Grand project

“A Study on Impact of NPA on Profitability and Liquidity In Public Sector Banks”

Table of Contents

Chapter - 1. INTRODUCTION TO TOPIC...............................................................................2

What is an NPA?.............................................................................................................................................2

Chapter – 2. LITERATURE REVIEW.......................................................................................5

Chapter – 3. INTRODUCTION OF BANKING INDUSTRY...................................................8

History of Banking In India.........................................................................................................................8

Reserve Bank Of India (RBI)...................................................................................................................11

Structure Of Indian Banking Industry...................................................................................................12

Aggregate Performance of the Banking Industry:.............................................................................18

Challenges facing by banking industry.................................................................................................20

Classification of Assets..............................................................................................................................23

Categories of NPAs.....................................................................................................................................23

Reporting Format For NPA – Gross And Net Npa...........................................................................25

Types Of Npa:...............................................................................................................................................26

Impact Of Npa:..............................................................................................................................................26

Procedures for NPA Identification in India.........................................................................................27

Chapter – 4. RESEARCH METHODOLOGY..............................................................32

Scope of the study:-.....................................................................................................................................32

Research objective:-....................................................................................................................................32

Methodology:-...............................................................................................................................................32

Tools and techniques:.................................................................................................................................32

Limitation........................................................................................................................................................33

Tools and techniques:.................................................................................................................................33

Chapter – 5. DATA BASE AND METHODOLOGY.....................................................35

Hypothesis of the Study.............................................................................................................................35

Chapter – 6. FINDING................................................................................................................50

Chapter – 7. CONCLUSION......................................................................................................51

Chapter – 8. REFERENCES......................................................................................................52

S.K.Patel Institute of Management and Computer Studies (MBA)


Chapter - 1. INTRODUCTION TO TOPIC

What is an NPA?An asset becomes non-performing when it ceases to generate income to the Bank. Thus, a

non-performing asset (NPA) is defined as a credit facility in respect of which the interest and

or instalments of principal has remained ‘overdue’ for a ‘specified period’ of time. The

concept of ‘specified period’ is reduced in a phased manner. The shortening of the period is

from 4 quarters in 1993 when the concept of IRAC norms was first introduced in India to the

present level of 90 days.

Thus from 31.3.2004 an advance or loan (other than direct agricultural advance) shall be

classified as an NPA where -

Interest and / or instalment of principal remain overdue for a period of more than 90 days

in respect of a term loan.

The account remains out of order in respect of an overdraft / cash credit for more than 90

days.

The bills remain overdue for a period of more than 90 days in the case of bills purchased

and discounted.

Any amount to be received remains overdue for a period more than 90 days in respect of

any other accounts.

In case of direct agricultural advances, w.e.f. 30.9.2004, a loan granted for short duration

crops will be treated as NPA, if the instalment of principal or interest thereon remains

overdue for 2 crop seasons. In the case of long duration crops, the loan will be treated as NPA

if the instalment of principal or interest thereon remains overdue for 1 crop season.

Explanation of some terms used in NPA management

Security Interest:

Security Interest means right, title and interest of any kind whatsoever upon property, created

in favour of any secured creditor and includes mortgage, charge, hypothecation and

assignment



Wilful defaulters:

"A Wilful Default” would be deemed to have occurred if any of the following events is noted

The unit has defaulted in meeting its payment / repayment obligations to the lender even

when it has the capacity to honour the said obligations.

The unit has defaulted in meeting its payment / repayment obligations to the lender and

has not utilised the finance from the lender for the specific purposes for which finance

was availed of but has diverted the funds for other purposes.

The unit has defaulted in meeting its payment/repayment obligations to the lender and has

siphoned off the funds so that the funds have not been utilised for the specific purpose for

which finance was availed of, nor are the funds available with the unit in the form of

other assets.”

Factors contributing to NPAs:

According to a recent study conducted by the RBI, the underlying reasons for NPAs in India

can be classified into two heads, namely:

1. Internal Factors

2. External Factors

Internal Factors:

Diversion of funds for expansion/diversification/modernisation or for taking up new

projects

Diversion of funds for assisting or promoting associate concerns

Time or cost overrun during the project implementation stage

Business failures due to product failure, failure in marketing, etc

Inefficiency in management

Slackness in credit management & monitoring

Inappropriate technology or problems related to modern technology



External Factors:

Recession in the economy as a whole

Input or power shortage

Price escalation of inputs

Exchange rate fluctuation

Accidents & natural calamities

Changes in government policies relating to excise & import duties, pollution control

orders, etc

Government loan waiver scheme

Other Factors:

Apart from the above factors, there are certain other factors which are responsible for

standard assets becoming NPAs. They are :

Liberalisation of the economy & the consequent pressures from liberalisation like

severe competition, reduction of tariffs, removal of restrictions

Poor monitoring of credits & the failure to recognise early warning signals shown by

standard assets

Promoters’ over-optimism in setting up large projects

Sudden crashing of capital markets & the failure to raise adequate funds

Granting of loans to certain sectors on the basis of the Government’s directives rather

than commercial imperatives

Mismatch of funding i.e. using loans granted for short term for long term transactions

High leveraging & high cost of borrowing



Chapter – 2. LITERATURE REVIEW

There is several research paper studies for carried out or find out the impact of NPA on

profitability and liquidity in public sector banks.

Dr. A. Shyamala (June -2012), “NPAs in Indian banking sector: impact on profitability”

using secondary data for years 10 year, The data has been analyzed using ratio. Like Gross

NPA to Gross Advances, Net NPA to Net Advances, Gross NPA to Total Assets, Net NPA to

Total Assets and covered Area under study of SBI Group, Nationalized Banks Group and

Private Banks Group and

Shahbaz Haneef, Tabassum Riaz, Muhammad Ramzan, “Impact of Risk Management on

Non-Performing Loans and Profitability of Banking Sector of Pakistan” (April 2012,)using

secondary data for the years 10 year and covered Area under study 5 banks.

Mahipal Singh Yadav, ( June, 2011) “Impact of Non Performing Assets on Profitability and

Productvity of Public Sector Banks in India” has conclude that non-performing assets in

public sector banks affects fifty percent profitability.

Siraj K.K Prof. (Dr). P. Sudarsanan Pillai, (March|2012) “A Study on the Performance of

Non-Performing Assets (NPAs) of Indian Banking During Post Millennium Period” has

conclude that NPA remained as an area of concern as it indicates the real efficiency of credit

risk management)

Anshu bansal (January 15, 2012 “A study on recent trends in risk management of

nonperforming assets (npas) by public sector banks in india” Types of data: Primary and

secondary data years :2007-2011 Area under study: all Public Sector Banks in India. Scope:

30% banks as sample, based at Dehradun and nearby surrounding towns and cities The

research work has been divided into three major steps, (1)namely: Theoretical study of NPAs;

(2)Historical study of NPAs and (3)analyzing the recent trends of NPAs. (4)Mathematical

and statistical tools such as percentage, trend analysis conclude that NPA shows the actual

burden of banks.



Dr.Hosmani ,Mr.Jagadish Hudagi (December 2011,) “Unearthing the epidemic of non-per

forming assets -a study with reference to public sector banks in india” Types of data:

secondary data years : 2005-2010. Area under study: Nonperforming assets in Commercial

banks operating in India wise public sector banks has been taken in to account Scope: Indian

banking sector for 5 year The study conducted on the topic unearthing the epidemic of non

performing assets with reference to public sector banks in India, found that there is a slight

improvement in the asset quality reflected by decline in the diverse NPA percentage.

Neha Kalra, Shaveta Gupta ,Rajesh Bagga “Non-Performing Assets: A Brunt on Financial

Performance of Banks” Types of data: secondary data years : (1998-2009 Area under study:

public sector: private sector: foreign banks: Scope: Indian & foreign banking sector for 10

year The money locked up in NPAs is not available for productive use and adverse effect on

banks' profitability is there)

Dr. Dhirajjain Ms. Nasreen Sheikh (September 2012, ) “A comparative study of loan

performance, npa and Net profit in selected indian private banks” Types of data: secondary

years : 2001-2011. Area under study: Axis, ICICI Bank, IDBI Bank, HDFC Bank, Induslnd

Bank, Kotak Mahindra Bank,Yes Bank,South Indian Bank, ING Vysya Bank, CITI Union

Bank Scope: Indian banking sector for 10 year The overall performance shows that it is the

moderately correlated.

P.Malyadri2.S.Sirisha“Asset Quality and Non Performing Assets of Indian Commercial

Banks” Types of data: secondary data years : 1996-2010, Area under study: NPA’s of Indian

Scheduled Commercial Banks. Scope: Indian banking sector for 14 year The asset quality of

banks in India has been improving over the past few years as reflected in the declining NPA

to advances ratio.

