-tail 0.558481873t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis

Debt equity ratiot-Test: Paired Two Sample for Means

SBI BOBMean 118.4 48.454

Variance 591.8796.325

1Observations 5 5Pearson Correlation 0.506736035Hypothesized Mean Difference 0df 4t Stat 5.943917394P(T<=t) one-tail 0.002009196t Critical one-tail 2.131846782P(T<=t) two-tail 0.004018393t Critical two-tail 2.776445105


As p (cal) is greater than p (tab) so we reject the null hypothesis

Total advance to total asset ratiot-Test: Paired Two Sample for Means


Variance 8.817.8844

3Observations 5 5Pearson Correlation 0.596003065Hypothesized Mean Difference 0df 4t Stat -1.290075051P(T<=t) one-tail 0.133276723t Critical one-tail 2.131846782P(T<=t) two-tail 0.266553445t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis

Total advance to total depositst-Test: Paired Two Sample for Means

SBI BOBMean 75.106 69.71Variance 16.69573 18.9066Observations 5 5Pearson Correlation 0.429065521Hypothesized Mean Difference 0df 4t Stat 2.674298426P(T<=t) one-tail 0.027778474t Critical one-tail 2.131846782P(T<=t) two-tail 0.055556947t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we acceptthe null hypothesis


Dividend payout ratiot-Test: Paired Two Sample for Means


Variance 4.7401210.7520

3Observations 5 5Pearson Correlation -0.724269505Hypothesized Mean Difference 0df 4t Stat -0.407385712P(T<=t) one-tail 0.352292146t Critical one-tail 2.131846782P(T<=t) two-tail 0.704584292t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis

Return on assetst-Test: Paired Two Sample for Means


Other income to total income


t-Test: Paired Two Sample for Means

SBI BOBMean 19.476 14.408Variance 105.10988 0.77622Observations 5 5Pearson Correlation -0.408437001Hypothesized Mean Difference 0df 4t Stat 1.064815765P(T<=t) one-tail 0.173483724t Critical one-tail 2.131846782P(T<=t) two-tail 0.346967448t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis

Interest income to total incomet-Test: Paired Two Sample for Means

SBI BOBMean 83.4 85.592Variance 0.3 0.77622Observations 5 5Pearson Correlation 0.510815283Hypothesized Mean Difference 0df 4t Stat -6.418142387P(T<=t) one-tail 0.001514515t Critical one-tail 2.131846782P(T<=t) two-tail 0.00302903t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis

Liquid assets to total assetst-Test: Paired Two Sample for Means

SBI BOB


Mean 9.5 12.078Variance 0.5669 0.82287Observations 5 5Pearson Correlation -0.879871998Hypothesized Mean Difference 0df 4t Stat -3.580783506P(T<=t) one-tail 0.011575737t Critical one-tail 2.131846782P(T<=t) two-tail 0.023151473t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis

Liquid assets to total depositst-Test: Paired Two Sample for Means

SBI BOBMean 14.2 14.18Variance 11.2 0.8788Observations 5 5Pearson Correlation 0.061358778Hypothesized Mean Difference 0df 4t Stat 0.013077875P(T<=t) one-tail 0.495095972t Critical one-tail 2.131846782P(T<=t) two-tail 0.990191944t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis

Business per employeet-Test: Paired Two Sample for Means

SBI BOBMean 4.608 7.112Variance 1.91837 5.94177


Observations 5 5Pearson Correlation 0.990725156Hypothesized Mean Difference 0df 4t Stat -5.17543197P(T<=t) one-tail 0.003313565t Critical one-tail 2.131846782P(T<=t) two-tail 0.00662713t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis

Profit per employeet-Test: Paired Two Sample for Means


Net npa ratiot-Test: Paired Two Sample for Means

SBI BOBMean 1.746 0.518Variance 0.01408 0.05197Observations 5 5Pearson Correlation 0.238071924


Hypothesized Mean Difference 0df 4t Stat 11.90830745P(T<=t) one-tail 0.000142421t Critical one-tail 2.131846782P(T<=t) two-tail 0.000284843t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we rejectthe null hypothesis

