lass 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-foldAfter 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.Classification of BanksThe Indian banking industry, which is governed by the Banking Regulation Act of India1949 can be broadly classified into two major categories, non-scheduled 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 Indian banking industry is a mix of the public sector, private sector and foreign banks. The private sector banks are again spilt into old banks and new banks.The banking system in India is significantly different from that of other Asian nations because of the countrys unique geographic, social, and economic characteristics. India has a large population and land size, a diverse culture, and extreme disparities in income, which are marked among its regions. There are high levels of illiteracy among a large percentage of its population but, at the same time, the country has a large reservoir of managerial and technologically advanced talents. Between about 30 and 35 percent of the population resides in metro and urban cities and the rest is spread in several semi-urban and rural centres The countrys economic policy framework combines socialistic and capitalistic features with a heavy bias towards public sector investment. India has followed the path of growth-led exports rather than the exported growth of other Asian economies, with emphasis on self-reliance through import substitution. These features are reflected in the structure, size, and diversity of the countrys banking and financial sector. The banking system has had to serve the goals of economic policies enunciated in successive five-year development plans, particularly concerning equitable income distribution, balanced regional economic growth, and the reduction and elimination of private sector monopolies in trade and industry. In order for the banking industry to serve as an instrument of state policy, it was subjected to various nationalization schemes in different phases (1955, 1969, and 1980). As a result, banking remained internationally isolated (few Indian banks had presence abroad in international financial centers) because of preoccupations with domestic priorities, especially massive branch expansion and attracting more people to the system.

These features have left the Indian banking sector with weaknesses and strengths. A big challenge facing Indian banks is how, under the current ownership structure, to attain operational efficiency suitable for modern financial intermediation. On the other hand, it has been relatively easy for the public sector banks to recapitalize, given the increase in nonperforming assets (NPAs), as their Government dominated ownership structure has reduced the conflicts of interest that private banks would face.

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 M&A.

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 VRS The private players however cannot match the PSBs 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 Banks merger with Times Bank Icici Banks 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 pandoras 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 Indias 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 joint-venture insurance company with risk participation.General Banking Scenario

The predicament of the banks in the developed countries owing to excessive leverage and lax regulatory system has time and again been compared with somewhat unscathed Indian Banking Sector. An attempt has been made to understand the general sentiment with regards to the performance, the challenges and the opportunities ahead for the Indian Banking Sector. A majority of the respondents, almost 69% of them, felt that the Indian banking Industry was in a very good to excellent shape, with a further 25% feeling it was in good shape and only 6% of the respondents feeling that the performance of the industry was just average. In fact, an overwhelming majority (93.33%) of the respondents felt that the banking industry compared with the best of the sectors of the economy, including pharmaceuticals, infrastructure, etc. Most of the respondents were positive with regard to the growth rate attainable by the Indian banking industry for the year 2009-10 and 2014-15, with 53.33% of the view that growth would be between 15-20% for the year 2009-10 and greater than 20% for 2014-15. On being asked what is the major strength of the Indian banking industry, which makes it resilient in the current economic climate; 93.75% respondents feel the regulatory system to be the major strength, 75% economic growth, 68.75% relative insulation from external market, 56.25% credit quality, 25% technological advancement and 43.75% our risk assessment systems

Indias GDP has been growing at a rapid clip over the past decade and is set to growat even a faster pace in the coming decade. Financial services penetration of the Indian economy is quite low compared to even other developing economies. With majority of the Indian population mired in poverty, access to banks and financial companies is quite hard as people lack knowledge and education. Indias banks have grown at a rapid pace over the past 2 decades after the financial liberalization. However this growth has still lacked in meeting the massive demand in the need of financial intermediation. This has led to the growth onnon-banking financing companies (NBFCs) and microfinance companies. With the opening of the insurance sector, financial companies in India are set to enter a new growth phase. Major Banks in India is either state owned or previous government ownedinstitutions which have been fully privatized like ICICI and HDFC Bank. Boththe state owned banks and the private banks have managed to grow without throwing the whole system in a crisis like what has happened in the recent past in Europe and USA and in China in the 1990s.Here is a list of the 10 Major Banks in India1)State Bank of India (SBI)- SBI is Indias Largest Bank which is majority owned by the Government. The Company has a number of Subsidiaries and has been a market outperformer in recent times with Revenue of $22 Billion. The SBI has 7 subsidiaries of which 2 have been merged and5 are remaining. State Bank Bikaner Jaipur

State Bank of Hyderabad

State Bank of Mysore

State Bank of Patiala

State Bank of Travancore

2)ICICI Bank This is the largest Indian Private Bank with operations in all Financial Services Sectors. The Company has faced a bad time during the Lehman downturn but has recovered well. ICICI Bank is also strong in almost all sectors of the financial industry and has one of the strongest management teams in the country. Like HDFC Bank majority of the shareholding is held by foreign investors. The company which overextended itself in the 2007-2008 boom has now reduced the size of its risky segments and is again back on the growth trajectory.

3)HDFC Bank HDFC Bank like Axis Bank has shown remarkable growth in the last few years. The Bank which was founded by Indias largest housing finance company HDFC has assets of around $22 billion. It is the one of the best rated banks in terms of service quality and growth.

4)Punjab National Bank Punjab National Bank (PNB, is the second largest PSU bank with about 5000 branches across 764 cities. The Bank like BOB and SBI has shown good growth while at the same time managed to control bad debt.

5)Axis Bank- Axis Bank has been the best performing private bank along with HDFC Bank showing excellent growth in top line and bottom line. The Bank has been expanding into insurance and investment banking (acquired Enam).Axis Bank was formerly UTI Bank that begun operations in 1994.The Bank was promoted jointly by UTI,LIC and other state owned general insurers. One of the best Indian bank stock picks.

6)Bank of Baroda Bank of Baroda (BoB) is the third largest bank in India and is government owned like SBI and PNB. BOB as it is popularly known has shown excellent growth over the last few years and has managed to control its Non-Performing Asset (NPA).The Bank has good management and manages to earn nice interest spreads.

7)Bank of India-Bank of India (BoI)is Indias 4th largest bank, with 3374 branches, including 27 branches outside India. It was the first bank in India promoted by Indian interests to serve all the communities of India. The stock of the company has not performed as well as it peers post the Lehman crisis. It has seen its market cap decrease relative to its larger PSU Bank peers

8) IDBI Bank -Industrial Development Bank of India Limited (IDBI) is a leading public sector banks. RBI categorised IDBI as an other public sector bank. The commercial banking arm, IDBI BANK, was merged into IDBI. This PSU Bank has supposed have great potential and could be the next ICICI in the making.

9)Kotak Mahindra Bank- This is the first NBFC to convert into a bank. The bank has its origins as an investment bank and is still very strong in the capital markets. The Bank and its sister concerns are present in most of the financial segments of the market like Private Equity, Wealth Management, Broking, Investment Banking etc.