Ms. Rajni Saluja, Dr. Roshan Lal (NOVEMBER-2007) “Comparative Analysis On Non‐Performing Assets NPAS Of Public Sector, Private Sector And Foreign Banks In India”

Types of data: secondary data years: 2004‐2009 Area under study: public sector, private

sector and foreign banks are selected Scope: Indian banking sector for 5 year It can be

concluded that NPAs are not confined to PSBs alone but are present in private banks and

foreign banks as well. There is more of NPAs in non‐priority sector than priority sector.



Chandan Chatterjee Jeet Mukherjee 3.Dr. Ratan Das (November 2012,) Management Of

Non Performing Assets - A Current Scenario” Types of data: secondary data years :2005-

2011 Area under study: study of NPA‟s of public sector banks, private sector banks and

foreign sector banks Scope: Indian banking sector for 6 year The NPAs have a negative

influence on the achievement of capital adequacy level, funds mobilization and deployment

policy, banking system credibility, productivity and overall economy.



Chapter – 3. INTRODUCTION OF BANKING INDUSTRY

Definition of Bank

“An organization, usually a corporation, chartered by a state or federal government, which

does most or all of the following: receives demand deposits and time deposits, honors

instruments drawn on them, and pays interest on them; discounts notes, makes loans, and

invests in securities; collects checks, drafts, and notes; certifies depositor's checks; and issues

drafts and cashier's checks.”

Definition of banking

In general terms, “The business activity of accepting and safeguarding money owned by other

individuals and entities, and then lending out this money in order to earn a profit” So we can

say that Banking is a company, which transacts the business of banking. The Banking

Regulations Acts defines the business as banking by stating the essential function of a banker.

The term banking is defined as “Accepting for the purpose of leading or investment, deposits

of money from the public, repayable on demand or otherwise and withdrawal by cheque,

draft, order or otherwise.”

History of Banking In India

Without a sound and effective banking system in India it cannot have a healthy economy. The

banking system of India should not only be hassle free but it should be able to meet new

challenges posed by the technology and any other external and internal factors.

For the past three decades India's banking system has several outstanding achievements to its

credit. The most striking is its extensive reach. It is no longer confined to only metropolitans

or cosmopolitans in India. In fact, Indian banking system has reached even to the remote

corners of the country. This is one of the main reasons of India's growth process.

The government's regular policy for Indian bank since 1969 has paid rich dividends with the

nationalization of 14 major private banks of India. Not long ago, an account holder had to

wait for hours at the bank counters for getting a draft or for withdrawing his own money.



Today, he has a choice. Gone are days when the most efficient bank transferred money from

one branch to other in two days. Now it is simple as instant messaging or dials a pizza.

Money has become the order of the day. The first bank in India, though conservative, was

established in 1786. From 1786 till today, the journey of Indian Banking System can be

segregated into three distinct phases. They are as mentioned below:

PHASE I

The General Bank of India was set up in the year 1786. Next were Bank of Hindustan and

Bengal Bank. The East India Company established Bank of Bengal (1809), Bank of Bombay

(1840) and Bank of Madras (1843) as independent units and called it Presidency Banks.

These three banks were amalgamated in 1920 and Imperial Bank of India was established

which started as private shareholders banks, mostly Europeans shareholders.

In 1865 Allahabad Bank was established and first time exclusively by Indians, Punjab

National Bank Ltd. was set up in 1894 with headquarters at Lahore.

Between 1906 and 1913, Bank of India, Central Bank of India, Bank of Baroda, Canara

Bank, Indian Bank, and Bank of Mysore were set up. Reserve Bank of India came in 1935.

During the first phase the growth was very slow and banks also experienced periodic failures

between 1913 and 1948. There were approximately 1100 banks, mostly small.

To streamline the functioning and activities of commercial banks, the Government of India

came up with The Banking Companies Act, 1949 which was later changed to Banking

Regulation Act 1949 as per amending Act of 1965 (Act No. 23 of 1965).

PHASE IIGovernment took major steps in this Indian Banking Sector Reform after independence. In

1955, it nationalized Imperial Bank of India with extensive banking facilities on a large scale

especially in rural and semi-urban areas. It formed State Bank of India to act as the principal

agent of RBI and to handle banking transactions of the Union and State Governments all over

the country.



Seven banks forming subsidiary of State Bank of India was nationalized in 1960 on 19th July,

1969, major process of nationalization was carried out. It was the effort of the then City

Minister of India, Mrs. Indira Gandhi. 14 major commercial banks in the country were

nationalized.

Second phase of nationalization Indian Banking Sector Reform was carried out in 1980 with

seven more banks. This step brought 80% of the banking segment in India under Government

ownership. The following are the steps taken by the Government of India to Regulate

Banking Institutions in the Country:

©. 1949: Enactment of Banking Regulation Act.

©. 1955: Nationalization of State Bank of India.

©. 1959: Nationalization of SBI subsidiaries.

©. 1961: Insurance cover extended to deposits.

©. 1969: Nationalization of 14 major banks.

©. 1971: Creation of credit guarantee corporation.

©. 1975: Creation of regional rural banks.

©. 1980: Nationalization of seven banks with deposits over 200 crore.

Banking in the sunshine of Government ownership gave the public implicit faith and

immense confidence about the sustainability of these institutions.

PHASE III

This phase has introduced many more products and facilities in the banking sector in its

reforms measure. In 1991, under the chairmanship of M Narasimham, a committee was set up

by his name which worked for the liberalization of banking practices.

The country is flooded with foreign banks and their ATM stations. Efforts are being put to

give a satisfactory service to customers. Phone banking and net banking is introduced.



The entire system became more convenient and swift. Time is given more importance than

money. The financial system of India has shown a great deal of resilience. It is sheltered from

any crisis triggered by any external macroeconomics shock as other East Asian Countries

suffered.

Reserve Bank Of India (RBI)

The central bank of the country is the Reserve Bank of India (RBI). It was established in

April 1935 with a share capital of Rs. 5 crores on the basis of the recommendations of the

Hilton Young Commission.

The share capital was divided into shares of Rs. 100 each fully paid which was entirely

owned by private shareholders in the beginning. The Government held shares of nominal

value of Rs. 2, 20,000Reserve Bank of India was nationalized in the year 1949.

The general superintendence and direction of the Bank is entrusted to Central Board of

Directors of 20 members, the Governor and four Deputy Governors, one Government official

from the Ministry of Finance, ten nominated Directors by the Government to give

representation to important elements in the economic life of the country, and four nominated

Directors by the Central Government to represent the four local Boards with the headquarters

at Mumbai, Kolkata, Chennai and New Delhi. Local Boards consist of five members each

Central Government appointed for a term of four years to represent territorial and economic

interests and the interests of co-operative and indigenous banks.

The Reserve Bank of India Act, 1934 was commenced on April 1, 1935. The Act, 1934 (II of

1934) provides the statutory basis of the functioning of the Bank.

The Bank was constituted for the need of following:

To regulate the issue of banknotes to maintain reserves with a view to securing monetary

stability and

To operate the credit and currency system of the country to it



Structure Of Indian Banking Industry

Banking Industry in India functions under the sunshade of Reserve Bank of India - the

regulatory, central bank. Banking Industry mainly consists of:

• Commercial Banks

• Co-operative Banks

The commercial banking structure in India consists of: Scheduled Commercial Banks

Unscheduled Bank. Scheduled commercial Banks constitute those banks which have been

included in the Second Schedule of Reserve Bank of India (RBI) Act, 1934. RBI in turn

includes only those banks in this schedule which satisfy the criteria laid down vide section 42

(60) of the Act. Some co-operative banks are scheduled commercial banks although not all

co-operative banks are. Being a part of the second schedule confers some benefits to the bank

in terms of access to accommodation by RBI during the times of liquidity constraints. At the

same time, however, this status also subjects the bank certain conditions and obligation

towards the reserve regulations of RBI.

For the purpose of assessment of performance of banks, the Reserve Bank of India categorize

them as public sector banks, old private sector banks, new private sector banks and foreign

banks.



Sr.No.Nationalized

Banks

Old Private

Sector

Banks

New Private Sector

BanksForeign Banks

1Allahabad Bank

Ltd.

Catholic Syrian

Bank

Ltd.

Axis Bank Ltd.

Abu Dhabi

Commercial

Bank

2 Andhra Bank Ltd.City Union Bank

Ltd.

Development Credit

Bank Ltd.

American

Express Bank

3Bank of Baroda

Ltd.

Dhanalakshmi

Bank Ltd.HDFC Bank Ltd.

