artigo 1 - the innovation process under the perspective of stakeholders a sustainable development...

8/19/2019 Artigo 1 - The Innovation Process Under The Perspective Of Stakeholders A Sustainable Development Point Of Vie…

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Copyright by Global Journal of Management and Business Research 2009. All rights reserved.

This is a special issue published in version 1.0 of ―Global Journal of Management and Business Research.‖ All articles are open access articles distributedunder the Global Journal of Management and Business Research Reading License, which permits restricted use. Entire contents are copyright byof ―GlobalJournal of Management and Business Research‖ unless otherwise noted on specific articles. No part of this publication may be reproduced or transmittany form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, withou permission.The opinions and statements made in this book are those of the authors concerned. Ultraculture has not verified and neither confirms nor denies aforegoing and no warranty or fitness is implied.Engage with the contents herein at your own risk.


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John A. Hamilton,"Drew" Jr.,

Ph.D., Professor, ManagementComputer Science and Software EngineeringDirector, Information Assurance LaboratoryAuburn University

Dr. Wenying Feng

Professor, Department of Computing &Information SystemsDepartment of MathematicsTrent University, Peterborough,ON Canada K9J 7B8

Dr. Henry HexmoorIEEE senior member since 2004Ph.D. Computer Science, University at BuffaloDepartment of Computer ScienceSouthern Illinois University at Carbondale

Dr. Thomas Wischgoll Computer Science and Engineering,Wright State University, Dayton, OhioB.S., M.S., Ph.D.(University of Kaiserslautern)

Dr. Osman Balci, Professor Department of Computer ScienceVirginia Tech, Virginia UniversityPh.D.and M.S.Syracuse University, Syracuse,New YorkM.S. and B.S. Bogazici University, Istanbul,Turkey

Dr. Abdurrahman Arslanyilmaz Computer Science & InformationSystems DepartmentYoungstown State UniversityPh.D., Texas A&M UniversityUniversity of Missouri, ColumbiaGazi University, Turkey

Yogita BajpaiM.Sc. (Computer Science), FICCTU.S.A.Email: [email protected]

Dr. Xiaohong HeProfessor of International BusinessUniversity of QuinnipiacBS, Jilin Institute of Technology; MA,MS, PhD,.(University of Texas-Dallas)

Dr. T. David A. ForbesAssociate Professor and Range NutritionistPh.D. Edinburgh University - Animal Nutrition

M.S. Aberdeen University - Animal NutritionB.A. University of Dublin- Zoology.

Burcin Becerik-GerberUniversity of Southern CaliforniPh.D. in Civil Engineering

DDes from Harvard UniversityM.S. from University of California,Berkeley & Istanbul University

Dr. Bart Lambrecht Director of Research in Accounting andFinanceProfessor of FinanceLancaster University Management SchoolBA (Antwerp); MPhil, MA, PhD (Cambridge)

Dr. Söhnke M. Bartram Department of Accounting and FinanceLancaster University ManagementSchoolPh.D. (WHU Koblenz)MBA/BBA (University of Saarbrücken)


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Dr. Carlos García Pont Associate Professor of MarketingIESE Business School, University of NavarraDoctor of Philosophy (Management),Massachussetts Institute of Technology (MIT)

Master in Business Administration, IESE,University of NavarraDegree in Industrial Engineering,Universitat Politècnica de Catalunya

Dr. Miguel Angel Ariño Professor of Decision SciencesIESE Business SchoolBarcelona, Spain (Universidad deNavarra)

CEIBS (China Europe InternationalBusiness School).Beijing, Shanghai and ShenzhenPh.D. in MathematicsUniversity of BarcelonaBA in Mathematics (Licenciatura)University of Barcelona

Dr. Fotini Labropulu Mathematics - Luther CollegeUniversity of ReginaPh.D., M.Sc. in MathematicsB.A. (Honors) in MathematicsUniversity of Windsor

Philip G. MoscosoTechnology and OperationsManagementIESE Business School, University ofNavarraPh.D in Industrial Engineering andManagement, ETH ZurichM.Sc. in Chemical Engineering, ETHZurich

Dr. Lynn Lim Reader in Business and MarketingRoehampton University, LondonBCom, PGDip, MBA (Distinction), PhD, FHEA

Dr. Sanjay Dixit, M.D. Director, EP Laboratories, PhiladelphiaVA Medical CenterCardiovascular Medicine - CardiacArrhythmiaUniv of Penn School of Medicine

Dr. Mihaly Mezei ASSOCIATE PROFESSORDepartment of Structural and ChemicalBiology

Mount Sinai School of Medical CenterPh.D., Etvs Lornd UniversityPostdoctoral Training, New York University