10)Yes Bank Yes Bank was founded by Ashok Kapur and Rana Kapoor. This bank though still small compared to its larger peers, has come into the top 10 due to its path breaking performance over the last few years in terms of growth. It has managed to set new standards and has broken out from the league of smaller private banks.Kerala Banking IndustryThe most essential element in the process of development and growth of the country is finance. The economy of a country becomes crippled without the flow of finance and the economic growth is stunted. Monitory resources can be channelized only with the help of a proper financial infrastructure. An effective financial system in the form of banks and financial institutions offer economical lending and borrowing.Kerala boasts of a well-developed banking infrastructure. With progressing time Kerala banking system has attained a high benchmark. Commercial, Nationalized a large number of Grameen banks have sprung up within the state. In fact there was a surge of Banks in the state following the nationalisation of the banks in1969. The State Bank of India (S.B.I.), Canara Bank and Syndicate Bank are the principal nationalized banks. The State Bank of India offers around 228 branches and the Syndicate Bank has 115 branches in the fourteen districts of Kerala. Apart from these commercial banks like Vijaya Bank, Dhanlakshmi Bank and the Federal Bank also offer commendable finance and banking facilities. Dhanalakshmi Bank offers 112 branches in the state. The Grameen Banks like SMGB and NMGB provide loans at low interest rates, special, subsidized lands and relief facilities to the local farmers and plays a great role in enhancing the agrarian productivity of the state.2.2 COMPANY PROFILEEstablished in 1985, the Kotak Mahindra group has been one of India's most reputed financial conglomerates. In February 2003, Kotak Mahindra Finance Ltd, the group's flagship company was given the license to carry on banking business by the Reserve Bank of India (RBI). This approval created banking history since Kotak Mahindra Finance Ltd. is the first non-banking finance company in India to convert itself in to a bank as Kotak Mahindra Bank Ltd. Today, we are one of the fastest growing bank and among the most admired financial institutions in India Kotak Mahindra Bank has over 335 branches and 803 ATMs, which are spread all over India, not just in the metros but in Tier II cities and rural India as well, we are redefining the reach and power of banking.

Kotak Mahindra Bank Limited (the Bank) is a commercial bank. The Bank operates in nine business segments: Treasury, Investments and Balance Sheet Management Unit includes dealing in debt, forex market, investments and primary dealership of government securities; Retail Banking includes lending, personal loans and agriculture finance, branch banking, which includes retail borrowings covering savings and branch banking network/services, including distribution of financial products, and credit cards, which includes receivables relating to credit card business; Corporate Banking includes wholesale borrowings and lendings; Vehicle Financing include retail vehicle and wholesale trade finance; Other lending activities include financing against securities and other loans; broking include brokerage income; advisory and transactional services provides financial advisory and transactional services; Asset Management include management of investments, and Insurance, which include life insurance.

Our Story

Milestones that have shaped the Kotak Mahindra Group, since 1986

Since the inception of the erstwhile Kotak Mahindra Finance Limited in 1985, it has been a steady and confident journey leading to growth and success. The milestones of the group growth story are listed below year wise2010 Ahmedabad Derivatives and Commodities Exchange, a Kotak anchored enterprise, became operational as a national commodity exchange.

2009 Kotak Mahindra Bank Ltd. opened a representative office in Dubai

Entered Ahmedabad Commodity Exchange as anchor investor.

2008 Launched a Pension Fund under the New Pension System.

2006 Bought the 25% stake held by Goldman Sachs in Kotak Mahindra Capital Company and Kotak Securities.

2005 Kotak Group realigned joint venture in Ford Credit; their stake in Kotak Mahindra Prime was bought out (formerly known as Kotak Mahindra Primus Ltd) and Kotak groups stake in Ford credit Kotak Mahindra was sold.

Launched a real estate fund

2004

Launched India Growth Fund, a private equity fund.

2003

Kotak Mahindra Finance Ltd. converted into a commercial bank - the first Indian company to do so.

2001

Matrix sold to Friday Corporation.

Launched Insurance Services.

Kotak Securities Ltd. was incorporated

2000

Kotak Mahindra tied up with Old Mutual plc. for the Life Insurance business.

Kotak Securities launched its on-line broking site.

Commencement of private equity activity through setting up of Kotak Mahindra Venture Capital Fund

1998

Entered the mutual fund market with the launch of Kotak Mahindra Asset Management Company.

1996

The Auto Finance Business is hived off into a separate company - Kotak Mahindra Prime Limited (formerly known as Kotak Mahindra Primus Limited). Kotak Mahindra takes a significant stake in Ford Credit Kotak

Mahindra Limited, for financing Ford vehicles. The launch of Matrix Information Services Limited marks the Group's entry into information distribution.

1995

Brokerage and Distribution businesses incorporated into a separate company - Securities. Investment banking division incorporated into a separate company - Kotak Mahindra Capital Company

1992

Entered the Funds Syndication sector

1991

The Investment Banking Division was started. Took over FICOM, one of India's largest financial retail marketing networks

1990

The Auto Finance division was started

1987

Kotak Mahindra Finance Ltd entered the Lease and Hire Purchase market

1986

Kotak Mahindra Finance Ltd started the activity of Bill Discounting

Kotak Mahindra Bank Ltd is a one stop shop for all banking needs. The bank offers personal finance solutions of every kind from savings accounts to credit cards, distribution of mutual funds to life insurance products. Kotak Mahindra Bank offers transaction banking, operates lending verticals, manages IPOs and provides working capital loans. Kotak has one of the largest and most respected Wealth Management teams in India, providing the widest range of solutions to high net worth individuals, entrepreneurs, business families and employed professionalsSenior Management

Core Kotak Mahindra Group team

Mr. Uday S. Kotak

Executive Vice Chairman and Managing DirectorMr. Uday Kotak, is the Executive Vice-Chairman and Managing Director of the Bank, and its principal founder and promoter. Mr. Kotak is an alumnus of Jamnalal Bajaj Institute of Management Studies.

In 1985, when he was still in his early twenties, Mr Kotak thought of setting up a bank when private Indian banks were not even seen in the game. First Kotak Capital Management Finance Ltd (which later became Kotak Mahindra Finance Ltd), and then with Kotak Mahindra Finance Ltd, Kotak became the first non-banking finance company in India's corporate history to be converted into a bank. Over the years, Kotak Mahindra Group grew into several areas like stock broking and investment banking to car finance, life insurance and mutual funds.