Bank

Internasional

Indonesia

4 Bank of India Ltd. Federal Bank Ltd ICICI Bank Ltd.Bank of

America NA

5Bank of

Maharashtra Ltd.

ING Vysya Bank

Ltd.IndusInd Bank Ltd. Bank of Ceylon

6 Canara Bank Ltd.

Jammu and

Kashmir

Bank Ltd.

Kotak Mahindram

Bank Ltd.

Bank of Nova

Scotia

(Scotia Bank)

7Central Bank of

India Ltd.

Karnataka Bank

Ltd.Yes Bank Ltd.

Bank of Tokyo

Mitsubishi UFJ



8Corporation Bank

Ltd.

Karur Vysya Bank

Ltd.-

Barclays Bank

PLC

9 Dena Bank Ltd.Lakshmi Vilas

Bank Ltd.- BNP Paribas

10 IDBI Bank Ltd.Nainital Bank

Ltd.- Calyon Bank

11 Indian Bank Ltd.Ratnakar Bank

Ltd.-

Chinatrust

Commercial

Bank



12Indian Overseas

Bank Ltd.

SBI Commercial

and International

Bank Ltd.

- Citibank N.A.

13Oriental Bank of

Commerce Ltd.

South Indian Bank

Ltd.- DBS Bank

14Punjab and Sind

Bank Ltd.

Tamilnad

Mercantile

Bank Ltd.

-Deutsche Bank

AG

15Punjab National

Bank Ltd.- - HSBC

16Syndicate Bank

Ltd.- -

JPMorgan Chase

Bank

17 UCO Bank Ltd. - -Krung Thai

Bank

18Union Bank of

IndiaLtd.- -

Mashreq Bank

psc

19United Bank of

India Ltd.- -

Mizuho

Corporate Bank

20 Vijaya Bank Ltd. - -Royal Bank of

Scotland

21

State Bank of

Bikaner

and Jaipur Ltd.

- - Shinhan Bank

22State Bank of

Hyderabad Ltd.- - Société Générale

23State Bank of India

Ltd.- - Sonali Bank

24State Bank of

Mysore Ltd.- -

Standard

Chartered Bank

25State Bank of

Patiyala Ltd.- -

State Bank of

Mauritius



26State Bank of

Travankore- - UBS

27 - - VTB

Industry scenario of Indian Banking Industry:

The growth in the Indian Banking Industry has been more qualitative than quantitative and it

is expected to remain the same in the coming years. Based on the projections made in the

"India Vision 2020" prepared by the Planning Commission and the Draft 10th Plan, the report

forecasts that the pace of expansion in the balance-sheets of banks is likely to decelerate. The

total assets of all scheduled commercial banks by end-March 2010 is estimated at Rs

40,90,000 crores. That will comprise about 65 per cent of GDP at current market prices as

compared to 67 per cent in 2002-03. Bank assets are expected to grow at an annual composite

rate of 13.4 per cent during the rest of the decade as against the growth rate of 16.7 per cent

that existed between 1994-95 and 2002-03. It is expected that there will be large additions to

the capital base and reserves on the liability side.

The Indian Banking industry, which is governed by the Banking Regulation Act of India,

1949 can be broadly classified into two major categories, nonscheduled banks and scheduled

banks. Scheduled banks comprise commercial banks and the co-operative banks. In terms of

ownership, commercial banks can be further grouped into nationalized banks, the State Bank

of India and its group banks, regional rural banks and private sector banks (the old/ new

domestic and foreign). These banks have over 67,000 branches spread across the country.

The Public Sector Banks(PSBs), which are the base of the Banking sector in India account for

more than 78 per cent of the total banking industry assets. Unfortunately they are burdened

with excessive Non Performing assets (NPAs), massive manpower and lack of modern

technology. On the other hand the Private Sector Banks are making tremendous progress.

They are leaders in Internet banking, mobile banking, phone banking, ATMs. As far as

foreign banks are concerned they are likely to succeed in the Indian Banking Industry. In the

Indian Banking Industry some of the Private Sector Banks operating are IDBI Bank, ING

Vyasa Bank, SBI Commercial and International Bank Ltd, Bank of Rajasthan Ltd. and banks

from the Public Sector include Punjab National bank, Vijaya Bank, UCO Bank, Oriental



Bank, Allahabad Bank among others. ANZ Grindlays Bank, ABN-AMRO Bank, American

Express Bank Ltd, Citibank are some of the foreign banks operating in the Indian Banking

Industry.

As far as the present scenario is concerned the Banking Industry in India is going through a

transitional phase. The first phase of financial reforms resulted in the nationalization of 14

major banks in 1969 and resulted in a shift from Class banking to Mass banking. This in turn

resulted in a significant growth in the geographical coverage of banks. Every bank had to

earmark a minimum percentage of their loan portfolio to sectors identified as “priority

sectors”. The manufacturing sector also grew during the 1970s in protected environs and the

banking sector was a critical source. The next wave of reforms saw the nationalization of 6

more commercial banks in 1980. Since then the number of scheduled commercial banks

increased four-fold and the number of bank branches increased eight-fold.

After the second phase of financial sector reforms and liberalization of the sector in the early

nineties, the Public Sector Banks (PSB) s found it extremely difficult to compete with the

new private sector banks and the foreign banks. The new private sector banks first made their

appearance after the guidelines permitting them were issued in January 1993. Eight new

private sector banks are presently in operation. These banks due to their late start have access

to state-of-the-art technology, which in turn helps them to save on manpower costs and

provide better services.

During the year 2000, the State Bank Of India (SBI) and its 7 associates accounted for a 25

percent share in deposits and 28.1 percent share in credit. The 20 nationalized banks

accounted for 53.2 percent of the deposits and 47.5 percent of credit during the same period.

The share of foreign banks (numbering 42), regional rural banks and other scheduled

commercial banks accounted for 5.7 percent, 3.9 percent and 12.2 percent respectively in

deposits and 8.41 percent, 3.14 percent and 12.85 percent respectively in credit during the

year 2000.



Current Scenario:

The industry is currently in a transition phase. On the one hand, the PSBs, which are the

mainstay of the Indian Banking system are in the process of shedding their flab in terms of

excessive manpower, excessive non Performing Assets (Npas) and excessive governmental

equity, while on the other hand the private sector banks are consolidating themselves through

mergers and acquisitions.

PSBs, which currently account for more than 78 percent of total banking industry assets are

saddled with NPAs (a mind-boggling Rs 830 billion in 2000), falling revenues from

traditional sources, lack of modern technology and a massive workforce while the new

private sector banks are forging ahead and rewriting the traditional banking business model

by way of their sheer innovation and service. The PSBs are of course currently working out

challenging strategies even as 20 percent of their massive employee strength has dwindled in

the wake of the successful Voluntary Retirement Schemes (VRS) schemes.

The private players however cannot match the PSB‟s great reach, great size and access to low

cost deposits. Therefore one of the means for them to combat the PSBs has been through the

merger and acquisition (M& A) route. Over the last two years, the industry has witnessed

several such instances. For instance, HDFC BANK‟s merger with Times Bank ICICI

BANK‟s acquisition of ITC Classic, Anagram Finance and Bank of Madura. Centurion

Bank, Indusind Bank, Bank of Punjab, Vysya Bank are said to be on the lookout. The UTI

bank- Global Trust Bank merger however opened a pandora‟s box and brought about the

realization that all was not well in the functioning of many of the private sector banks.

Private sector Banks have pioneered internet banking, phone banking, anywhere banking,

mobile banking, debit cards, Automatic Teller Machines (ATMs) and combined various other

services and integrated them into the mainstream banking arena, while the PSBs are still

grappling with disgruntled employees in the aftermath of successful VRS schemes. Also,

following India‟s commitment to the W To agreement in respect of the services sector,

foreign banks, including both new and the existing ones, have been permitted to open up to

12 branches a year with effect from 1998-99 as against the earlier stipulation of 8 branches.



Talks of government diluting their equity from 51 percent to 33 percent in November 2000

have also opened up a new opportunity for the takeover of even the PSBs. The FDI rules

being more rationalized in Q1FY02 may also pave the way for foreign banks taking the M&

A route to acquire willing Indian partners.

Meanwhile the economic and corporate sector slowdown has led to an increasing number of

banks focusing on the retail segment. Many of them are also entering the new vistas of

Insurance. Banks with their phenomenal reach and a regular interface with the retail investor

are the best placed to enter into the insurance sector. Banks in India have been allowed to

provide fee-based insurance services without risk participation, invest in an insurance

company for providing infrastructure and services support and set up of a separate

jointventure insurance company with risk participation.