Dr. Han-Xiang Deng MD., Ph.DAssociate Professor and ResearchDepartment

Division of Neuromuscular MedicineDavee Department of Neurology andClinical NeurosciencesNorthwestern University FeinbergSchool of Medicine


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Dr. R.K. Dixit (HON.)M.Sc., Ph.D., FICCTChief Author, IndiaEmail: [email protected]

Vivek Dubey (HON.)MS (Industrial Engineering),MS (Mechanical Engineering)

University of WisconsinFICCTEditor-in-Chief, [email protected]

Er. Suyog Dixit BE (HONS. in Computer Science),FICCT

SAP Certified ConsultantTechnical Dean, IndiaWebsite: www.suyogdixit.comEmail:[email protected],[email protected] Dixit

M.Sc., FICCTDean and Publisher, [email protected]


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i. Copyright Noticeii. Editorial Board Members

iii. Chief Author and Deaniv. Table of Contentsv. From the Chief Editor’s Desk

vi. Research and Review Papers

1. Venture Capital Financing In India: Path of Differential Diffusion Trajectory A Comparison with the USA 2-10

2. Modelling Armed Robbery Crime Insurance Claims in Nigeria11-20

3. Promoting an Emerging Tourism Destination 21-28 4. Are the Global Stock Markets Inter-linked? Evidence from the Literature 29-40 5. Critical Service Encounters: The Employee’s Viewpoint (A Study on Restaurant Services in Dhaka City) 41-47 6. Reliability and Availability Based Hybrid Flow Shop Scheduling Using Fuzzy Logic 48 -55 7. Financial Liberalisation Policy for Fostering Credit to the Private Sector in Nigeria for Economic Growth 56-65

8. Oil Politics and the Crisis of Development in the Niger Delta 66-73 9. Eccentric Turnover Behavior among the Working Students of Pakistan 74-80 10. Impact of Brand Placement in Films- A Viewer’s Perception 81-87 11. Regulating Bank Systemic Risk: New Principles in Macroprudential Management 88-96 12. Clinical Trials: A Branding Opportunity? 97-103 13. Strategies to Increase E-Government Take-Up: Looking Beneath Statistics 104-114 14. The Innovation Process under the View 115-122 15. Knowledge Management: Promises and Premises 123-131 16. The Role of Life Skills Training on Self-Efficacy, Self Esteem, Life Interest, and Role Behavior for Unemployed Youth 132-139 17. Assessing of the SME’s Financial Competitiveness 140 -147 18. A Study of the Integrity of Internet Financial Reporting: Empirical Evidence of Emerging Economy 148-158 19. Brand Decisions and Brand Influence: A Comparison of Rural and Urban Consumers 159-171


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20. Management of the Modernization Projects from the Technical-Economic Systems 172-175 21. Sensitivity and Uncertainty Analysis: Applications to Small-land Scale Agriculture Systems in Nigeria 176-183

vii. Auxiliary Membershipsviii. Process of Submission of Research Paper

ix. Preferred Author Guidelinesx. Index


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P a g e | 1 Vol. 10 Issue 1 (Ver 1.0), January2010 Global Journal of Management and Business Research

he research activities among different disciplines of natural science are backboneof system. The deep and strong affords are the demands of today. Sincere affordmust be exposed worldwide. Which, in turns, require international platform for

rapid and proper communication among similar and interdisciplinary research groups.

The Global Journal of Management and Business Research is to fulfill all such demandsand requirements, and functions also as an international platform. Of course, thepublication of research work must be reviewed to establish its authenticity. This helps

to promote research activity also. We know, great scientific research have been workedout by philosopher seeking to verify quite erroneous theories about the nature ofthings.

The research activities are increasing exponentially. These great increments requirerapid communication, also to link up with others. The balanced communication amongsame and interdisciplinary research groups is major hurdle to aware with status of anyresearch field.

The Global Journals is proving as milestone of research publication. In view of wholespectrum of Knowledge, the research work of different streams may be considered asbranches of big tree. Every branch is of great importance. Thus, we look after thecomplete spectrum as whole. Global Journals let play all the instrumentssimultaneously. We hope, affords of global Journals will sincerely help to build theworld in new shape.

Dr. R. K. DixitChief [email protected]

T


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Global Journal of Management and Business Research Vol. 10 Issue 1 (Ver 1.0), Febuary 2010 P a g e | 2

Venture Capital Financing In India: Path ofDifferential Diffusion Trajectory A Comparison

with the USADr. Chimun Kumar Nath Lecturer, Department of Commerce,Dibrugarh [email protected]

Dr. A. SahaReader,Department of Commerce,Dibrugarh [email protected][email protected]

Abstract- Purpose- To compare between the recent US venturescapital financing (VCF) to that of Indian VCF. The paper alsoattempts to extract perceptional di fferences between the FI’stowards VCF operating in the country.