Among the many awards to Mr Kotak's credit are the CNBC TV18 Innovator of the Year Award in 2006 and the Ernst & Young Entrepreneur of the Year Award in 2003. He was featured as one of the Global Leaders for Tomorrow at the World Economic Forum's annual meet at Davos in 1996. He was also featured among the Top Financial Leaders for the 21st Century by Euromoney magazine. He was named as CNBC TV18 India Business Leader of the Year 2008 and as the most valued CEO by businessworld in 2010.Mr. C Jayaram

Joint Managing DirectorMr. C. Jayaram, is a Joint Managing Director of the Bank and is currently in charge of the Wealth Management Business of the Kotak Group. An alumnus of IIM Kolkata, he has been with the Kotak Group since 1990 and member of the Kotak board in October 1999. He also oversees the international subsidiaries and the alternate asset management business of the group. He is the Director of the Financial Planning Standards Board, India. He has varied experience of over 25 years in many areas of finance and business, has built numerous businesses for the Group and was CEO of Kotak Securities Ltd. An avid player and follower of tennis, he also has a keen interest in psychologyMr. Dipak Gupta

Joint Managing DirectorAn electronics engineer and an alumnus of IIM Ahmedabad, Mr. Gupta has been with the Kotak Group since 1992 and joined the board in October 1999.

He heads commercial banking, retail asset businesses and looks after group HR function. Early on, he headed the finance function and was instrumental in the joint venture between Kotak Mahindra and Ford Credit International. He was the first CEO of the resulting entity, Kotak Mahindra Primus Ltd.

Kotak Mahindra Bank has reported its results for the quarter ended Dec '11. Interest earned for the quarter was Rs 1,640.98 crore and net profit was Rs 276.08 crore. For the quarter ended Dec 2010 the interest earned was Rs 1135.40 crore and net profit was Rs 187.87 crore

Products and Services The bank offers complete financial solutions for infinite needs of all individual and non-individual customers depending on the customer's need - delivered through a state of the art technology platform. Investment products like Mutual Funds, Life Insurance, retailing of gold coins and bars etc are also offered. The bank follows a mix of both open and closed architecture for distribution of the investment products. All this is backed by strong, in-house research on Mutual Funds.

The banks savings account goes beyond the traditional role of savings, and allows us to put aside a lot more than just money. The worry-free feature of Savings Account provides a range of services from funds transfer, bill payments, 2-way sweep through our Active Money feature and much more. We can place standing instructions for investment options that can be booked through Internet or through Phone banking services. The Savings Account thus provides for attractive returns earned through a comprehensive suite products and services that offer investment options, all delivered seamlessly to the customer by well integrated technology platforms.

Apart from Phone banking and Internet banking, the Bank offers convenient banking facility through Mobile banking, SMS services, Netc@rd, Home banking and Bill Pay facility among others.

The Depository services offered by the Bank allows the customers to hold equity shares, government securities, bonds and other securities in electronic or Demat forms.

The Salary 2 Wealth offering provides comprehensive administrative solutions for Corporates with features such as easy and automated web based salary upload process thereby eliminating the paper work involved in the process, a dedicated relationship manager to service the corporate account, customized promotions and tie - ups and many such unique features. The whole gamut of investment products and investment advisory services is available to the salary account holders as well.

For the business community, the bank offer comprehensive business solutions that include the Current Account, Trade Services, Cash Management Service and Credit Facilities. The banks wholesale banking products offer business banking solutions for long-term investments and working capital needs, advice on mergers and acquisitions and equipment financing. To meet special needs of the rural market, the bank has dedicated business offerings for agricultural financing and infrastructure. Its Agriculture Finance division delivers customised products for capital financing and equipment financing needs of our rural customers.

For financial liquidity the bank offers loans that meet personal requirements with quick approval and flexible payment options. To complete the personal financial offerings space, the bank now offers Kotak Credit Card which is a hassle-free, transparent product that also happens to be the first vertical credit card in the industry.

Kotak Mahindra Bank addresses the entire spectrum of financial needs of Non-Resident Indians. The bank has tie-up with the Overseas Indian Facilitation Centre (OIFC) as a strategic partner, which gives them a platform to share their comprehensive range of banking and investment products and services for Non Resident Indians (NRIs) and Persons of Indian Origin (PIOs). Their Online Account Opening facility and Live Chat service helps to get in touch at the comfort of homes and at the convenience. These offerings are specifically designed to suit the overseas Indian's personal financial needs and give the global Indians a near to home feel.Products

TERM LOAN 1. Normal SENP& SEP 2. Net Margin3. 3 to 94. PSL / Non PSL5. PL PTR1. NORMAL SENP

Terms & Condition

Max 5 inward cheque return allowed ( 6 month bank statement)

DSCR Debt service coverage ratio- minimum 1

Business continuity 5 year

Minimum loan amount 3 lakh maximum 1 crore

Tenor minimum 12 month maximum 36 month

SEP maximum 60 month

Maximum age limit 60 years

Case update 1 month from the last approval

After 1 month update docs & CIBIL2. NET MARGIN

Business Net margin Turnover

Petrol Pump

1% 5 cr

Gas agency

2% 2 cr

Pharma

4% 1 cr

FMCG& Mbl

1% 1cr

Restaurant

10% 30 cr

Caters

10% 40 cr

Printers

4% 1 cr

Medical store / General store 10% 60 cr

Department store

10% 50 cr

Maximum Loan amount 10 lacs

Last 11 month 1 bounce

12 to 17 month 2 bounce

Above 17 month 3 bounce

Maximum age limit-65 years

Maximum 6 inward cheque return allowed ( Last 6 month bank statement) 3. 3 TO 9

Conditions

1. Minimum Business income 1.5 Lacs

2. Minimum turnover manufacture 50 Lacs

Other business normal turnover

3. Business continuity Manufactures 4 year, other 5 year

4. Past track record - 12 month existing track minimum EMI 5000

- Last 6 month closed track accepted

- Within 12 month 1 bounce

- 13 to 23 month 2 bounce

- Above 24 months 3 bounce

- Last 6 month not any bounce allowed

5. Any loan last 6 month - 5 PL allowed

1 loan last 6 month - 3 PL allowed

6. statement bounce last 6 month - 6 bounce

7. Not more than 2 PL enquiry in last one month

8. within 6 month closed track is not obligation4. PL PTR Scheme

Age Norms Min 25 Max 65

Only SENP Cases

Own Property compulsory

Minimum 3yrs BCP

6 non EMI cheque bounce is allowed in the Bank Statement.

CIBIL score should be >= 725

Max PL customer can have is 4

Approved Financiers

1. ICICI

2. HDFC

3. Citi Bank (not citi finance)

4. ABN

5. SCB

6. Reliance

7. HSBC

8. Barclays

9. Religare

10. Bajaj

1 fresh loan in last 6mts is allowed and customer shouldnt have taken any PL in last 3mts.

Minimum Original loan amount should be 5L

Minimum seasoning is 18mts and also loans matured in 3mts can be considered.

If the loan is topped up and combined seasoning is considered, then the lower EMI to be considered for eligibility.