Aggregate Performance of the Banking Industry:

Aggregate deposits of scheduled commercial banks increased at a compounded annual

average growth rate (Cagr) of 17.8 percent during 1969-99, while bank credit expanded at a

Cagr of 16.3 percent per annum. Banks‟ investments in government and other approved

securities recorded a Cagr of 18.8 percent per annum during the same period.

In FY01 the economic slowdown resulted in a Gross Domestic Product (GDP) growth of only

6.0 percent as against the previous year‟s 6.4 percent. The WPI Index (a measure of inflation)

increased by 7.1 percent as against 3.3 percent in FY00. Similarly, money supply (M3) grew

by around 16.2 percent as against 14.6 percent a year ago.

The growth in aggregate deposits of the scheduled commercial banks at 15.4 percent in FY01

percent was lower than that of 19.3 percent in the previous year, while the growth in credit by

SCBs slowed down to 15.6 percent in FY01 against 23 percent a year ago.

The industrial slowdown also affected the earnings of listed banks. The net profits of 20 listed

banks dropped by 34.43 percent in the quarter ended March 2001. Net profits grew by 40.75

percent in the first quarter of 2000-2001, but dropped to 4.56 percent in the fourth quarter of

2000-2001. On the Capital Adequacy Ratio (CAR) front while most banks managed to fulfill

the norms, it was a feat achieved with its own share of difficulties. The CAR, which at

present is 9.0 percent, is likely to be hiked to 12.0 percent by the year 2004 based on the

Basle Committee recommendations. Any bank that wishes to grow its assets needs to also



shore up its capital at the same time so that its capital as a percentage of the risk-weighted

assets is maintained at the stipulated rate. While the IPO route was a much-fancied one in the

early „90s, the current scenario doesn‟t look too attractive for bank majors.

Consequently, banks have been forced to explore other avenues to shore up their capital base.

While some are wooing foreign partners to add to the capital others are employing the M& A

route. Many are also going in for right issues at prices considerably lower than the market

prices to woo the investors.

Interest Rate Scene:The two years, post the East Asian crises in 1997-98 saw a climb in the global interest rates.

It was only in the latter half of FY01 that the US Fed cut interest rates. India has however

remained more or less insulated. The past 2 years in our country was characterized by a

mounting intention of the Reserve Bank Of India (RBI) to steadily reduce interest rates

resulting in a narrowing differential between global and domestic rates.

The RBI has been affecting bank rate and CRR cuts at regular intervals to improve liquidity

and reduce rates. The only exception was in July 2000 when the RBI increased the Cash

Reserve Ratio (CRR) to stem the fall in the rupee against the dollar. The steady fall in the

interest rates resulted in squeezed margins for the banks in general.

Governmental Policy:

After the first phase and second phase of financial reforms, in the 1980s commercial banks

began to function in a highly regulated environment, with administered interest rate structure,

quantitative restrictions on credit flows, high reserve requirements and reservation of a

significant proportion of lendable resources for the priority and the government sectors. The

restrictive regulatory norms led to the credit rationing for the private sector and the interest

rate controls led to the unproductive use of credit and low levels of investment and growth.

The resultant „financial repression‟ led to decline in productivity and efficiency and erosion

of profitability of the banking sector in general.

This was when the need to develop a sound commercial banking system was felt. This was

worked out mainly with the help of the recommendations of the Committee on the Financial

System (Chairman: Shri M. Narasimham), 1991. The resultant financial sector reforms called

for interest rate flexibility for banks, reduction in reserve requirements, and a number of

structural measures. Interest rates have thus been steadily deregulated in the past few years



with banks being free to fix their Prime Lending Rates(PLRs) and deposit rates for most

banking products. Credit market reforms included introduction of new instruments of credit,

changes in the credit delivery system and integration of functional roles of diverse players,

such as, banks, financial institutions and non-banking financial companies (Nbfcs). Domestic

Private Sector Banks were allowed to be set up, PSBs were allowed to access the markets to

shore up their Cars.

Challenges facing by banking industry

The banking industry in India is undergoing a major transformation due to changes in

economic condition and continuous deregulation. These multiple changes happening one

after other has a ripple effect on a bank trying to graduate from completely regulated sellers

market to completed deregulated customers market.

Deregulation

This continuous deregulation has made the banking market extremely competitive with

greater autonomy, operational flexibility, and decontrolled interest rate and liberalized norms

for foreign exchange. The deregulation of the industry coupled with decontrol in interest rates

has led to entry of a number of players in the banking industry. At the same time reduced

corporate credit off thanks to sluggish economy has resulted in large number of competitors

battling for the same pie

New Rules:

As a result, the market place has been redefined with new rules of the game. Banks are

transforming to universal banking, adding new channels with lucrative pricing and freebees

to offer. Natural fall out of this new players, new channels squeezed spreads, demanding

customers better service, marketing skills heightened competition, new rules of the

game pressure on efficiency missed opportunities. Need for new orientation diffused

customer loyalty. Bank has led to a series of innovative product offerings catering to various

customer segments, specifically retail credit



Efficiency:

This in turn has made it necessary to look for efficiencies in the business. Bank need to

access low cost funds and simultaneously improve the efficiency. The banks are facing

pricing pressure, squeeze on spread and have to give thrust on retail assets.

Diffused customer loyalty:

This will definitely impact customer preferences, as they are bound to react to the value

added offerings. Customers have become demanding and the loyalties are diffused. These are

multiple choices; the wallet share is reduced per bank with demand on flexibility and

customization. Given the relatively low switching costs; customer retention calls for

customized service and hassle free, flawless service delivery.

Misaligned mindset:

These changes are creating challenges, as employees are made to adapt to changing

conditions. There is resistance to change from employees and the seller market mindset is yet

to be changed coupled with fear of uncertainty and control orientation. Acceptance of

technology in but the utilization is not maximized.

Competency gap:

Placing the right skill at the right place will determine success. The competency gap needs to

be addressed simultaneously otherwise there will be missed opportunities. The focus of

people will be doing work but not providing solutions, on escalating problems rather than

solving them and on disposing customers instead of using the opportunity to cross sell.

Strategic Options with Banks to Cope With the Challenges:

Leading players in the industry have embarked on a series of strategic and tactical initiatives

to sustain leadership. The major initiatives include:

Investing in state of the start of the art technology as the back bone of to ensure reliable

service delivery.

Leveraging the branch network and sales structure to mobilize low cost current and

savings deposits.



Making aggressive forays in the retail advances segments of home and personal loans.

Implementing organization wide initiatives involving people, process and technology to

reduce the fixed costs and the cost per transaction.

Focusing on fee based income to compensate foe squeezed spread.

Innovating products to capture customer ‘mind share’ to begin with and later the wallet

share.

Improving the asset quality as Basel II norms.



Classification of AssetsStandard Assets:

The standard assets consist of assets which are totally regular, safe and conducted as per

norms of sanction. However, during the operations of such accounts, some of them, at times,

show signs of deviations, sickness, out of order position wherein they became irregular.

When such irregularities are noticed, they are classified as ‘Watch Category” assets with

Code No. 12 but continues to be a part of “Standard Asset”. These accounts need higher level

of monitoring and have to be regularised before these irregularities continue for more than 90

days. Provision requirement for a standard asset (including Watch Category asset) is given

below:

Categories of NPAs Banks are required to classify NPAs further into following categories, based on the period for

which asset has remained non-performing and realisability of dues.

Sub-standard Asset

Doubtful Asset

Loss Asset

Substandard Assets:

With effect from 31st March 2005, substandard asset is one which has remained NPA for a

period less than or equal to 12 months. Its Asset Code is 20. The provision requirement in

substandard asset was earlier flat 10% of the outstanding dues, irrespective of the category of

the advance (secured or clean).