Design/methodology/approach- A comparison of VCFbetween US operations and Indian operations in this contexthas been pursued. 2 Indian states i.e. Karnataka and Assamhave been studied on various aspects of VCF, followed bycomparing the findings there from with that of US findingsbetween the periods ranging from 1990 to 2006.

Findings- It is observed that convergence of VCF maturityin US and acceleration of growth of Indian VCF has beenattained during 1990s. Despite a discernible growth of VCF inIndia since 2000 onwards, venture capital investments inenterprises both in the early and the expansion stages has beensignificantly less diffusive than that of the US.

Research Limitations/ Implications- the study hasconsidered 6 VCFs and 12 VCFs from Assam and Karnatakarespectively out of 56 VCF entities in India recognized bySEBI.

Originality/Value- the paper signifies the operationaldifferences in US and India in the context of VCF. The inputfrom US study however, can be used to improve the modalitiesof operation in India.

Paper Type- Review of literatures and field survey. Keywords- venture capital, Venture Capital Financing(VCF), equity investment, India, United States, Karnataka,Assam

I PROLOGUE

here are many definitions of venture capital. However,the present researchers accept the simple definition that

states Venture capital as the risky capital collected throughdifferent sources to invest alongside management in rapidlygrowing industries. Venture capital is often referred to as a prerequisite for productivity and employment growth. Inline with the American tradition, as an experiencedintermediary, the venture capitalist, understands venturecapital as offering financial means to young high-technologyenterprises in combination with management support forthese enterprises. Investments by a venture capital fund cantake the form of either equity participation, or a combinationof equity participation and debt obligation - often withconvertible debt instruments that become equity if a certainlevel of risk is exceeded. In most cases, the venturecapitalist becomes part owner of the new venture. Someinvestments are structured as debt to equity participation -often reserved by covenant for a future buyout. Venturecapital investment criteria usually include a planned exit

event (an IPO or acquisition), normally within three to sevyears.The role of venture capital in facilitating employment a productivity growth has made venture capital a major tarof financial market policies by the government of IndThey attempted to ease the access to equity capital fyoung high-technology enterprises by improving thregulatory conditions the venture capitalists face in thIndian markets and by granting different subsidies.The US venture capital financing size can serve as benchmark for the discussion of the development in tIndian size of VCF. In the US, venture capital i predominantly invested in relatively young, high technoloenterprises. During the 1990s, pension funds were the macapital provider to venture capital funds. These funds wemanaged by independent venture capitalists that are oftspecialized on particular stages of enterprises‘ developmentand/or particular technologies.The size of Indian venture capital financing, are relativesmaller as compared to the US size. This follows from tcomparisons of investments in young enterprises and froinvestments in particular high technology areas in IndUntil 1990, banks were the main sources of financing heOnly at the beginning of the new millennium, thimportance of pension funds increased in most parts of tworld. In India, venture capitalists are often dependent their capital providers. Especially banks prefer to invest their own subsidiaries and not in an independent ventucapital fund.Moreover, this paper also investigate whether FIs as venture equity investors acting in a particular nationmarket differ significantly with respect to investmestrategies using a collection of primary data of FIs of Assaand Karnataka. This is important because many stagovernments of India like Gujarat, Maharastra etc. haintroduced specific policies to stimulate venture capitactivity, which cannot be identified in aggregated data VCF activity in India.The paper proceeds with a description of the Key facts the US venture capital market. In the next section, thdevelopment, of Indian VC market along with two Indiregional VC environments have been examined with respto the funds raised, investments, and impact of Human aSocial Capital in formation of VC and finally compared wthe US venture capital market. All these discussions aranging from 1990 to 2006. Last section summarizes tfindings.

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mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


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II THE US MARKET OF VENTURECAPITAL FINANCE

The venture capital market in the US is the oldest and mostdeveloped of the world and is therefore chosen as the benchmark for the analysis of the Indian market. In theAmerican tradition, which is used here, venture capitalfinance denotes the simultaneous offering of financial meansand management support for a certain area of young high-technology firmsi. Venture capital funded companies are anintegral part of the American economy. The dollars andcents contribution of the venture capital industry goes well beyond the objective economic contribution. It continuallyreinforces America‘s entrepreneurial spirit. In addition, in sodoing, the venture capital industry becomes a catalyst forchange. Venture capitalists, many of whom are successfulformer entrepreneurs themselves, shepherd new businesspersons and women to reach their full potential.The late 1980s marked the transition of the primary sourceof venture capital funds from wealthy individuals and