Sbi and boi


SBI BOIMean 13.066 12.098Variance 0.90093 0.87057Observations 5 5Pearson Correlation 0.897834374Hypothesized Mean Difference 0df 4t Stat 5.084605893P(T<=t) one-tail 0.003528991t Critical one-tail 2.131846782P(T<=t) two-tail 0.007057981t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI BOIMean 118.4 105.204Variance 591.8 1392.06533Observations 5 5Pearson Correlation 0.913356077


Hypothesized Mean Difference 0df 4t Stat 1.634615305P(T<=t) one-tail 0.088734443t Critical one-tail 2.131846782P(T<=t) two-tail 0.177468887t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI BOIMean 57.4 61.224Variance 8.8 5.30258Observations 5 5Pearson Correlation 0.33604106Hypothesized Mean Difference 0df 4t Stat -2.77253191P(T<=t) one-tail 0.025100335t Critical one-tail 2.131846782P(T<=t) two-tail 0.050200671t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI BOIMean 75.106 72.936Variance 16.69573 7.39783Observations 5 5Pearson Correlation 0.471107793Hypothesized Mean Difference 0df 4t Stat 1.314685603P(T<=t) one-tail 0.129462983


t Critical one-tail 2.131846782P(T<=t) two-tail 0.258925967t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI BOIMean 21.388 18.89Variance 4.74012 27.29945Observations 5 5Pearson Correlation -0.196219439Hypothesized Mean Difference 0df 4t Stat 0.924503536P(T<=t) one-tail 0.203774149t Critical one-tail 2.131846782P(T<=t) two-tail 0.407548298t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis




Other income to total incomet-Test: Paired Two Sample for Means

SBI BOIMean 19.476 14.684Variance 105.10988 1.20928Observations 5 5Pearson Correlation -0.069360217Hypothesized Mean Difference 0df 4t Stat 1.031632612P(T<=t) one-tail 0.180267077t Critical one-tail 2.131846782P(T<=t) two-tail 0.360534154t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI BOIMean 83.4 85.4Variance 0.3 1.3Observations 5 5Pearson Correlation -0.320256308Hypothesized Mean Difference 0df 4t Stat -3.16227766P(T<=t) one-tail 0.017054712t Critical one-tail 2.131846782P(T<=t) two-tail 0.034109423t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we rejectthe null hypothesis


SBI BOI


Mean 9.5 10.816Variance 0.5669 1.15393Observations 5 5Pearson Correlation -0.659863706Hypothesized Mean Difference 0df 4t Stat -1.762286822P(T<=t) one-tail 0.076404224t Critical one-tail 2.131846782P(T<=t) two-tail 0.152808449t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI BOIMean 14.2 12.8Variance 11.2 2.7Observations 5 5Pearson Correlation 0.600099198Hypothesized Mean Difference 0df 4t Stat 1.158648244P(T<=t) one-tail 0.155530384t Critical one-tail 2.131846782P(T<=t) two-tail 0.311060767t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI BOIMean 4.608 6.75Variance 1.91837 6.40385Observations 5 5Pearson Correlation 0.998298188Hypothesized Mean Difference 0df 4


t Stat -4.1622925P(T<=t) one-tail 0.007059474t Critical one-tail 2.131846782P(T<=t) two-tail 0.014118947t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis




SBI BOIMean 1.746 0.856Variance 0.01408 0.25173Observations 5 5Pearson Correlation 0.444784009Hypothesized Mean Difference 0df 4t Stat 4.313583225P(T<=t) one-tail 0.006255295t Critical one-tail 2.131846782P(T<=t) two-tail 0.01251059t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis


Sbi and pnb


SBI PNBMean 13.066 13.178Variance 0.90093 1.01657Observations 5 5Pearson Correlation 0.925272154Hypothesized Mean Difference 0df 4t Stat -0.654266328P(T<=t) one-tail 0.274324768t Critical one-tail 2.131846782P(T<=t) two-tail 0.548649535t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI PNBMean 118.4 54.55Variance 591.8 1303.2923Observations 5 5Pearson Correlation 0.674048743Hypothesized Mean Difference 0df 4t Stat 5.353830214P(T<=t) one-tail 0.002935271t Critical one-tail 2.131846782P(T<=t) two-tail 0.005870543t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis



SBI PNBMean 57.4 59.278Variance 8.8 21.89597Observations 5 5Pearson Correlation 0.728041043Hypothesized Mean Difference 0df 4t Stat -1.296933491P(T<=t) one-tail 0.132203114t Critical one-tail 2.131846782P(T<=t) two-tail 0.264406227t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI PNBMean 75.106 70.348Variance 16.69573 24.89732Observations 5 5Pearson Correlation 0.727359985Hypothesized Mean Difference 0df 4t Stat 3.079767125P(T<=t) one-tail 0.018469983t Critical one-tail 2.131846782P(T<=t) two-tail 0.036939966t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis


SBI PNBMean 21.388 22.738Variance 4.74012 32.35712Observations 5 5Pearson Correlation -0.051490036


Hypothesized Mean Difference 0df 4t Stat -0.48731318P(T<=t) one-tail 0.325768639t Critical one-tail 2.131846782P(T<=t) two-tail 0.651537278t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI PNBMean 0.932 1.22Variance 0.00767 0.0338Observations 5 5Pearson Correlation 0.37885568Hypothesized Mean Difference 0df 4t Stat -3.764143128P(T<=t) one-tail 0.009852033t Critical one-tail 2.131846782P(T<=t) two-tail 0.019704066t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis


SBI PNBMean 19.476 16.98Variance 105.10988 20.557Observations 5 5Pearson Correlation -0.660737698Hypothesized Mean Difference 0df 4t Stat 0.408037014P(T<=t) one-tail 0.352071546t Critical one-tail 2.131846782P(T<=t) two-tail 0.704143092


t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis




SBI PNBMean 9.5 10.876Variance 0.5669 13.26688Observations 5 5Pearson Correlation -0.027767212Hypothesized Mean Difference 0df 4t Stat -0.822726397P(T<=t) one-tail 0.228440649t Critical one-tail 2.131846782P(T<=t) two-tail 0.456881299t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis



SBI PNBMean 14.2 12.422Variance 11.2 18.54692Observations 5 5Pearson Correlation -0.266119731Hypothesized Mean Difference 0df 4t Stat 0.649945495P(T<=t) one-tail 0.275583421t Critical one-tail 2.131846782P(T<=t) two-tail 0.551166841t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis




SBI PNB


Mean 3.494 4.354Variance 1.38943 4.29688Observations 5 5Pearson Correlation 0.885734269Hypothesized Mean Difference 0df 4t Stat -1.650249308P(T<=t) one-tail 0.087118366t Critical one-tail 2.131846782P(T<=t) two-tail 0.174236733t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI PNBMean 1.746 0.454Variance 0.01408 0.04563Observations 5 5Pearson Correlation -0.638339847Hypothesized Mean Difference 0df 4t Stat 9.521128888P(T<=t) one-tail 0.000339692t Critical one-tail 2.131846782P(T<=t) two-tail 0.000679384t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis

Sbi and idbi



SBI IDBIMean 13.066 12.672Variance 0.90093 2.30962Observations 5 5Pearson Correlation -0.923684643Hypothesized Mean Difference 0df 4t Stat 0.363465542P(T<=t) one-tail 0.367326063t Critical one-tail 2.131846782P(T<=t) two-tail 0.734652126t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI IDBIMean 118.4 392.758Variance 591.8 32310.51382Observations 5 5Pearson Correlation 0.209039728Hypothesized Mean Difference 0df 4t Stat -3.480191113P(T<=t) one-tail 0.012673793t Critical one-tail 2.131846782P(T<=t) two-tail 0.025347586t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis


SBI IDBIMean 57.4 60.356Variance 8.8 2.17333Observations 5 5Pearson Correlation 0.113073835


Hypothesized Mean Difference 0df 4t Stat -2.09184725P(T<=t) one-tail 0.052306053t Critical one-tail 2.131846782P(T<=t) two-tail 0.104612107t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI IDBIMean 75.106 60.356Variance 16.69573 2.17333Observations 5 5Pearson Correlation 0.495499413Hypothesized Mean Difference 0df 4t Stat 9.183109066P(T<=t) one-tail 0.000390469t Critical one-tail 2.131846782P(T<=t) two-tail 0.000780937t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis


SBI IDBIMean 21.388 22.796Variance 4.74012 3.22113Observations 5 5Pearson Correlation 0.876965199Hypothesized Mean Difference 0df 4t Stat -2.991319879P(T<=t) one-tail 0.020142785t Critical one-tail 2.131846782P(T<=t) two-tail 0.04028557


t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis




SBI IDBIMean 19.476 15.172Variance 105.10988 10.94252Observations 5 5Pearson Correlation 0.733024067Hypothesized Mean Difference 0df 4t Stat 1.181662607P(T<=t) one-tail 0.151396099t Critical one-tail 2.131846782P(T<=t) two-tail 0.302792198t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis



SBI IDBIMean 83.4 84.828Variance 0.3 10.94252Observations 5 5Pearson Correlation -0.239535798Hypothesized Mean Difference 0df 4t Stat -0.917554383P(T<=t) one-tail 0.205385317t Critical one-tail 2.131846782P(T<=t) two-tail 0.410770634t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis




SBI IDBIMean 14.2 13.29Variance 11.2 24.3226


Observations 5 5Pearson Correlation 0.189185757Hypothesized Mean Difference 0df 4t Stat 0.376061313P(T<=t) one-tail 0.362983344t Critical one-tail 2.131846782P(T<=t) two-tail 0.725966688t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI IDBIMean 4.608 18.722Variance 1.91837 14.62247Observations 5 5Pearson Correlation 0.878379693Hypothesized Mean Difference 0df 4t Stat -11.73202373P(T<=t) one-tail 0.000150967t Critical one-tail 2.131846782P(T<=t) two-tail 0.000301934t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis


SBI IDBIMean 3.494 9.322Variance 1.38943 3.09182Observations 5 5Pearson Correlation -0.631443615Hypothesized Mean Difference 0df 4t Stat -4.891172647


P(T<=t) one-tail 0.004047606t Critical one-tail 2.131846782P(T<=t) two-tail 0.008095212t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis


SBI IDBIMean 1.746 1.074Variance 0.01408 0.02098Observations 5 5Pearson Correlation -0.215567926Hypothesized Mean Difference 0df 4t Stat 7.291437285P(T<=t) one-tail 0.000940333t Critical one-tail 2.131846782P(T<=t) two-tail 0.001880667t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis

Bob and avg(h2)


BOB AvgMean 13.36 12.8748

Variance 1.042550.17762

9Observations 5 5Pearson Correlation 0.83723


3Hypothesized Mean Difference 0df 4

t Stat1.53495

2

P(T<=t) one-tail0.09979

4

t Critical one-tail2.13184

7

P(T<=t) two-tail0.19958

8

t Critical two-tail2.77644

5 As p (cal) is greater than p (tab) so we accept the null hypothesis


BOB Avg

Mean 48.454143.873

2

Variance796.325

11528.39

1Observations 5 5

Pearson Correlation0.22665

8Hypothesized Mean Difference 0df 4t Stat -4.995


8


7


7


5 As p (cal) is greater than p (tab) so we reject the null hypothesis



BOB AvgMean 59.376 59.5268

Variance17.8844

36.92057

5Observations 5 5




6


7


1




BOB AvgMean 69.71 69.6912

Variance 18.90668.80202

5Observations 5 5



t Stat0.01871

9


1


7


2





BOB AvgMean 22.314 21.6252

Variance10.7520

30.76009

7Observations 5 5



t Stat0.46049

4


2


7


4




BOB AVGMean 0.956 0.9496

Variance 0.034680.01499

9Observations 5 5



t Stat0.09967

7


8



7


6





Variance 0.776223.99330

4Observations 5 5Pearson Correlation -0.08044Hypothesized Mean Difference 0df 4t Stat -1.72691