Now RBI has removed the CAP on the unsecured exposures and individual Bank Boards

were given the freedom to formulate their own policy guidelines for prudential norms on

unsecured exposures. Simultaneous with this liberalisation, RBI has made norms of provision

requirement on unsecured exposure of Banks more stringent. Unsecured exposure is defined

as an exposure where the realisable value of security as stipulated and ascertained by the

valuation is not more than 10% `ab initio’. That means all clean / unsecured advances when

they become NPA as substandard asset, will now (w.e.f. 31.3.2005) require a provision at

20% of the outstanding



Balances. As against this, the normal secured advances, when moving to NPA as substandard

asset will require 10% of the outstanding balance as provision (no change from existing

system). Thus from 31.3.2005 onwards the substandard asset will have 2 segments with

different provision requirement as below:-

(a) Substandard – secured assets – Code 21 – provision at 20% of outstanding dues

(b) Substandard – unsecured assets – Code 22 – provision at 20% of outstanding dues

Doubtful Assets:

It consists of 3 stages - Doubtful I, Doubtful II and Doubtful III. The provision requirement in

each stage of Doubtful asset will be as under:

Doubtful I (Code 31) - Assets remaining for a period of 12 months in Doubtful category –

provision requirement shall be 20% of RVS + 100% of shortfall in security (i.e. NPAs over

12 months upto 24 months)

Bank Group

Standard AssetsSub-standard assets

Doubtful assets Loss assets Total NPAs

Year Amt % Amt % Amt % Amt % Amt %

2002-03 523724 90.6 149092.6

32340 5.6 6840 1.2 528079.4

2003-04 610435 92.2 169092.6

28756 4.3 5876 0.9 501497.8

2004-05 830029 94.6 110681.3

30799 3.5 5929 0.7 456195.4

2005-06 1092607 96.2 11453 1 25028 2.2 5636 0.5 413783.7

2006-07 1425519 97.3 14275 1 19873 1.4 4826 0.3 386022.7

2007-08 1778476 97.8 17290 1 19291 1.1 4018 2 397392.2

2008-09 2237556 97.9 266030.9

21019 0.9 4296 0.1 440432.2

2009-10 2673534 97.8 28791 1 25383 0.9 5750 0.2 573012.1

2010-11 327291497.7

734973 1 33180 0.99 6463

0.19

713262.1

2011-12 3825500 97 623001.6

49000 1.2 6000 0.2 83772 2

AVERAG 1827029.4 95.9 23857.1 1. 28466.9 2.21 5563.4 0.6 52473.6 4



E 2 4 3TOTAL 18270294 238571 284669 55634 524736



Reporting Format For NPA – Gross And Net Npa Name of the Bank:

Position as on………

PARTICULARS

1) Gross Advanced *

2) Gross NPA *

3) Gross NPA as %age of Gross Advanced

4) Total deduction( a+b+c+d )

( a ) Balance in interest suspense a/c **

( b ) DICGC/ECGC claims received and held pending

adjustment

( c ) part payment received and kept in suspense a/c

( d ) Total provision held ***

5) Net advanced ( 1-4 )

6) Net NPA ( 2-4 )

7) Net NPA as a %age of Net Advance

*excluding Technical write-off of Rs.________crore.

**Banks which do not maintain an interest suspense a/c to park the accrued interest on

NPAs may furnish the amount of interest receivable on NPAs.

***Excluding amount of Technical write-off (Rs.______crore) and provision on standard

assets. (Rs._____crore).



TYPES OF NPA: 1. Gross NPA

2. Net NPA

Gross NPA:

Gross NPAs are the sum total of all loan assets that are classified as NPAs as per RBI

guidelines as on Balance Sheet date. Gross NPA reflects the quality of the loans made by

banks. It consists of all the nonstandard assets like as sub-standard, doubtful, and loss assets.

It can be calculated with the help of following ratio: Gross NPAs Ratio = Gross NPAs

Gross Advances

Net NPA:

Net NPAs are those type of NPAs in which the bank has deducted the provision regarding

NPAs. Net NPA shows the actual burden of banks. Since in India, bank balance sheets

contain a huge amount of NPAs and the process of recovery and write off of loans is very

time consuming, the provisions the banks have to make against the NPAs according to the

central bank guidelines, are quite significant. That is why the difference between gross and

net NPA is quite high. It can be calculated by following: Net NPAs = Gross NPAs –

Provisions

Gross Advances – Provisions

IMPACT OF NPA:

Profitability:

NPA means booking of money in terms of bad asset, which occurred due to wrong choice of

client. Because of the money getting blocked the prodigality of bank decreases not only by

the amount of NPA but NPA lead to opportunity cost also as that much of profit invested in

some return earning project/asset. So NPA doesn’t affect current profit but also future stream

of profit, which may lead to loss of some long-term beneficial opportunity. Another impact of

reduction in profitability is low ROI (return on investment), which adversely affect current

earning of bank.



Liquidity:

Money is getting blocked, decreased profit lead to lack of enough cash at hand which lead to

borrowing money for shortest period of time which lead to additional cost to the company.

Difficulty in operating the functions of bank is another cause of NPA due to lack of money

Routine payments and dues.

Involvement of management: Time and efforts of management is another indirect cost which

bank has to bear due to NPA. Time and efforts of management in handling and managing

NPA would have diverted to some fruitful activities, which would have given good returns.

Now day’s banks have special employees to deal and handle NPAs, which is additional cost

to the bank.

Credit loss: Bank is facing problem of NPA then it adversely affect the value of bank in terms

of market credit. It will lose its goodwill and brand image and credit which have negative

impact to the people who are putting their money in the banks

Procedures for NPA Identification in India.

Internal Checks and Control

Since high level of NPAs dampens the performance of the banks identification of potential

problem accounts and their close monitoring assumes importance. Though most banks have

Early Warning Systems (EWS) for identification of potential NPAs, the actual processes

followed, however, differ from bank to bank. These early warning signals used by banks are

generally independent of risk rating systems and asset classification norms prescribed by

RBI. The major components/processes of a EWS followed by banks in India as brought out

by a study conducted by Reserve Bank of India at the instance of the Board of Financial

Supervision are as follows:

Designating Relationship Manager/ Credit Officer for monitoring account/s

Preparation of `know your client' profile

Credit rating system

Identification of watch-list/special mention category accounts

Monitoring of early warning signals



Relationship Manager/Credit Officer

The Relationship Manager/Credit Officer is an official who is expected to have complete

knowledge of borrower, his business, his future plans, etc. The Relationship Manager has to

keep in constant touch with the borrower and report all developments impacting borrowable

account. As a part of this contact he is also expected to conduct scrutiny and activity

inspections. In the credit monitoring process, the responsibility of monitoring a corporate

account is vested with Relationship Manager/Credit Officer

Know your client' profile (KYC)

Most banks in India have a system of preparing `know your client' (KYC) profile/credit

report. As a part of `KYC' system, visits are made on clients and their places of

business/units. The frequency of such visits depends on the nature and needs of relationship.

Credit Rating System

The credit rating system is essentially one point indicator of an individual credit exposure

and is used to identify measure and monitor the credit risk of individual proposal. At the

whole bank level, credit rating system enables tracking the health of banks entire credit

portfolio. Most banks in India have put in place the system of internal credit rating. While

most of the banks have developed their own models, a few banks have adopted credit rating

models designed by rating agencies. Credit rating models take into account various types of

risks viz. financial, industry and management, etc. associated with a borrowable unit. The

exercise is generally done at the time of sanction of new borrowable account and at the time

of review renewal of existing credit facilities.

Watch-list/Special Mention Category

The grading of the bank's risk assets is an important internal control tool. It serves the need

of the Management to identify and monitor potential risks of a loan asset. The purpose of

identification of potential NPAs is to ensure that appropriate preventive / corrective steps

could be initiated by the bank to protect against the loan asset becoming non-performing.

Most of the banks have a system to put certain borrowable accounts under watch list or

special mention category if performing advances operating under adverse business or

economic conditions are exhibiting certain distress signals.



Early Warning Signals It is important in any early warning system, to be sensitive to signals

of credit deterioration. A host of early warning signals are used by different banks for

identification of potential NPAs. Most banks in India have laid down a series of operational,

financial, transactional indicators that could serve to identify emerging problems in credit

exposures at an early stage. Further, it is revealed that the indicators which may trigger early

warning system depend not only on default in payment of installment and interest but also

other factors such as deterioration in operating and financial performance of the borrower,

weakening industry characteristics, regulatory changes, general economic conditions, etc.

Early warning signals can be classified into five broad categories viz.

a) Financial

b) Operational

c) Banking

d) Management and

e) External factors

Financial:

Related warning signals generally emanate from the borrowers' balance sheet, income

expenditure statement, statement of cash flows, statement of receivables etc. Following

common warning signals are captured by some of the banks having relatively developed

EWS.

Financial warning signals

Persistent irregularity in the account

Default in repayment obligation

Devolvement of LC/invocation of guarantees

Deterioration in liquidity/working capital position

Substantial increase in long term debts in relation to equity

Declining sales

Operating losses/net losses

Rising sales and falling profits

Disproportionate increase in overheads relative to sales



Rising level of bad debt losses Operational warning signals

Low activity level in plant

Disorderly diversification/frequent changes in plan

Nonpayment of wages/power bills

Loss of critical customer/s

Frequent labor problems

Evidence of aged inventory/large level of inventory

Management related warning signals

Lack of co-operation from key personnel

Change in management, ownership, or key personnel

Desire to take undue risks

Family disputes

Poor financial controls

Fudging of financial statements

Diversion of funds

Banking related signals

Declining bank balances/declining operations in the account

Opening of account with other bank

Return of outward bills/dishonored cheques

Sales transactions not routed through the account

Frequent requests for loan

Frequent delays in submitting stock statements, financial data, etc.