families to endowment, pension, and other institutionalfunds. The surge in capital in the 1980s had predictableresults. Returns on venture capital investments plunged.Many investors went into the funds anticipating returns of30 percent or higher. That was probably an unrealisticexpectation to begin with. The consensus today is that private equity investments generally should give the investoran internal rate of return something to the order of 15 percent to 25 percent, depending upon the degree of risk afirm takes.However, by 1990, the average long-term return on venturecapital funds fell below 8 percent, leading to yet anotherdownturn in venture funding. Disappointed families and

institutions withdrew from venture investing in phasesduring the 1989-91 periods. The economic recovery and theIPO boom of 1991-94 had gone a long way towards

reversing the trend in both private equity investme performance and partnership commitments.In 1998, the venture capital industry in the United Statcontinued its seventh straight year of growth. It raiseUSD25bn in committed capital for investments by ventufirms, who invested over USD16bn into domestic growcompanies in all sectors, but primarily focused o

information technology.This potential can be seen in the growth of sales figures fthe US. From 1992 to 1998, venture-backed companies stheir sales grow, on average, by 66.5 per cent per annum against five per cent for Fortune 500 firms. The expogrowth by venture-funded companies was 165 per cent. Ttop ten US sectors, measured by asset and sales growtwere technology-related.Thus, venture capital is valuable not just, because it makrisk capital available in the early stages of a project, but a because a venture capitalist brings expertise that leads superior product development. The big focus of ventucapital worldwide is, of course, technology. So in 1999,

USD30bn of venture capital invested in the US, technolofirms received approximately 80 per cent. In addition to thhuge supply of venture funds from formally organizventure capital firms, is an even larger pool of angel seed/start-up funds provided by private investors. In 199according to estimates, approximately USD90bn of anginvestment was available, thus making the total ‗at -risk'investment in high technology ventures in a single yeworth around USD120bn.Pension funds have been the main capital providers venture capital funds (limited partnerships), whicorporations, and financial and insurance have playedminor role (Exhibit 1). Pension funds contributed betwe

35 and 60 per cent of the new funds raised between 19and 1998. In 1999, however, only 23 per cent of the capiwas contributed by pension funds.

Exhibit 1: Sources of New Funds and its Allocation in the US*

*Compiled from the original table source: European new funds raised and exchange rates are from EVCA 1991 – 2000,US new funds raised are from NVCA (2000), consumer

price indices are from International Financial Statistics CD ROM IFS (2000). The 1980 ‗Safe Harbor‘ Regulation further improved theconditions for venture capital committed by pension fun

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999


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because it defined pension funds as limited partners, whichreduced the risk exposure of venture capitalists. These actshad clearly a considerable impact for the upswing in venturecapital activity at the beginning of the 1980s. Especially pension funds and their de-regulation seem to have played asignificant role in the development of the US venture capitalmarket.

This extraordinary boom during the 1990s is not the firstsignificant change that the American market for venturecapital has experienced since its humble beginnings in the1930s. Two upswings of venture capital activity can beidentified in the time series. The first upswing took place inthe mid- 1960s, the second at the beginning of the 1980s.Both upswings, however, in the US, new funds raised for private equity grew at a lower rate than new funds raised forventure capital are small compared to the increase in venturecapital activity at the end of the 1990s. The first twoupswings seemed to be influenced by public policies2.The journal ‗Venture Economics‘ had identified two reasonsfor the extraordinary boom in the investments in enterprises‘

early and expansion stages at the end of the 1990s (BVK2001)3. Venture capital funds brought their passive investorshigh returns, resulting in a considerable re-investment ofmoney; especially institutional investors reinvested largeamounts of their funds. Secondly, the development of stockmarkets resulted in a restructuring of institutional investors‘ portfolios so as to invest more money in venture capitalfunds.4 Thus, the US government also supports the creationof venture capital companies.California, Texas, Massachusetts, Washington, andPennsylvania topped the list of states by sales of venturecapital backed firms headquartered in the State by 2003.Venture capital backed companies headquartered in

California were responsible for USD438 billion in sales in2003. In Texas, venture backed sales reached nearlyUSD190 billion in 2003 and exceeded USD100 billion inMassachusetts. Other leading states measured by venturecapital backed firms sales were Washington, at slightly morethan USD100 billion, and Pennsylvania, at USD 94 billionin 2003. (Exhibit 2)Venture capital funded companies were directly responsiblefor more than 10 million jobs and $1.8 trillion in sales in2003. This corresponds to 9.4 percent of total U.S. privatesector employment and 9.6 percent of company sales. Thisis impressive given that venture investment was less thantwo percent of total equity investment for most of the past

34 years. Venture Capital Backed Firms Outperform OtherCompanies Venture backed firms added some 600,000 net jobs to the U.S. economy between 2000 and 2003.Venture supported firms such as ebay, Google, and JetBlueare just three examples of the many successful ventured businesses that have hired hundreds of new employees overthese three years.