9


7


7



Interest income to total income BOB AVG

Mean 85.592 85.364

Variance 0.776220.53090

4Observations 5 5


9Hypothesized Mean 0


Differencedf 4

t Stat0.66246

4


8


7


6





Variance 0.822870.37397

9Observations 5 5Pearson Correlation -0.19139Hypothesized Mean Difference 0df 4

t Stat4.02648

1P(T<=t) one-tail 0.00789


7


9






Variance 0.87884.16125

9Observations 5 5



t Stat0.95825

7


9


7


8





Variance 5.941775.48526

5Observations 5 5




4


7


9


5


As p (cal) is greater than p (tab) so we reject the null hypothesis



Variance 5.922851.60590

2Observations 5 5




5


7P(T<=t) two-tail 0.34655



Net Npa ratiot-Test: Paired Two Sample for Means


Variance 0.051970.01953

1Observations 5 5




t Stat -5.73297


2


7


5



Boi and avg


BOI AvgMean 12.098 12.8748

Variance 0.870570.17762

9Observations 5 5




6


7


3




BOI Avg


Mean 105.204143.873

2

Variance1392.06

51528.39

1Observations 5 5


1Hypothesized Mean Difference 0df 4t Stat -2.07438P(T<=t) one-tail 0.05335






BOI AvgMean 61.224 59.5268

Variance 5.302586.92057

5Observations 5 5



t Stat2.70959








BOI AvgMean 72.936 69.6912

Variance 7.397838.80202

5Observations 5 5



t Stat5.26349







BOI AvgMean 18.89 21.6252

Variance27.2994

50.76009

7Observations 5 5Pearson Correlation 0.44713Hypothesized Mean Difference 0df 4t Stat -1.24881


6


7


2t Critical two-tail 2.77644


5As p (cal) is greater than p (tab) so we accept the null hypothesis


BOI AVGMean 1.006 0.9496

Variance 0.130480.01499

9Observations 5 5Pearson Correlation 0.85611Hypothesized Mean Difference 0df 4

t Stat0.47757

9


8


7


5





Variance 1.209283.99330

4Observations 5 5


5Hypothesized Mean Difference 0


df 4t Stat -1.57403


7


7


5





Variance 1.30.53090


t Stat0.05662

6


9


7


9






Variance 1.153930.37397

9Observations 5 5



t Stat1.72946

6


1


7


2



Pnb and avg


PNB AvgMean 13.178 12.8748

Variance 1.016570.17762

9Observations 5 5



t Stat1.02984

6


9




8




PNB Avg

Mean 54.55143.873

2

Variance1303.29

21528.39

1Observations 5 5




3


7


6




PNB AvgMean 59.278 59.5268

Variance21.8959

76.92057

5Observations 5 5Pearson Correlation 0.98354Hypothesized Mean Difference 0


df 4t Stat -0.25933


9


7


8




PNB AvgMean 70.348 69.6912

Variance24.8973

28.80202

5Observations 5 5



t Stat0.67257

8


5






PNB Avg


Mean 22.738 21.6252

Variance32.3571

20.76009

7Observations 5 5



t Stat0.45959

7


7


7


5




PNB AVGMean 1.22 0.9496

Variance 0.03380.01499

9Observations 5 5



t Stat4.62120

3


6


7


2






Variance 20.5573.99330


t Stat0.33088



7


9





Variance 2.30.53090

4Observations 5 5



t Stat3.79156



1


7


3


5 As p (cal) is greater than p (tab) so we rejectthe null hypothesis



Variance13.2668

80.37397

9Observations 5 5



t Stat0.67933

3


2


7


5




PNB AVGMean 12.422 13.3784

Variance18.5469

24.16125

9


Observations 5 5




2


7


4





Variance 3.684235.48526

5Observations 5 5


6Hypothesized Mean Difference 0df 4t Stat -13.8338P(T<=t) one-tail 7.91E-05


7


8






Variance 4.296881.60590

2Observations 5 5




3


7


6





Variance 0.045630.01953

1Observations 5 5




6t Critical one-tail 2.13184


7


3



Idbi and avg


IDBI AvgMean 12.672 12.8748

Variance 2.309620.17762



2


7


5




IDBI Avg

Mean 392.758143.873

2

Variance32310.5

11528.39

1Observations 5 5


4


Hypothesized Mean Difference 0df 4

t Stat3.72546

4


9


7


7





Variance 2.173336.92057

5Observations 5 5



t Stat0.70088

2


3


7


5






Variance 2.173338.80202

5Observations 5 5




6


7


3





Variance 3.221130.76009


t Stat1.21607

3


6


7


2





IDBI AVGMean 0.634 0.9496

Variance 0.003930.01499



3


7


7





Variance10.9425

23.99330

4Observations 5 5


7Hypothesized Mean Difference 0


df 4t Stat -0.87522


2


7


4





Variance10.9425

20.53090

4Observations 5 5




6


7


1






Variance 0.078170.37397



1


7


2





Variance 24.32264.16125

9Observations 5 5




2


7


3






Variance14.6224

75.48526

5Observations 5 5


6Hypothesized Mean Difference 0df 4t Stat 12.5014


8


7


6





Variance 3.091821.60590


t Stat3.54145

2



1


7


2





Variance 0.020980.01953

1Observations 5 5



t Stat1.81734

3


9


7


9



Sbi and avg(h3)