Signals relating to external factors

Economic recession

Emergence of new competition

Emergence of new technology

Changes in government / regulatory policies

Natural calamities

Willful Defaulters



RBI has issued revised guidelines in respect of detection of willful default and diversion and

siphoning of funds. As per these guidelines a willful default occurs when a borrower defaults

in meeting its obligations to the lender when it has capacity to honor the obligations or when

funds have been utilized for purposes other than those for which finance was granted. The list

of willful defaulters is required to be submitted to SEBI and RBI to prevent their access to

capital markets. Sharing of information of this nature helps banks in their due diligence

exercise and helps in avoiding financing unscrupulous elements. RBI has advised lenders to

initiate legal measures including criminal actions, wherever required, and undertake a

proactive approach in change in management, where appropriate.



Chapter – 4. RESEARCH METHODOLOGY

Scope of the study:-

This research report is based on historical data of public sector banks and the source

for the data is Trends and progress report of banking industry from RBI website. For the

analysis the main NET NPA and NET PROFIT are being taken etc. and area of research in

banking industry very wide but my report is limited to these public sector banks only and

time period of data is ten year it’s to get probable output and on the basis of this forecasting

can be done.

Research objective:- To analysis the impact of non-performing assets on profitability of Public sector

banks.

To evaluate the impact of non-performing assets on profitability with other variables.

To examine the impact of non-performing assets on efficiency and Liquidity.

To know the ratio of NPA and Advances of public sector banks

Methodology:- Types of data: secondary data

Sampling unit: - All public sector banks

Period of the study: 10 year (1/4/2002 to 31/3/2012)

Data collection: journals, articles, internet, books

Tools and techniques: Descriptive test

Correlation analysis

Regression analysis

Jarque-Bera,

Kurtosis,

Skewness,

Pairwise Granger Causality Tests,

Johansen Cointegration Test, and

Ratio of NPA and Advances.



Limitation

This project Report study only past 10 year data so the chances of relationship between

variable me be wrong.

We have taken assumption for find out liquidity result, the Net advances will return back as

their perfect time period, so no outstanding amt remaining at end of the year.

Report study only on public sector banks.

Tools and techniques:Correlation Analysis:

There can be both short-run and long-run relationships between financial time series.

Correlation coefficients are used for examining short-run co-movements and multi-

collinearity among the variables. If correlation coefficient is greater than 0.8, it indicates that

multi collinearity exists. The population correlation coefficient, p, (-1 ≤ p ≤ 1) measures the

degree of linear association between two variables.

Co-integration Test:

Johansen's cointegration test (Johansen and Juselius, 1990) has been applied to check whether

the long run equilibrium relationship exists between the variables. The Johansen approach to

cointegration test is based on two test statistics, viz., trace statistic, and maximum eigenvalue

statistic. The trace statistic can be specified as:

Trace (r, k) = - T∑ ln (1-λi) (1)

Where λi is the i th largest eigenvalue of matrix Π and T is the number of observations. In the

trace test, the null hypothesis is that the number of distinct cointegrating vector(s) is less than

or equal to the number of cointegration relations (r). From the above, it is clear that λ trace

equals Zero when all λ= 0. The maximum eigenvalue test examines the null hypothesis of

exactly r cointegrating relations against the alternative of r + 1 cointegrating relations with

the test statistic:

λ max (r, r+1) = -T ln (1- λr+1) (2)



Granger Causality test:

At the end, the Granger Causality test (Engle and Granger, 1987) has been used to find out

the direction of causality between the variables. To test for Granger Causality, the following

bivariate regression model can be used:

m n yt = α0 + ∑ αiYt-1 + ∑ βjXt-1 + εt (3)

i=1 j=1

m nxt = ω0 + ∑ γiYt-1 + ∑ θjXt-1 + εt (4)

i=1 j=1

The null hypothesis is H0: ∑ βj = 0 in the first regression equation of y i.e. lagged X terms do

not belong in the regression means X does not cause y.

If all the coefficients of x in the first regression equation of y, i.e. β j for j = 1...... are

significant, then the null hypothesis that x does not cause y is rejected.



Chapter – 5. DATA BASE AND METHODOLOGY

Hypothesis of the Study.

Ho= There is no significant association between gross NPAs to gross advances of the

public sector banks.

Ho= There is no significant association between priority sector, non priority sector, public

sector & from NPAs point of view.

Ho= There is no significant reduction in the portion of gross NPAs to gross advances.

Ho= There is no significant relation between Net NPA and NET PROFIT.



(1) To analysis the impact of Non-performing assets on profitability of Public sector banks.

Table-1: Net Npa to Net Profit of Public Sector Banks. (Amount in Crores)

(Source: Report On Trend And Progress of Banking In India from 2003 to 2012)

Table No-1.1 : Descriptive Statistics

NET NPA NET PROFITMean 23472.30 35144.20

Median 20184.00 23372.00Std. Dev. 8826.273 25332.07Skewness 0.758552 0.857480Kurtosis 2.151510 2.150133

Jarque-Bera 1.258974 1.526400Probability 0.532865 0.466172

Analysis:

Jarque-Bera: From the Data it is clear that Probability is more than 0.05 that’s shows that

data follow the normality in the past 10 year in NPA & PROFIT. The probability is

respectively 0.532 & 0.4466 that’s show normally distributed.

Kurtosis: From the result it is clear that data follow the Platykurtic. The standard is less than

3 then data follow Platykurtic, if more than 3 then data follow the Leptokurtic. Here both

variable NPA & PROFIT result is 2.1589 &2.1501 respectively.


Year Net NPA Net Profit

2002-03 24877 12295

2003-04 19335 16546

2004-05 16904 15784

2005-06 14566 16539

2006-07 14145 20152

2007-08 17726 26592

2008-09 21033 34394

2009-10 29644 57109

2010-11 36071 70331

2011-12 39423 81700


Skewness: The standard of the test is in negative or positive; here result shows positive in

both the variable its show the normally distributed follow by data.

Table No-1.2: Correlation Analysis:

Analysis:Correlation result shows the positive correlation between NET NPA and NET PROFIT. Its

show the one of the objective to know the impact of npa on profitability its clear in result that

Correlation is 0.912 is more than 0.800, it indicate high correlation between them.

Table No-1.3: Regression analysis.

Variable Coefficient Std. Error t-Statistic Prob.

C -26288.31 10378.30 -2.533007 0.0351

NET NPA 2.617234 0.416446 6.284688 0.0002

R-squared 0.831569 Mean dependent var 35144.20

Adjusted R-squared 0.810516 S.D. dependent var 25332.07

S.E. of regression 11027.00 Akaike info criterion 21.63094

Sum squared resid 9.73E+08 Schwarz criterion 21.69146

Log likelihood -106.1547 Hannan-Quinn criter. 21.56455

F-statistic 39.49731 Durbin-Watson stat 0.468111

Prob(F-statistic) 0.000237

Analysis:

The regression test on NET NPA and NET PROFIT show the R squared is .831569 means

the both variable in the test show the relation between each other positive and data will affect

with each other. If the variable is more than 2 then the chances of getting R-square is 1 means

High relationship between them, therefore we can applied the test of Adjusted R-squared.

Here the variable more than two does not affect with each other. And Adjusted R-square is

0.810516 it shows high relationship between NPA and PROFIT if the NPA increase its affect

the PROFIT margin of public sector Banks.


NET NPA NET PROFITNET NPA 1

NET PROFIT 0.912 1


Table No-1.4: Granger Causality Tests.

Null Hypothesis F-Statistic Probability DecisionNETPROFIT does not Granger Cause NETNPA 0.07989 0.9251 Accepted

NETNPA does not Granger Cause NETPROFIT .86378 0.5055 Accepted

Analysis:

Granger Causality test say if the probability is less than 0.05 reject the null hypothesis, if

more than 0.05 accepted the hypothesis. Here in Net Profit to Net NPA the probability is

0.9251 means Accepted and NET NPA to NET PROFIT is 0.5055 the null hypothesis

Accepted and will affected the each other, here if Net Profit Decreases its means the affected

by NPA.