Exhibit 2: State Wise Classification of Turnovers by VCBacked Firms in US

Source: Global Impact 2004, v.18, no.3In the first quarter of 2007, venture capitalists investUSD7.1 billion into 778 deals, the highest quarterly dolamount since the fourth quarter of 2001, according to tMoneyTree Report by Price Waterhouse Coopers and t National Venture Capital Association based on ThomsFinancial data. Deal volume actually declined in the quarcompared with the fourth quarter of 2006, indicating ventucapitalists‘ willingness to put more dollars into each round.The Life Sciences sector (Biotechnology and MedicDevices together) had an extremely strong quarter, wiBiotechnology ranked as the number one industry finvestment, while Medical Devices was at an all-time higLater Stage investing also jumped in the quarter to thighest dollar level since the fourth quarter of 2000. Firtime financings remained relatively steady, increasinslightly over last year. Medical Device investinskyrocketed to an all-time high in the first quarter, wiUSD1.08 billion going into 96 deals, a 60 percent increain dollars over last quarter 2006. Biotechnology was tsingle largest industry sector with USD1.5 billion going in102 deals, unseating software, which was traditionally tlargest sector. Life Sciences accounted for 36 percent of tquarter‘s dollars, an all -time high.

III THE INDIAN MARKET OF VENTURECAPITAL FINANCE

In the early 1980s, the idea that venture capital might established in India would seem to be fuzzy. India hhighly insulated economy, avowed pursuit of socialismquite conservative social and business perception, andrisk-averse financial system provided little institutionspace for the development of venture capital. With the hilevel of government involvement, it is not surprising that t


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first formal venture capital organizations began in the publicsector.The 1980s were marked by an increasing disillusionmentwith the trajectory of the economic system and a belief thatliberalization was needed. Prior to 1988, the Indiangovernment had no policy toward venture capital. In 1988,the Indian government issued its first guidelines to legalize

venture capital operations, Ministry of Finance (19885

).These regulations were aimed at allowing state-controlled banks to establish venture capital subsidiaries, though it wasalso possible for other investors to create a venture capitalfirm. There was only minimal interest, however, in the private sector in establishing a venture capital firm, Rameshet al. (19956)In the late 1990s, the Indian government became aware ofthe potential benefits of a healthy venture capital sector.Thus in 1999 a number of new regulations were introduced.Some of the most significant of these related to liberalizingthe regulations regarding the ability of various financialinstitutions to invest in venture capital. Perhaps the most

important of these went into effect in April 1999 andallowed banks to invest up to 5% of their new fundsannually in venture capital. Until 2001, however, they hadnot made any venture capital investments. This is notsurprising since bank managers are rewarded for risk-averse behavior. Lending to a risky, fast-growing firm could beunwise because the loan principal is at risk while the rewardis only interest.7 In such an environment, even if bankerswere good at evaluating fledgling firms, itself a dubious proposition, extending loans would be unwise. This meantthat since banks control the bulk of discretionary financialsavings in the country, there is little internally generatedcapital available for venture investing.

From 2000 onwards, the venture capital industry has madean enormous contribution to the high-technology industry.In turn, high technology has furthered national productivity.The three percent annual growth rate in productivity since1996 in the US, stems from investments in a range oftechnology industries such as computers, software, andcommunications equipment. It has helped user industrieslike retailing, airlines, and manufacturing to be more productive. By 2000 some new countries has emerged in thefield of VCF. India is a country where the VCF penetrationwas although taken place lately, but by 2002, it has attainedthe coveted list of top twenty countries based on investmentcriteria (Exhibit 3)

Exhibit 3: The World View: Top 20 Countries in 2002 &2001 - Based on Investment

Source: AVCA report, 2003

The Indian government has reiterated its commitment to tIndian software-driven IT industry by creating a NationVenture Capital Fund for the Software and IT Industr(NFSIT). NFSIT, set up in association with various financinstitutions and the industry, operates under the umbrella the Small Industries Development Bank of India (SIDBThe objective of the fund is to encourage entrepreneurshin the areas of software, services, dot.com and other Irelated sectors in which India has inherent as well acquired competency. The fund is expected to be a kecomponent in addressing the rapidly growing demand fventure capital in India. The fund will be looking supporting entrepreneurship in high growth sectors.Many state governments have already set up venture capifunds for the IT sector in partnership with local sta

financial institutions and SIDBI. These include AndhPradesh, Karnataka, Delhi, Kerala, and Tamil Nadu. With much of changes happening around venture capitfinancing in India yet, the fruitful result of exploring tadvantages of such financing has not been equaldistributed among the states in India. It is a fact that certastates like Maharashtra, Gujarat, Karnataka and AndhPradesh are far more advanced in mobilizing the ventucapital funds rather than the rest of the country. Especialstate like Karnataka is on the launching pad; thanks to tinformation technology advancement.The picture of venture capital financing is gloomier in ent North Eastern Region in general and Assam in Particul