SBI AvgMean 13.066 12.8748Variance 0.90093 0.1776292Observations 5 5


Pearson Correlation 0.844476941Hypothesized Mean Difference 0df 4t Stat 0.673547487P(T<=t) one-tail 0.268757196t Critical one-tail 2.131846782P(T<=t) two-tail 0.537514393t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI AvgMean 118.4 143.8732Variance 591.8 1528.391261Observations 5 5Pearson Correlation 0.688653891Hypothesized Mean Difference 0df 4t Stat -2.000994987P(T<=t) one-tail 0.057992344t Critical one-tail 2.131846782P(T<=t) two-tail 0.115984688t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI AvgMean 57.4 59.5268Variance 8.8 6.9205752Observations 5 5Pearson Correlation 0.747650547Hypothesized Mean Difference 0df 4


t Stat -2.36271001P(T<=t) one-tail 0.038716857t Critical one-tail 2.131846782P(T<=t) two-tail 0.077433714t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI AvgMean 75.106 69.6912Variance 16.69573 8.8020252Observations 5 5Pearson Correlation 0.781500215Hypothesized Mean Difference 0df 4t Stat 4.730859344P(T<=t) one-tail 0.004549159t Critical one-tail 2.131846782P(T<=t) two-tail 0.009098318t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis


SBI AvgMean 21.388 21.6252Variance 4.74012 0.7600972Observations 5 5Pearson Correlation 0.013327754Hypothesized Mean Difference 0df 4t Stat -0.227204291P(T<=t) one-tail 0.415702448t Critical one-tail 2.131846782P(T<=t) two-tail 0.831404896


t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI AVGMean 0.932 0.9496Variance 0.00767 0.0149988Observations 5 5Pearson Correlation 0.873695299Hypothesized Mean Difference 0df 4t Stat -0.628026947P(T<=t) one-tail 0.282029726t Critical one-tail 2.131846782P(T<=t) two-tail 0.564059452t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis


SBI AVGMean 19.476 16.144Variance 105.10988 3.993304Observations 5 5Pearson Correlation 0.925297088Hypothesized Mean Difference 0df 4t Stat 0.88304506P(T<=t) one-tail 0.213544322t Critical one-tail 2.131846782P(T<=t) two-tail 0.427088644t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis



SBI AVGMean 83.4 85.364Variance 0.3 0.530904Observations 5 5Pearson Correlation 0.306949876Hypothesized Mean Difference 0df 4t Stat -5.73737523P(T<=t) one-tail 0.002285914t Critical one-tail 2.131846782P(T<=t) two-tail 0.004571827t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis


SBI AVGMean 9.5 9.9404Variance 0.5669 0.3739788Observations 5 5Pearson Correlation -0.253331624Hypothesized Mean Difference 0df 4t Stat -0.908797334P(T<=t) one-tail 0.207430807t Critical one-tail 2.131846782P(T<=t) two-tail 0.414861614t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis



SBI AVGMean 14.2 13.3784Variance 11.2 4.1612588Observations 5 5Pearson Correlation 0.409543709Hypothesized Mean Difference 0df 4t Stat 0.587773741P(T<=t) one-tail 0.294132308t Critical one-tail 2.131846782P(T<=t) two-tail 0.588264616t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we accept the null hypothesis







SBI AVGMean 1.746 0.9296Variance 0.01408 0.0195308Observations 5 5Pearson Correlation 0.327022972Hypothesized Mean Difference 0df 4t Stat 12.09918392P(T<=t) one-tail 0.000133836t Critical one-tail 2.131846782P(T<=t) two-tail 0.000267672t Critical two-tail 2.776445105 As p (cal) is greater than p (tab) so we reject the null hypothesis


final project

Documents

total capital

equity capital

capital risk adequacy

minimum capital

capitaladequacy ratios

ratio of capital fund

c capital adequacy

indicator of capital