Table No-1.5: Johansen Cointegration Test.Unrestricted Cointegration Rank Test (Trace)

Hypothesized Trace 0.05No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None * 0.950581 24.07038 15.49471 0.0020At most 1 0.001385 0.011090 3.841466 0.9159

Trace test indicates 1 cointegrating eqn(s) at the 0.05 level

* denotes rejection of the hypothesis at the 0.05 level**MacKinnon-Haug-Michelis (1999) p-values

Unrestricted Cointegration Rank Test (Maximum Eigenvalue)

Hypothesized Max-Eigen 0.05No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None * 0.950581 24.05929 14.26460 0.0011At most 1 0.001385 0.011090 3.841466 0.9159

Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level




(2) To evaluate the impact of non-performing assets on profitability with other variables.

Table No-2: NPA of Priority, Non-priority, and Remaining Public to Net Profit

(Amount in Crores)

Year Priority Sector Non-priority Sector Public Sector Net Profit2002-03 24939 26781 1087 122952003-04 23841 25698 610 165462004-05 21926 23249 444 157842005-06 22374 18664 341 165392006-07 22954 15158 490 201522007-08 25287 14153 299 265922008-09 24318 19251 474 343942009-10 30848 25929 524 571092010-11 41245 29803 278 703312011-12 48524 34502 746 81700

(Source: Report on Trend And Progress of Banking In India from 2003 to 2012)

Table No-2.1: Descriptive test.

PRIORITY NON PRIORITY PUBLIC NET PROFITMean 28625.60 23318.80 529.3000 35144.20

Median 24628.50 24473.50 482.0000 23372.00Std. Dev. 9082.669 6501.273 242.2244 25332.07Skewness 1.390414 0.111797 1.224214 0.857480Kurtosis 3.408916 2.064054 3.841249 2.150133

Jarque-Bera 3.291758 0.385829 2.792707 1.526400Probability 0.192843 0.824553 0.247498 0.466172

Analysis:

Jarque-Bera: From the Data it is clear that Probability is more than 0.05 that’s show the data

follow the normality in the past 10 year in NPA & PROFIT. The probability is respectively in

priority sector, Non priority sector & Public sector to Net Profit like 0.1928 & 0.82450 &

0.2474 & 0.4661 that’s shows normally distributed.


3 in both the variable like Non priority & Net Profit and more than 3 than data follow the

Leptokurtic. Both variable priority sector and public sector result is 3.4089 &3.8141

respectively.



Skewness: The standard of the test is in negative or positive; here result shows positive in the

entire variable its show the normally distributed follow by data.

Table No-2.2: Correlation Analysis.

PRIORITY NONPRIORITY PUBLIC NETPROFITPRIORITY 1

NON PRIORITY 0.77145 1PUBLIC 0.08411 0.45452 1

NET PROFIT 0.94424 0.6574 -0.09704 1

Analysis:

Correlation results show the positive correlation between PRIORITY and NET PROFIT and

Average correlation between NON PRIORITY and NET PROFIT and no correlation between

PUBLIC SECTOR and NET PROFIT. The one of the objective to know the impact of npa on

profitability with other variable it’s clear in result that Correlation is respectively 0.94424,

0.6574 and -0.09704. If correlation more than 0.800 then it indicate high relation and between

0 .8 to 0.5 then it indicate average relation.

Table No-2.3: Regression Test.


C -31528.83 11185.74 -2.818664 0.0304PRIORITY 2.689335 0.562783 4.778634 0.0031

NONPRIORITY -0.026662 0.879563 -0.030313 0.9768PUBLIC -18.30542 15.07430 -1.214346 0.2702

R-squared 0.922970 Mean dependent var 35144.20Adjusted R-squared 0.884455 S.D. dependent var 25332.07S.E. of regression 8610.854 Akaike info criterion 21.24861Sum squared resid 4.45E+08 Schwarz criterion 21.36964

Log likelihood -102.2430 Hannan-Quinn criter. 21.11583F-statistic 23.96392 Durbin-Watson stat 1.433864


Analysis:

The regression test on NPA of Priority sector, Non-Priority sector and Public sector and NET

PROFIT show the R squared is 0.922970 means the both variable in the test show the relation

between each other is very high and data will affect with each other. If the variable is more

than 2 the chances of getting R-square is 1 means High relationship between them, therefore

we can applied the test of Adjusted R-squared. Here the variable more than two does not



affect with each other. And Adjusted R-square is 0.884455 it show high relationship between

NPA of Priority sector, Non- priority sector, public sector and PROFIT. If the NPA of

different sector increase the decrease in the PROFIT margin of public sector Banks

Table No-2.4: Pairwise Granger Causality Tests.

Null Hypothesis F-Statistic Probability Decision

NETPROFIT does not Granger Cause PRIORITY 11.9584 0.0372 Rejected

PRIORITY does not Granger Cause NETPROFIT 3.7898 0.1510 Accepted

NETPROFIT does not Granger Cause NONPRIORITY 1.87085 0.2968 Accepted

NONPRIORITY does not Granger Cause NETPROFIT 13.1264 0.0328 Rejected

NETPROFIT does not Granger Cause PUBLIC 1.57091 0.3414 Accepted

PUBLIC does not Granger Cause NETPROFIT 1.75564 0.3127 Accepted

Analysis:

Granger Causality test say if the probability is less than 0.05 reject the null hypothesis and if

more than 0.05 accepted the null hypothesis. Here in Net Profit to Priority Sector the

probability is 0.0372 means Rejected the null hypothesis and Net Profit to Non Priority sector

the probability is 0.2968 means Accepted the null hypothesis and Net Profit to Public Sector

the probability is 0.3414 means Accepted the null hypothesis and other like Priority to Net

profit is accepted, Non priority to Net profit Rejected and Public to Net profit Accepted. The

results show the accepted and rejection of null hypothesis, and will affected the each other,

here if Net Profit Decreases its means the affected by NPA.



(3) To examine the impact of non-performing assets on efficiency and Liquidity.

Table No-3: Gross NPA to Gross Advance and Ratio of Gross NPA to Gross Advance. (Amount in Crores)

Year Gross NPA Gross AdvanceGross NPA To Gross

Advances

2002-03 56,473 577813 6.85

2003-04 54,090 661975 7.79

2004-05 52,880 877825 5.53

2005-06 41,358 1134724 3.64

2006-07 38,968 1464493 2.66

2007-08 40,595 1819074 2.23

2008-09 44,957 2282081 2.19

2009-10 59,926 2736347 2.23

2010-11 74,614 3265245 2.5

2011-12 117,200 3645235 3.1

(Source: Report On Trend And Progress of Banking In India from 2003 to 2012)

Table No-3.1: Descriptive Statistics of Public sector bank.

GROSS ADVANCE GROSS NPAMean 1846481. 58106.10

Median 1641784. 53485.00Std. Dev. 1097176. 23429.14Skewness 0.393184 1.742166Kurtosis 1.780627 5.165252


Analysis:

Jarque-Bera: From the Data it is clear that Probability is more than 0.05 that’s show the data

follow the normality in the past 10 year in GROSS NPA & GROSS ADVANCES. Here the

probability is respectively 0.030016 & 0.644943 that’s show normally distributed in GROSS

ADVANCE and GROSS NPA Do not follow the normal distribution.




3 in gross advances and gross NPA it follow the Leptokurtic. Here the result respectively in

GROSS ADVANCES and GROSS NPA is 1.780627 and 5.165252.




GROSS ADVANCE GROSS NPAGROSS ADVANCE 1

GROSS NPA 0.67952 1

Analysis:Correlation result shows the positive correlation between GROSS NPA and GROSS

ADVANCE its shows the one of the objective to know the liquidity impact of NPA in public

sector Banks, it’s clear in result that Correlation is 0.67952 if more than 0.800 it indicate high

correlation between them, but here not more correlation between gross advance and gross npa

its result the npa does not affected greater to Liquidity.

Table No-3.3: Regression analysis.


C 31312.51 11740.57 2.667035 0.0285

GROSSADVANCE 0.014511 0.005539 2.619754 0.0307

R-squared 0.461755 Mean dependent var 58106.10Adjusted R-squared 0.394474 S.D. dependent var 23429.14






Analysis:The regression test on GROSS ADVANCES and GROSS NPA show the R squared is

0.461755 means the both variable in the test show the relation between each other are not

positive and data will affect with each other is lesser. If the variable is more than 2 the

chances of getting R-square is 1 means High relationship between them, therefore we can



applied the test of Adjusted R-squared. Here the variable more than two does not affect with

each other. And Adjusted R-square is 0.394474 it show less relationship between GROSS

ADVANCES and GROSS NPA if the GROSS NPA increase it does not affect the GROSS

ADVANCES of public sector Banks.



GROSS NPA does not Granger Cause GROSS ADVANCE 4.22619 0.1341 Accepted

GROSS ADVANCE does not Granger Cause GROSS NPA 6.35724 .0834 Accepted

Analysis:Granger Causality test say if the probability is less than 0.05 reject the null hypothesis if more

than 0.05 accepted the null hypothesis. Here in GROSS NPA and GROSS ADVANCES the

probability is 0.1341 means accepted the null hypothesis and in GROSS ADVANCES and

GROSS NPA probability 0.0834 accepted the null hypothesis.