Although it has been recognized several times that an business running in the North Eastern Region comparatively risky proposition due to its geographiclocation, environment, the infrastructural bottlenecks, e but there are hardly any venture capital environment beideveloped around this place. There is an urgent need beifelt to uncover why the entrepreneurs in this part of Ind possess an averse attitude towards venture capital financi- whether they do not have innovative ideas (in the form new technology) or other factors governing the growth adevelopment of human and social capital or the investienvironment of the region is a deterrence.


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IV THE VCF ENVIRONMENT OF ASSAM AND KARNATAKA

By considering the above factors, a research observationwould be to look into the problem of Venture Capitalgrowth in Assam. At the same time, it is noteworthy to graspsome more information about the growth of Venture Capitalin some of the advance states of India where VCF has taken

place in large numbers. In India, Maharastra is the leadingstate in terms of Venture Capital movement followed byGujarat, Tamil Nadu and Karnataka8 Karnataka happens to be the state where it has been observed that, before theinformation technology (IT) revolution since 1995 onwards;there was negligible diffusion of venture capital funding9.Predominantly having an agro- based economy, Karnatakahas shifted their focus from Agriculture to IT and IT enabledservices during the first generation of reforms and hasstarted enjoying the benefits during the second-generationreforms starting from 1995 onwards. So far, it has also beenobserved that the other top positioned states in terms of VCF penetration differ in characteristics as compared to Assam.

Thus, the study has attempted to gather the experiences ofKarnataka in the direction of VCF development to suggest acomprehensive methodology of VCF development in Assamas because Assam is still an agrarian economy like pre 1995Karnataka.Even after having rich natural and other resources, Assamhas witnessed very poor development of venture capitalgrowth. It has been observed that the impact of Social andHuman Capital on venture capital needs to be considered asa source of funding for young high-technology enterprisesand in the Karnataka market the presence of social andhuman capital paves the way for formation of financialcapital, which ultimately develops the venture capital

market positively. The differences between equity investorsacting in a single state market are of special interest, sincetheir likely heterogeneity is important when interpretingaggregated data on investments or on new funds raised, because this heterogeneity may imply significant differencesin the quality of capital offered. The study was carried out by approaching 12 financial institutions offering venturecapital in Karnataka and six financial institutions that aresponsors of venture capital but having the business ofconventional financing in Assam. These financialinstitutions engaged in the business of conventionalfinancing in Assam have been financing venture capitalthrough their subsidiaries or through a separate fund created

exclusively for the purpose in Karnataka and some otherstates in India. Data have been collected by way ofcanvassing a questionnaire amongst the respondents andanalyses have been pursued based on the feedback therein.It was observed from the study that the formation offinancial capital in the state of Assam suffers due to some poor record of accomplishment of repayments inconventional type of loans. This creates a sense of lack ofconfidence among the Financial Institutions in the statetowards the budding entrepreneurs. At the same time inorder to protect their risk involvement in financing a projectto get the repayment on time, the Financial Institutions prefer to finance only those projects, which are backed by

some existing successful enterprises. This could be of aform like experienced entrepreneurs, entrepreneurigenerations, conventional type of business where a steaearning can be obtained, or stake of successful businehouses in the proposed enterprise. Such an attitude thou provides a good support for the Financial Institutions safeguard their business risk but it also left behind ma

negative impacts. One of them could be in terms formation of Venture Capital Financing. Because VentuCapital Financing is generally provided to a sunrise indushaving no experience of any actual performance unless itstarted and/or to those entrepreneurs who have for the fitime ventured into the project. Such conceptual conflict ahas some negative impact on the budding entrepreneurs they were deprived of getting their venture financed.It was observed from the study that the formation of HumCapital in the state of Assam in comparison to Karnatakasomewhat unorganized. However, Assam has enoug potentiality to form such Human Capital but due to tinformation asymmetry, the proper development of suc

capital is not there in the state at present. At the same timthe brain drainage could be another problem patronizing tlow formation of Human Capital in the state. However,detailed analysis as to why such problems exist in the stareveals low formation of Social Capital. Interestingly, case of Karnataka it was found that the Financial Institutioare least bothered to analyze the human capital whireceiving a proposal as such because the Social Capital the state is of high quality.It was also observed that, as a compensating strategy thentrepreneurs can adopt, is to have a wide range of contain their social networks. Research also showed that whnetworks contain people from a verity of work backgroun