Minimum loan amount is Rs 2.50 Lac/24M and Max is Rs 12.50 Lac/36M. The loan amount cannot exceed the original loan amount based on which the eligibility being calculated.

Maximum tenor should not exceed tenor of loan considered for eligibilityFacility against Credit Card Receivables

Avail upto Rs. 3 crores as a Business Loan

Kotak Mahindra Bank introduces a unique new product, Facility against Credit Card Receivables where under you can avail upto Rs. 3 crores as a Business Loan or have the flexibility to have some portion of the facility as an Overdraft.

It is a finance option for merchant establishments that use credit card Point of Sales (POS) machines for their daily business transactions. With this product, a merchant with a POS machine can avail of either a Business Loan or an Overdraft Facility on the basis of the yearly sales that takes place on his credit card POS machine.

1. 12 month audited credit-card sales statement

2. Basic financial documentationKey Features

Higher eligibility for Self Employed

Loan amounts up to Rs. 3 crores

Flexibility of combining Loan and Overdraft

Lower Processing Fees

Easy repayment option

Collateral free

Features & Benefits

Loan amounts up to Rs. 3 crores

Flexibility of combining Loan and Overdraft

Easy repayment option

Competitive interest rates

Quick disbursement

CHAPTER 3

REVIEW OF LITERATURE

3.1 Review of Literature

Allen and Gayle (2003) describe the most recent BIS proposals for the credit risk measurement of retail credits in capital regulations1. We also describe the recent trend away from relationship lending toward transactional lending in thesmall business loanarena. These trends create the opportunity to adopt more analytical, data-based approaches to credit risk measurement. We survey proprietary credit scoring models (such as Fair Isaac), as well as options-theoretic structural models (such as KMV and Moodys Risk Calc), and reduced-form models (such as Credit Risk Plus). These models allow lenders and regulators to develop techniques that rely on portfolio aggregation to measure retail credit risk exposure.David Blanch flow (1993) et.al investigated data from the 1993 National Survey of Small Business Finances to determine the extent to which minority-owned small businesses face constraints in the credit market beyond those faced by white-owned small businesses2. First, we present qualitative evidence indicating that black- and white-owned firms report similar concerns about the factors that may affect their businesses except that blacks are far more likely to report problems with credit availability. Second, we conduct an econometric analysis of loan denial probabilities by race and find that black-owned small businesses are almost three times more likely to have a loan application denied. Even after controlling for the differences in credit-worthiness and other factors that exist between black- and white-owned firms, blacks are still about twice as likely to be denied credit. A series of specification checks indicates that this gap is unlikely to be largely attributed to omit variable bias. Third, we conduct a similar analysis regarding interest rates charged to approved loans and find black-owned firms pay higher interest rates as well. Finally, even these results are likely to understate differences in credit access because many potential black-owned firms are not in operation due to the lack of credit and those in business may be too afraid to apply. These results indicate that the racial disparity in credit availability is likely caused by discrimination. Marc (2010) et.al explains a unique dataset comprised of small firms facing a very real, and binding, credit constraint, to question whether a corrective scheme such as the SFLGS has, in practice, alleviated such constraints by promoting access to debt finance for small credit constrained firms3. The results broadly support the view that the SFLGS has fulfilled its primary objective. It is a widely heldperception, although empirically contentious, that credit rationing is an important phenomenon in the UK smallbusiness Jimn & Sau(2004) analyses the determinants of the probability of default (PD) of bankloans4. We focus the discussion on the role of a limited set of variables (collateral, type of lender and bankborrower relationship) while controlling for the other explanatory variables. The study uses information on the more than three millionloansentered into by Spanish credit institutions over a completebusinesscycle (19882000) collected by the Bank of Spain's Credit Register (Central de Informacin de Riesgos). We find that collateralisedloanshave a higher PD,loansgranted by savings banks are riskier and, finally, that a close bankborrower relationship increases the willingness to take more risk.Scott & Aruna (2001) examines the effect of credit scoring on small-business lending for a sample of large U.S. banking organizations5. We find that credit scoring is associated with an 8.4 percent increase in the portfolio share of small-business loans, or $4 billion per institution. However, we fail to uncover any specific attributes of bank small-business credit-scoring programs that lead to this increased lending. Overall, we conclude that credit scoring lowers information costs between borrowers and lenders, thereby reducing the value of traditional, local bank lending relationships.John and Jonathan (1989) examine the first rigorous statistical test of the transaction cost models of secured debt6. Data from two samples of over 1,000 small business loans generally support the common set of predictions of these theories. The incidence of secured debt is positively related to probability of default, loan size, loan maturity, and marketability of assets. Changes in the legal and economic environment also alter firms' decisions regarding the pledging of collateral. Critics claim that theories of secured debt fail to explain the widespread use of collateral because they incorrectly predict when a loan will be securedJonathan (1986) investigate The Bankruptcy Reform Act of 1978 contains several provisions that can affect the cost of producing loansfor financial intermediaries7. In a competitive lending market the additional monitoring and expected foreclosure costs imposed by the change in the bankruptcy law should be passed on to the borrower. Using survey data from a sample of smallbusiness loansfrom commercial banks, evidence is presented that the enactment of the new law resulted in higher contract rates of interest.Jeremy Berk (2004) et.al investigates how personal bankruptcy law affects small firms' access to credit8. When a firm is unincorporated, its debts are personal liabilities of the firm's owner, so that lending to the firm is legally equivalent to lending to its owner. If the firm fails, the owner has an incentive to file for personal bankruptcy, since the firm's debts will be discharged and the owner is only obliged to use assets above an exemption level to repay creditors. The higher the exemption level, the greater is the incentive to file for bankruptcy. We show that supply of credit falls and demand for credit rises when non-corporate firms are located in states with higher bankruptcy exemptions. We test the model and find that, if small firms are located in states with unlimited rather than low homestead exemptions, they are more likely to be denied credit, they receive smaller loans and interest rates are higher. Results for non-corporate versus corporate firms suggest that lenders often disregard small firms' organizational status in making loan decisions.William and Nelson (1998) find that the use of risk rating systems is quite widespread, but that smaller banks generally have less detailed systems than do larger banks9. In addition, the new survey data allow us to assess the relationships between loan risk ratings and loan terms. Not surprisingly, riskierloansgenerally carry higher interest rates, even after taking account of other loan terms. There are more complex relationships between loan risk and other loan terms. Regression results indicate that banks of all sizes price for risk. We do not find a relationship between reported loan risk and delinquency and charge-off rates. However, this may reflect how recently the risk rating data have become available. In recent years many banks have attempted to improve the measurement and management of credit risk by assigning risk ratings tobusinessloans. Virtually all large banks now assign such ratings. However, until recently there has been little information on the use of risk ratings by smaller banks. Recent revisions to the Federal Reserve's Survey of Terms ofBusiness Lending and telephone consultations with more than 100 banks on the survey panel provide data on the prevalence and precision of risk rating systems at banks of all sizes. Frame (2004) et.al estimates that credit scoring is associated with about a $3,900 increase in small business lending per sample banking organization, per low- and moderate-income (LMI) area served, and this effect is roughly equivalent to that estimated for higher-income areas10. For our sample, this corresponds to a $536 million increase in small business credit in LMI areas in 1997 than otherwise would have been the case. This effect appears to be driven by increased out-of-market lending by banking organizations, as in-market lending generally declines. Overall, it does not appear that credit scoring has a disparate impact on LMI areas.Shelagh (2006) points out an econometric model to examine the pricing behaviour of British financial institutions with respect to key bank products/services offered to small and medium sized enterprises (SMEs) including current accounts, investment accounts,business loans, and mortgages11. A mean group approach is used on a panel of monthly data to gauge individual banks reactions to identify factors influencing the setting of deposit andloanrates, and to assess the competitive structure that best describes the UKs SME banking market. Though the results should be interpreted with caution, the empirical evidence is suggestive of a complex oligopoly. Policies directed at improving information and making it easier for smallbusinessesto change banks/accounts would reduce inertia and improve competition among financial institutions.Jalal (2001) et.al investigates a significant contribution to the financial innovation literature by examining the diffusion of a recent important innovation of the 1990s: banks' use of credit scoring for smallbusinesslending12. We examine the responses of 95 large banking organizations to a survey that asked whether they had adopted credit scoring for smallbusinesslending as of June 1997 (56 had done so) and, if they had adopted it, when they had done so. We estimate hazard and tobit models to explain the diffusion pattern of smallbusinesscredit scoring models. Explanatory variables include several market, firm, and managerial factors of the banking organizations' under study. The hazard model indicates that larger banking organizations innovated earlier, asdid those located in the New York Federal Reserve district; both results are consistent with our expectations. The tobit model confirms these results and also finds that organizations with fewer separately chartered banks but more branches innovated earlier, which is consistent with theories stressing the importance of bank organizational form on lending style. Though the managerial variables' signs are consistent with our expectations, none yields significant results.Frame (2001) et.al empirically examines the effect of the use of credit scoring by large banking organizations on smallbusinesslending in low- and moderate-income (LMI) areas13. Using census tract level data for the south-eastern United States, the authors estimate that credit scoring increases smallbusinesslending by $16.4 million per LMI area served. Furthermore, this effect is almost 2.5 times larger than that estimated for higher income census tracts ($6.8 million). The authors also find that credit scoring increases the probability that a large banking organization will make smallbusinessloansin a given census tract. The change in this probability is 3.8 percent for LMI areas and 1.7 percent for higher income areas. These findings suggest that credit scoring reduces asymmetric information problems for borrowers and lenders and that this is particularly important for LMI areas, which lenders may have historically bypassed because of their questionable economic health.Gregory (1990) describes that most commercialloansare made on a secured basis, yet little is known about the relationship between collateral and credit risk14. Several theoretical studies find that when borrowers have private information about risk, the lowest-risk borrowers tend to pledge collateral. In contrast, conventional wisdom holds that when risk is observable, the highest-risk borrowers tend to pledge collateral. An additional issue is whether securedloans(as opposed to secured borrowers) tend to be safer or riskier than unsecured loans. Empirical evidence presented here strongly suggests that collateral is most often associated with riskier borrowers, riskierloansand riskier banks.Forrest (1996) et.al explore this issue by examining how in the years before 1914 these banks treated loan applications from industrialists, specifically analysing the extent of refusals and the reasons given for refusals15. The results confirm that the banks operated their lending business within general constraints imposed by the principles of prudent banking. However, it is also clear that the banks gave very careful consideration to all applicants, applied a set of reasonable criteria, and approved the great bulk of all applications for industrial lending. English commercial banks have suffered severe criticism for their alleged failure to support industrial activity, to provide industrial finance. They are said to compare unfavourably with their European counterparts. Jays et.al describes that the unsecured enterprise loans can be procured quickly with speedy help16. So, funding company no more stays a problem. Also, you do not have to go by means of the unpleasant &amp time sucking process of finding to banking institutions, heading by way of endless identity or safety verifications. If your goal is company growth, renovation or up gradation then, you know you might be secure and well furnished for, with the alternative of unsecured business loans. The most fascinating bit is that you dont have to complacent financially to procure these loans.