Table No-3.5: Johansen Cointegration test.

Unrestricted Cointegration Rank Test (Trace)


None * 0.969779 37.31267 15.49471 0.0000At most 1 * 0.688035 9.318926 3.841466 0.0023

Trace test indicates 2 cointegrating eqn(s) at the 0.05 level

* denotes rejection of the hypothesis at the 0.05 level


Hypothesized Max-Eigen 0.05

No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None * 0.969779 27.99374 14.26460 0.0002



At most 1 * 0.688035 9.318926 3.841466 0.0023


Ratio analysis of ratio between gross advances and gross NPA

On the basis of Ratio of last 10 year gross advances and gross NPA is high in 2002-03 to

2005-06, is approximately between in 2003-04 is 7.79 thereafter slowly decreases and low in

the year 2008-09 is 2.19. If we taken average of all the ratio is 3.871 is good than individual

year ratio.



(4) To know the ratio of NPA and Advances of public sector banks.

Table No-4: Net NPA to Net Advance and Ratio of NPA and Advance.

Year Net NPA Net AdvanceNet NPA To Net

Advances

2002-03 24877 5,49,351 3.03

2003-04 19335 6,31,383 2.99

2004-05 16904 8,48,912 2.06

2005-06 14566 11,06,128 1.32

2006-07 15144 14,40,123 1.05

2007-08 17726 17,97,504 0.99

2008-09 21033 22,60,156 1.09

2009-10 29644 26,32,236 1.09

2010-11 36071 32,03,125 1.1

2011-12 39423 35,21,563 1.4

(Source: Report on Trend and Progress of Banking in India from 2003 to 2012)

Table No-4.1: Descriptive Statistics of Public sector.

Analysis:Jarque-Bera: From the Data it is clear that Probability is more than 0.05 it show the data

follow the normality in the past 10 year in NET ADVANCES and NET NPA. The probability

is respectively 0.64989 & 0.532865 it show normally distributed.


3 then data follow Platykurtic, if more than 3 then data follow the Leptokurtic. Here both

variable NET ADVANCE & NET NPA result is 1.757141 &2.151510 respectively.


NET ADVANCE NET NPAMean 1799048. 23472.30

Median 1618814. 20184.00Std. Dev. 1068864. 8826.273Skewness 0.362051 0.758552Kurtosis 1.757141 2.151510






NETADVANCE NET NPANETADVANCE 1

NETNPA 0.7969 1

Analysis:

Correlation result shows the positive correlation between NET NPA and NET ADVANCE.

Its show the one of the objective to know the impact of npa on liquidity. It’s clear in result the

Correlation is 0.7969 is equal to 0.800 it indicate high correlation between them.

Table No-4.3: Regression test.


C 11632.64 3641.754 3.194240 0.0127

NETADVANCE 0.006581 0.001763 3.731944 0.0058

R-squared 0.635160 Mean dependent var 23472.30

Adjusted R-squared 0.589555 S.D. dependent var 8826.273






Analysis:

The regression test on NET NPA and NET ADVANCE shows the R squared is 0.635160

means the both variable in the test show the relation between each other positive and data will

affect with each other. If the variable is more than 2 then the chances of getting R-square is 1,

means High relationship between them, therefore we can applied the test of Adjusted R-

squared. Here the variable more than two does not affect with each other. And Adjusted R-

square is 0.589555 it show average relationship between NET NPA and NET ADVANCE.





NET NPA does not Granger Cause NET ADVANCE 44.7597 .0058 Rejected

NET ADVANCE does not Granger Cause NET NPA 1.76669 0.3112 Accepted

Analysis:

Granger Causality test say if the probability is less than 0.05 reject the null hypothesis if more

than 0.05 accepted the null hypothesis. Here in Net ADVANCE to Net NPA the probability is

0.3112 means Accepted and NET NPA to NET ADVANCE is 0.0058 the null hypothesis

rejected and NET NPA does not cause NET ADVANCE and in second test NET ADVANCE

cause the NET NPA.

Table No-4.5: Johansen Cointegration Test.

Unrestricted Cointegration Rank Test (Trace)


None * 0.978742 32.18377 15.49471 0.0001At most 1 0.157973 1.375550 3.841466 0.2409

Trace test indicates 1 cointegrating eqn(s) at the 0.05 level* denotes rejection of the hypothesis at the 0.05 level**MacKinnon-Haug-Michelis (1999) p-values


Hypothesized Max-Eigen 0.05No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None * 0.978742 30.80822 14.26460 0.0001At most 1 0.157973 1.375550 3.841466 0.2409

Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level* denotes rejection of the hypothesis at the 0.05 level**MacKinnon-Haug-Michelis (1999) p-values



Ratio analysi between NET ADVANCES and GROSS NPA

On the basis of Ratio of last 10 year net advances and net NPA is average in 2002-03 to

2011-12 compare to Gross Advances to Gross Npa and approximately between heights in

2002-03 is 3.03 thereafter slowly decreases and low in year 2007-08 is 0.99. If we taken

average of all the ratio is 1.1612 is good than individual year ratio.



Chapter – 6. FINDING

a. Form the Analysis we came to know that there is a positive relationship between NPA

and Profitability in public sector banks.

b. After analysis of impact of non-performing assets on profitability with other variables.

Like priority sector, non priority sector, and other variable, show high correlation ship

between NPA with Priority sector and average correlation ship between NPA and Non-

Priority sector and other public sector.

c. After analysis of the impact of non-performing assets on efficiency and Liquidity show

Average correlation ship.

d. The ratio of NPA and Advances of public sector banks is high.



Chapter – 7. CONCLUSION

The NPAs of public sector banks in absolute terms has shown increasing trend till 2003-04 to

2011-12 and declined later on in 2004-05 to 2007-08, where as its test applied in the NET

NAP and NET ADVANCE also prove that’s the significant impact of NPA on profitability in

public sector banks. If the talk about profitability from applied all the test it’s null hypothesis

rejected and correlation is more than 0.8 and regression R-square is also good and Johansen

Cointegration Test give the result that null hypothesis is also rejected at 0.05 level.

Result of other variable of priority sector, non-priority sector and remaining public sector its

result of impact on profit is also more and other result for liquidity show there is not much

more but only average impact on liquidity. Indian banking sector is facing a serious problem

of NPA. The extent of NPA is comparatively higher in public sectors banks than the private

sector.

The impact of NPA on profitability them from applied a test we concluded that Correlation

result show the positive correlation between NET NPA and NET PROFIT its show

Correlation is 0.912 is more than 0.800 the indicate high correlation between them. Also

other tools analysis Granger Causality test says if Net Profit Decreases its means the affected

by NPA. The Correlation result show the positive correlation between PRIORITY and NET

PROFIT and Average relation between NON PRIORITY and NET PROFIT and no

correlation between PUBLIC SECTOR And NET PROFIT show the one of the objective to

know the impact of npa on profitability with other variable its clear in result the Correlation is

respectively like 0.94424, 0.6574 and -0.09704 is more than 0.800 the indicate high

correlation and between0 .8 to 0.5between them indicate average.

Correlation result show the positive correlation between GROSS NPA and GROSS

ADVANCE its show the one of the objective to know the liquidity impact of NPA in public

sector Banks, it’s clear in result the Correlation is 0.67952 if more than 0.800 the indicate

high correlation between them, but here the not more correlation between gross advance and

gross npa its result the npa does not affected greater to Liquidity. Correlation result show the

positive correlation between NET NPA and NET ADVANCE its show the one of the



objective to know the impact of npa on liquidity its clear in result the Correlation is 0.7969 is

more than 0.800 the indicate high correlation between them.

Chapter – 8. REFERENCES

1. Anshu Bansal* (2012) " A Study On Recent Trends In Risk Management Of Non

Performing Assets (Npas) By Public Sector Banks In India”- Journal of Information and

Operations Management ISSN: 0976–7754 & E-ISSN: 0976–7762 , Volume 3, Issue

1, , pp-50– 56.

2. Chandan Chatterjee*, Jeet Mukherjee; Dr.Ratan Das (November 2012) “ Management

Of Non Performing Assets - A Current Scenario” International Journal of Social

Science & Interdisciplinary Research Vol.1 Issue 11, , ISSN 2277 3630.

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Performing Assets (NPAs) of Indian Banking During Post Millennium Period”

International Journal of Business and Management Tomorrow Vol. 2 No. 3


Grand project

Economy & Finance

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