especially those beyond the immediate work group, thtended to be more powerful (Blauet al 1982)10 In Karnatakamarket, it is seen that most of the IT based VC receivers a previously having working experience mostly in the SilicValley as highly paid executives. There is a positivrelationship between prior work experience and ventusurvival and success, it was proved once again in the staespecially in IT, and IT enabled Venture Capital FinancinThus, network diversity enhances the chances of accessingwide array of resources. However, the likelihood that tcontacts will deliver value or resources depends on thstrength of the tie, or the nature of the relationships betwethe network members. Individuals draw instrument

resources like materials and physical resources, as well expressive resources such as friendship, mutual trust, frotheir network contacts. In case of Karnataka, it seems ththe financial institutions were keen in financing VC as t presence of social and human capital are there among tentrepreneurs. Apart from education and training, humcapital derives from work environment (Carteret al. 1997)11 and social capital derives from social environment. Karnataka, such environment is created not only from tefforts of people of the state but also by the government.However, in Assam due to the information asymmetry, bradrainage, as well as absence of social network, thentrepreneurial development in the state is not proper. T


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governmental effort receives lesser success due to creationof a negative atmosphere in developing entrepreneurialskills among the youths. A financially disciplined approachis necessary for Venture Capital Financing, which is missingin the state.An interesting finding by studying both the states is that bootstrapping and loan financing provide a foundation for

gaining experience and legitimacy that position ventures tosecure equity financing. From the study it was observed thatin Karnataka, almost all the Financial institutions weredoing equity financing and for that they consider only the presence of Human and Social capital. However, in Assam,the loan financing itself gives such a gloomy picture to thefinancial institutions as it was found that the majority of therepayment scenario for the conventional loans in the state isvery poor. Under the circumstances, an equity financingcould turn out to be a daydream. It can also be inferred thatsince the human as well as social capital formulation in thestate is very low, the financial institutions are not interestedto go for Venture Capital Financing.

The study reveals that there are many factors, which have anadverse impact on the venture capital financing in Assam.At the same time if it is looked from the business potentiality and that too for growing up a considerableventure capital market, the state of Assam can providecertain opportunities also. It has a Strategic location - accessto the vast domestic and South Asian market. Assam has alarge and rapidly growing consumer market; constitute themarket for branded consumer goods - estimated to begrowing at 8% per annum. Demand for several consumer products is growing at over 12% per annum. Assam is oneof the largest agro based sectors in the world in terms of Tea production. An R&D investment in this sector may bring

many innovations that may lead to create many sunriseindustries. Assam has one of the pools of scientists,engineers, technicians, and managers in certain specificareas in the country having IIT, RRL, AgricultureUniversity, B-Schools etc. Assam has a potential R&Dinfrastructure and technical and marketing services for biotech sector. The state/ Central government has created policy environment that provides freedom of entry,investment, location, choice of technology, production,import and export. There is a well-balanced package offinancial institutional incentives, Free, and full repatriationof capital, technical fee, royalty, and dividends. There is noincome tax on profits derived from export of goods.

Complete exemption from Customs Duty on industrialinputs and Corporate Tax Holiday for five years for 100 percent Export Oriented units & units in Export ProcessingZones may makes the environment a Venture capitalfriendly one provided the entrepreneurs of the region shouldcome up to capitalize it. The information asymmetry presently exist in Assam should be reduced and thedemonstration effect of Venture Capital Financing must be properly communicated to the entrepreneurs. The security ofinvestment must be protected by way of mutual dependence between the demand and supply side. Role of NGOs cannot be ignored in creation of social capital. At the same time, themutual trust between the entrepreneurs and the financial

institutions must be created so that the Venture CapitFinancing gets momentum. An intervention from stagovernment machineries is necessary for creation of soccapital.In Assam, the concept of supporting entrepreneurs aninnovators with Venture Capital funds has not yedeveloped. Even though development funds have be

available from various Financial Institutions anDevelopment Banks, they are largely to support provtechnologies whether indigenously developed or importeSupport by funding "Home grown technologies" aavailable though Government and other sources they stfollow the pre-condition of having validated the technolo but at least at the laboratory scale, if not in the Pilot PlaEven today, most of the Venture Capital Companies whethattached to large financial institutions such as IDBI or ICIor to State and Central Governments are varying supporting very early stage projects, which are at an R&stage, primarily due to the fear of failure. In Assam, therean urgent need to develop a Financial Institution, which w

work exclusively to promote Venture Capital Financing the state. The AIDC in collaboration with other FinancInstitutions can create such fund to facilitate the ventucapital growth in the state. A combination of Equity aDebt financing support could be the ideal form of VentuCapital Financing in the state. The VCF prospects in tstate include equity support to Pharmaceutical industry, enabled industry, indigenous engineering process in OTea, Natural Gas production, Carbon based industrieexclusive SME financing etc. It is only when the humasocial and financial capital will meet together to haveconducive atmosphere for Venture Capital Financing growin the state.