Andrew Baker explains about Businesspersons, who have undergone bad credit history, also make use of this category of loans17. Such businesspersons and enterprises are known as problem cases. Failure to pay certain debts in the past leads to county court judgements, and bankruptcy, which in turn leads to bad credit history. Such businesspersons are disadvantaged in secured loan deals. Unsecured business loans however, present immense financial opportunities before borrowers; particularly where the loan amount desired is small. The amount received through unsecured business loans will be used for business commencement or expansion purposes, assets and equipment purchase and refinance, and to restructure finances. Some businesses use the loan proceeds as a working capital. Still others would use the unsecured business loan to finance a particular consignment. The repayment of this type of loan will be due immediately after the entrepreneur gets payment from the consignee, or any date decided.Todd Kalb describes about small businesses and entrepreneurs facing a perpetual lack of funds for taking their business to the next level, small business unsecured loans are the solution18.With the easy availability of unsecured loans most small businesses prefer going in for small business unsecured loans.Sometimes business owners are put off by what they perceive as slightly higher rates of interest for small business unsecured loans. Since the loan is unsecured it is natural to think that lenders use the higher rates to offset the risk involved. However in reality, these types of unsecured business loans may have lower interest rates than other types of collateralized loans, such as factoring. To put it all together you get capital without any stakes and a lot of ease. Also, you can use it in any way that you want. Now suppose you took the loan to buy some office equipment, but decided to go in for that sales program instead. The small business unsecured loan lender couldn't care less. You can spend it in any way that you want.Small business unsecured loans are similar to other loans in most other aspects, with unsecured loans not requiring collateral and with good credit you can apply now with no documented income. The loan application process is initiated by the borrower filling in the unsecured loan application, which can be done online via desktop conferencing technology. Once the application is received the lender starts to work to find more about the borrower in regards to his credit history and their financial details also decides on what they can offer to the borrower. If the borrower's requirements and the lenders offerings are in-line with each other, the deal works out and even if they are not, oftentimes the lender may make a counter offer to the borrower until they do come to equilibrium and they fall into line with each other and the loan gets approved and funded. Generally for small business, unsecured loans are approved faster compared to secured loans and this is one of the key factors that a borrower would consider when having multiple lenders offering them various types of loans. Borrowers like to have their unsecured loans available promptly.Unsecured small business loans are now in the mainstream and are considered as a regular source of acquiring finance. Unsecured loans are offered with absolutely no strings attached and the borrower is free to spend it any way they find suitable. This makes it a more lucrative proposition for the borrowers and they are increasingly using unsecured small business loans forbusiness start up, debt settlement, purchase of assets, business expansion and even working capital.

Venditto (2007) et.al discusses the Official Committee of Unsecured Creditors in the U.S19. The committee is aimed at representation and protection of the interests of unsecured creditors during the reorganization proceedings.The committee has several responsibilities including consulting with the debtor in possession about the administration of the case and investigating the debtors business finances and the desirability of continued operation.

Many people prefer to apply for unsecured loans or loans without collateral, thinking that it involves much less risk and responsibility20. While it is true that unsecured loans do not require the submission of collateral or the borrowers home property, a borrower must still take his/her repayment obligations seriously. Today, lets discuss some of the basic things about unsecured loans along with some tips on how you can a better loan deal. Compared to secured loans, loans without collateral are expected to have higher interest rates. It is very important to make sure that the rate of your unsecured loan is based on a fixed-rate system, not a variable one. A fixed-rate loan will ensure that your monthly interest will never change until your loan has been completely paid off. Lenders who extend unsecured loans offer limited loan amounts or loan value to ensure that the borrower will be capable of repayment. It is still worth the try to request your lending company for a lower interest rate especially if your credit history does show that you are credit worthy. Even if your lending company may refuse to lower your rate, you will never know until you try to negotiate. Again, make sure that the interest rate will be fixed and that there will be no hidden charges or extra fees that are not in your contract. Youll want to inquire about the different payment methods that the lender offers so you can submit your payments at your convenience. Also, a shorter repayment period may come with a slightly higher rate but in the end, your total costs will be much lower than a loan with a longer repayment period. Last but not least, see to it that you have a realistic plan in paying off your unsecured loan to avoid expensive late charges or an increased rate of interest. Borrow only the amount of money you need so that repayment will not be such a burden later on.

3.2 Theoretical Review

3.2 (A) Factor Analysis

Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved, uncorrelated variables called factors. In other words, it is possible, for example, that variations in three or four observed variables mainly reflect the variations in fewer such unobserved variables. Factor analysis searches for such joint variations in response to unobserved latent variables. The observed variables are modeled as linear combinations of the potential factors, plus "error" terms. The information gained about the interdependencies between observed variables can be used later to reduce the set of variables in a dataset. Computationally this technique is equivalent to low rank approximation of the matrix of observed variables. Factor analysis originated in psychometrics, and is used in behavioral sciences, social sciences, marketing, product management, operations research, and other applied sciences that deal with large quantities of [data.]

Factor analysis is related to principal component analysis (PCA), but the two are not identical. Latent variable models, including factor analysis, use regression modelling techniques to test hypotheses producing error terms, while PCA is a descriptive statistical technique21.

3.2 (B) Type of factor analysis

Exploratory factor analysis (EFA) is used to uncover the underlying structure of a relatively large set of variables. The researcher's a priori assumption is that any indicator may be associated with any factor. This is the most common form of factor analysis. There is no prior theory and one uses factor loadings to intuit the factor structure of the data.

Confirmatory factor analysis (CFA) seeks to determine if the number of factors and the loadings of measured (indicator) variables on them conform to what is expected on the basis of pre-established theory. Indicator variables are selected on the basis of prior theory and factor analysis is used to see if they load as predicted on the expected number of factors. The researcher's a priori assumption is that each factor (the number and labels of which may be specified a priori) is associated with a specified subset of indicator variables. A minimum requirement of confirmatory factor analysis is that one hypothesizes beforehand the number of factors in the model, but usually also the researcher will posit expectations about which variables will load on which factors. The researcher seeks to determine, for instance, if measures created to represent a latent variable really belong together.

3.2 (C) Types of factoring

Principal component analysis(PCA)

The most common form of factor analysis, PCA seeks a linear combination of variables such that the maximum variance is extracted from the variables. It then removes this variance and seeks a second linear combination which explains the maximum proportion of the remaining variance, and so on. This is called the principal axis method and results inorthogonal(uncorrelated) factors.

Canonical factor analysis

It is called Rao's canonical factoring, is a different method of computing the same model as PCA, which uses the principal axis method. Canonical factor analysis seeks factors which have the highest canonical correlation with the observed variables. Canonical factor analysis is unaffected by arbitrary rescaling of the data. Common factor analysisIt also called principalfactoranalysis (PFA) or principal axis factoring (PAF), seeks the least number of factors which can account for the common variance (correlation) of a set of variables.

Image factoring

Based on thecorrelation matrixof predicted variables rather than actual variables, where each variable is predicted from the others usingmultiple regressions.

Alpha factoring

Based on maximizing the reliability of factors, assuming variables are randomly sampled from a universe of variables. All other methods assume cases to be sampled and variables fixed.

Factor regression model

This is a combinatorial model of factor model and regression model; or alternatively, it can be viewed as the hybrid factor model, whose factors are partially known22.3.2 (D) Terminology

a) Factor loadings

The factor loadings, also called component loadings in PCA, are thecorrelation coefficientsbetween the variables (rows) and factors (columns). Analogous toPearson's r, the squared factor loading is the percent of variance in that indicator variable explained by the factor. To get the percent of variance in all the variables accounted for by each factor, add the sum of the squared factor loadings for that factor (column) and divide by the number of variables. (Note the number of variables equals the sum of their variances as the variance of a standardized variable is 1.) This is the same as dividing the factor's eigenvalue by the number of variables.

b) Interpreting factor loadings

By one rule of thumb in confirmatory factor analysis, loadings should be .7 or higher to confirm that independent variables identified a priori are represented by a particular factor, on the rationale that the .7 level corresponds to about half of the variance in the indicator being explained by the factor. However, the .7 standard is a high one and real-life data may well not meet this criterion, which is why some researchers, particularly for exploratory purposes, will use a lower level such as .4 for the central factor and .25 for other factors call loadings above .6 "high" and those below .4 "low". In any event, factor loadings must be interpreted in the light of theory, not by arbitrary cutoff levels.

In oblique rotation, one gets both a pattern matrix and a structure matrix. The structure matrix is simply the factor loading matrix as in orthogonal rotation, representing the variance in a measured variable explained by a factor on both a unique and common contributions basis. The pattern matrix, in contrast, containscoefficientswhich just represent unique contributions. The more factors, the lower the pattern coefficients as a rule since there will be more common contributions to variance explained. For oblique rotation, the researcher looks at both the structure and pattern coefficients when attributing a label to a factor.

c) Communality

The sum of the squared factor loadings for all factors for a given variable (row) is the variance in that variable accounted for by all the factors, and this is called the communality. The communality measures the percent of variance in a given variable explained by all the factors jointly and may be interpreted as the reliability of the indicator.

d) Spurious solutions

If the communality exceeds 1.0, there is a spurious solution, which may reflect too small a sample or the researcher has too many or too few factors.

e) Uniqueness of a variableThat is, uniqueness is the variability of a variable minus its communality.

f) Eigenvalues:/Characteristic roots

The eigenvalue for a given factor measures the variance in all the variables which is accounted for by that factor. The ratio of eigenvalues is the ratio of explanatory importance of the factors with respect to the variables. If a factor has a low eigenvalue, then it is contributing little to the explanation of variances in the variables and may be ignored as redundant with more important factors. Eigenvalues measure the amount of variation in the total sample accounted for by each factor.

g) Extraction sums of squared loadings

Initial eigenvalues and eigenvalues after extraction (listed by SPSS as "Extraction Sums of Squared Loadings") are the same for PCA extraction, but for other extraction methods, eigenvalues after extraction will be lower than their initial counterparts. SPSS also prints "Rotation Sums of Squared Loadings" and even for PCA, these eigenvalues will differ from initial and extraction eigenvalues, though their total will be the same.

h) Factor scores

It also called component scores in PCA. These are the scores of each case (row) on each factor (column). To compute the factor score for a given case for a given factor, one takes the case's standardized score on each variable, multiplies by the corresponding factor loading of the variable for the given factor, and sums these products. Computing factor scores allows one to look for factor outliers. Also, factor scores may be used as variables in subsequent modelling.

3.2 (E) Criteria for determining the number of factors

Using one or more of the methods below, the researcher determines an appropriate range of solutions to investigate. Methods may not agree. For instance, the Kaiser criterion may suggest five factors and the scree test may suggest two, so the researcher may request 3-, 4-, and 5-factor solutions discuss each in terms of their relation to external data and theory.

i. Comprehensibility

A purely subjective criterion would be to retain those factors whose meaning is comprehensible to the researcher. This is not recommended.

ii. Kaiser criterion

The Kaiser rule is to drop all components with eigenvalues under 1.0 this being the eigenvalue equal to the information accounted for by an average single item. The Kaiser criterion is the default inSPSSand moststatistical softwarebut is not recommended when used as the sole cut-off criterion for estimating the number of factors as it tends to overextract factors23. iii. Variance explained criteria

Some researchers simply use the rule of keeping enough factors to account for 90% (sometimes 80%) of the variation. Where the researcher's goal emphasizes parsimony(explaining variance with as few factors as possible), the criterion could be as low as 50%iv. Scree plotThe Cattell scree test plots the components as the X axis and the correspondingeigenvaluesas theY-axis. As one moves to the right, toward later components, the eigenvalues drop. When the drop ceases and the curve makes an elbow toward less steep decline, Cattell's scree test says to drop all further components after the one starting the elbow. This rule is sometimes criticised for being amenable to researcher-controlled "fudging". That is, as picking the "elbow" can be subjective because the curve has multiple elbows or is a smooth curve, the researcher may be tempted to set the cut-off at the number of factors desired by his or her research agenda.3.2 (F) Horn's Parallel Analysis (PA):

A Monte-Carlo based simulation method that compares the observed eigenvalues with those obtained from uncorrelated normal variables. A factor or component is retained if the associated eigenvalue is bigger than the 95th of the distribution of eigenvalues derived from the random data. PA is one of the most recommendable rules for determining the number of components to retain, but only few programs include this option24.

Before dropping a factor below one's cut-off, however, the researcher should check its correlation with the dependent variable. A very small factor can have a large correlation with thedependent variable, in which case it should not be dropped.

3.2 (G) Rotation methods

The unrotated output maximises the variance accounted for by the first and subsequent factors, and forcing the factors to beorthogonal. This data-compression comes at the cost of having most items load on the early factors, and usually, of having many items load substantially on more than one factor. Rotation serves to make the output more understandable, by seeking so-called "Simple Structure": A pattern of loadings where items load most strongly on one factor, and much more weakly on the other factors. Rotations can be orthogonal or oblique (allowing the factors to correlate).

i. Varimax rotation

It is an orthogonal rotation of the factor axes to maximize the variance of the squared loadings of a factor (column) on all the variables (rows) in a factor matrix, which has the effect of differentiating the original variables by extracted factor. Each factor will tend to have either large or small loadings of any particular variable. A varimax solution yields results which make it as easy as possible to identify each variable with a single factor. This is the most common rotation option.

ii. Quartimax rotation

Itis an orthogonal alternative which minimizes the number of factors needed to explain each variable. This type of rotation often generates a general factor on which most variables are loaded to a high or medium degree. Such a factor structure is usually not helpful to the research purpose.

iii. Equimax rotation

Itis a compromise between Varimax and Quartimax criteria.

iv. Direct oblimin rotation

Itis the standard method when one wishes a non-orthogonal (oblique) solution that is, one in which the factors are allowed to be correlated. This will result in higher eigenvalues but diminishedinterpretabilityof the factors. v. Promax rotation

It is an alternative non-orthogonal (oblique) rotation method which is computationally faster than the direct oblimin method and therefore is sometimes used for very largedatasetsREFERENCE

1. Linda Allen and Gayle DeLong, Issues in the credit risk modeling of retail markets, Zicklin School of Business, Baruch College, One Bernard Baruch Way, Box B 10-225, New York, NY 10010, USA, Available online 27 November 20032. David G. Blanchflower & Phillip B. Levine & David J. Zimmerman, 2003. "Discrimination in the Small-Business Credit Market," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 930-943, 09.

3. Marc Cowling, The role of loan guarantee schemes in alleviating credit rationing in the UK, Financial Stability, Volume 6, Issue 1, April 2010, Pages 36-44

4. Gabriel Jimnez, Jess Saurina, Collateral, type of lender and relationship banking as determinants of credit risk, Journal of Banking & Finance, Volume 28, Issue 9, September 2004, Pages 2191-2212

5. W. Scott Frame, Aruna Srinivasan and Lynn Woosley, Journal of Money, Credit and Banking, Vol. 33, No. 3 (Aug., 2001), pp. 813-8256. John D. Leeth and Jonathan A. Scott, The Incidence of Secured Debt: Evidence from the Small Business Community, Journal of Financial and Quantitative Analysis(1989), 24 : pp 379-3947. Jonathan A. Scott, The effect of the Bankruptcy Reform Act of 1978 on small business loan pricing, Journal of Financial Economics, Volume 16, Issue 1, May 1986, Pages 1191408. Berkowitz, Jeremy and Michelle J. White. "Bankruptcy and Small Firms' Access to Credit." RAND Journal of Economics 35, 1 (Spring 2004): 69-84

9. William B. and Nelson, William R., Bank Risk Rating ofBusinessLoan (December 7, 1998). Board of Governors of the Federal Reserve System FEDS Paper No. 98-51.

10. W. Scott Frame & Lynn Woosley, Credit Scoring and the Availability of Small Business Credit in Low- and Moderate-Income Areas, Financial Review Volume 39,Issue 1,pages 3554,February 2004

11. Shelagh Heffernan, UK bank services for small business, Finance, Volume 30, Issue 11, November 2006, Pages 3087-3110

12. Akhavein, Jalal D., Frame, W. Scott and White, Lawrence J., The Diffusion of Financial Innovations: An Examination of the Adoption of SmallBusinessCredit Scoring by Large Banking Organizations (March 2001)

13. Frame, W. Scott, Padhi, Michael and Woosley, Lynn W., The Effect of Credit Scoring on SmallBusinessLending in Low- and Moderate-Income Areas (April 2001). FRB Atlanta Working Paper No. 2001-6.

14. Gregory F. Udell, Collateral, loan quality and bank risk, Journal of Monetary Economics Volume 25, Issue 1, January 1990, Pages 214215. Forrest Capiea&Michael Collins, Industrial Lending by English Commercial Banks, 1860s1914: Why Did Banks Refuse Loans?, Business History, Volume 38,Issue 1, 1996

16. Jay,s, Unsecured business loans Effortless finance for tiny enterprise operations, Finance For A Small Business category17. Andrew Baker, Benefits of Unsecured Business Loans, EzineArticles.com Expert Author

18. Todd Kalb, Small Business Unsecured Loans, Articlesnatch.com19. Venditto, Michael, Business Credit; May2007, Vol.109 Issue 5, p6-8, 3p

20. Getting to Know Unsecured Type Loans, All Topics-Personal Finance- Financial Planning21. Bartholomew, D. J., Steele, F., Galbraith, J., & Moustaki, I. (2008). Analysis of Multivariate Social Science Data (2 ed.). New York: Chapman & Hall/Crc.

22. Meng, J. (2011). "Uncover cooperative gene regulations by microRNAs and transcription factors in glioblastoma using a nonnegative hybrid factor model". International Conference on Acoustics, Speech and Signal Processing.

23. Bandalos, D.L. & Boehm-Kaufman, M.R. (2009). Four common misconceptions in exploratory factor analysis In Statistical and methodological myths and urban legends: Doctrine, verity and fable in the organizational and social sciences. Lance, Charles E. (Ed.); Vandenberg, Robert J. (Ed.). New York: Routledge. pp. 6187.

24. Ledesma, R.D. and Valero-Mora, P. (2007). "Determining the Number of Factors to Retain in EFA: An easy-to-use computer program for carrying out Parallel Analysis". Practical Assessment Research & Evaluation, 12(2), 1-11

CHAPTER 4

RESEARCH METHODOLOGY

Descriptive research design was used for carrying out this study. This study is focused to analyse Unsecured Business Loans requirements.

4.1 Data Source Primary and secondary data was explored for the requirements of the study. The preliminary study and extensive literature review was carried out. The primary data is directly collected from the respondents using a questionnaire. The scope of Internet for collecting secondary data was also exploited. 4.2 Research Approach

Survey using a questionnaire was adopted in this study. Personal interactive method was followed with respondents to find out their requirements. The questionnaire shall be circulated to the respondents as per the research design

4.3 Research Instrument

Questionnaire was prepared with the objective of collecting all relevant information required for achieving the research objectives. Wide discussions with experts in the field of Business loans were conducted before selecting the questions and included it in the questionnaire. The prepared questionnaire was pre-tested before using the study.4.4 The Population

The population was defined as all registered SME in Ernakulum District.

4.5 Sample Size

Sample size was estimated from the list of registered SME in The Confederation of Indian Industryat Ernakulum District.

4.6 Sampling Procedure

The sample size was selected by using simple random lottery method, from the list of SME registered in The Confederation of Indian Industry at Ernakulum District.4.7 Scope

This study can be very useful for the Banks to understand how a SMEs responds for an Unsecured Business Loans and also to find out the respondents requirements while preferring an Unsecured Business Loans.4.8 Limitations All respondents may not be willing to answer and also difficulty in contacting respondentsCHAPTER-5

DATA ANALYSIS

This study was executed in all registered SME in Ernakulum District. Sample size was estimated from the list of registered SME in The Confederation of Indian Industryat Ernakulum District. Finally the sampling procedure was selected by using simple random lottery method, from the list of SME registered in The Confederation of Indian Industry at Ernakulum District.Availed Loans for Business PurposeTable-5.1 Availed loans for Business Purpose

FrequencyPercentValid PercentCumulative Percent

Yes6868.068.068.0

No3232.032.0100.0

Total100100.0100.0

Source: Survey DataFrom the table it can be concluded that, 68% of the people who are doing Business in SME opted for Business loans and 32% of the people did not opt for Business loans.

Figure 5.1First Preference for Business Loan

Table-5.2 First Preference for Business Loan

FrequencyPercentValid PercentCumulative Percent

Secured8080.080.080.0

Unsecured2020.020.0100.0

Total100100.0100.0

Source: Survey DataFrom the table it can be seen that, 80% of the people preferred Secured loans over unsecured loans. This can be because the term for secured loan is longer than that of unsecured loan and the interest rate is lower for secured loan.

Figure -5.2Cross Tabulation for Availed loans for Business Purpose and first Preference for Business Loans5.2.1 Availed loans for Business Purpose * First Preference for Business Loans Cross tabulation

First Preference for Business LoansTotal

SecuredUnsecured

Availed loans for Business PurposeYesCount501868

Expected Count54.413.668.0

% within Availed loans for Business Purpose73.5%26.5%100.0%

% within First Preference for Business Loans62.5%90.0%68.0%

NoCount30232

Expected Count25.66.432.0

% within Availed loans for Business Purpose93.8%6.3%100.0%

% within First Preference for Business Loans37.5%10.0%32.0%

TotalCount8020100

Expected Count80.020.0100.0

% within Availed loans for Business Purpose80.0%20.0%100.0%

% within First Preference for Business Loans100.0%100.0%100.0%

Source: Survey DataIt was observe that out of 68 who took business loan, 73.5% took secured loan and 26.5% took unsecured loans and out of 32 people, who took loan for other than business purpose, 93.7% took secured loans and only 6.3% took unsecured loanHypothesis

H0: There is no relationship between availed business loan and type of loan taken

H1: There is relationship between availed business loans and type of loan taken

Table 5.2.2 Chi-Square Test

ValuedfAsymp. Sig. (2-sided)Exact Sig. (2-sided)Exact Sig. (1-sided)

Pearson Chi-Square5.561a1.018

Continuity Correction4.3691.037

Likelihood Ratio6.5201.011

Fisher's Exact Test.018.014

Linear-by-Linear Association5.5051.019

N of Valid Cases100

Source: Survey DataFrom table 5.2.2 we can interpret that Chi-square test was found to be significant with is 5.561, df=1, P