V COMPARISON OF US AND INDIANVCF MARKET

India is a significant case study in VCF penetration fornumber of reasons. First, in contrast to the United StateIndia had a history of state-directed institutiondevelopment that is similar, in certain ways, to sucdevelopment in Japan and Korea, with the exception thideologically the Indian government was hostile capitalism prior to 1991. In the United States, ventucapital is only a small component of the much largnational innovation system (NIS), and as such is depende

on many other institutions. In the United States and in Indthe development of venture capital has been a cevolutionary process. This is particularly true in Indiwhere it remains a small industry precariously dependeupon other institutions, particularly the government, aexternal factors such as international lending agencieoverseas investors, and successful Indian entrepreneurs Silicon Valley. The growth of Indian venture capital must examined within the context of the larger political aneconomic system in Indiaii. As was true in other countrithe Indian venture capital industry is the result of aiterative learning process, and it is still in its infancy. If it


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to be successful, it will be necessary not only for it to grow, but also for its institutional context to evolve.In sharp contrast to the United States, however, where aventure capital fund can invest in any industry it wishes, inIndia only six industries have been approved for investment:software, information technology, pharmaceuticals, biotechnology, agriculture, and allied industries during 1990

until 2001. Statutory guidelines also limited investments inindividual firms based on the firm‘s and the fund‘s capital.The result of these various regulations has been a channelingof venture capital investment toward late-stage financing.After a lot of debate finally, the SEBI regulations did nothave any sectoral investment restrictions except to prohibitinvestment in financial services firms and of late investmentin real estate. Impediments to the development of venturecapital also exist in India‘s corporate, tax, and currencylaws. India‘s corporate law did not provide for limited partnerships, limited liability partnerships, or limitedliability corporations (LP, LLP, and LLC, respectively) asavailable in USA.

Moreover, Indian regulations did not recognize limited lifefunds, so in India, it was relatively easy to terminate a trust, but this meant that the entire firm was closed rather than aspecific fund within the firm. Therefore, each fund had to becreated as a separate trust or company. This process wasadministratively and legally time-consuming. Terminating afund was even more cumbersome, as it requires courtapproval on a case by- case basis. The restrictions onventure capital extend beyond the framework of corporatelaw.The largest single source of funds for US venture capitalfunds since the 1980s has been public and private sector pension funds. In India, there are large pension funds but

they are prohibited from investing in either equity or venturecapital vehicles, thus closing off this source of capital. Insummation, prior to the late 1980s, though India did have avibrant stock market, the rigid and numerous regulationsmade it nearly impossible for the existing financialinstitutions to invest in venture capital firms or in startups.Investors amenable to purchasing the equity in early stagecompanies. It was also possible to bootstrap a firm and/orsecure funds from friends and family — if one was wellconnected. However, no financial intermediariescomfortable with backing small technology-based firmsexisted prior to the mid-1980s. It is safe to say that littlecapital was available for any entrepreneurial initiatives. An

entrepreneur aiming to create a firm would have to drawupon familial capital or bootstrap their firm.An interesting observation between the two countries is thatthere is a surge in risk capital by 2004 onwards. The spreadof growth of such capital is outside the informationtechnology sector. The two of the three biggest deals of2003 in India had nothing to do with technology. One wasCDC‘s $57 million investment in Punjab Tractors and theother was Warburg‘s $50 million deal with RadhakrishnaFoodland. Henceforth the important point to reallyconcentrate here as to why the sudden diversification ofopportunities occurred in India. At the same time, the USmarket also witnessed shifting of priorities from IT to

biotech by 2003 onwards. One may blame it on India‘shappy growth story as the economy is clipping at 7 perce plus and could possibly gather more steam. On the othhand, outsourcing has become a major movement acrosectors- from IT to BPO to automotive to textiles Pharmaceuticals – and on the other, smaller but strategiccompanies, especially in FMCG, are racking up stunni

growth thanks to their low cost, high quality strategy. Sudevelopments in IT sector in Indian market have downswing of VCF growth in certain states, which atraditionally IT, backed like Karnataka and Andhra PradesHowever, these states have shifted its gear to adopt variosectors to be incorporated in their priority list.

VI SUMMARY

The above section has analyzed the differences ansimilarities between the markets for Venture Capital in Indand the United States. In the American tradition, ventucapital comprises management support and financial mea

for a subset of young high-technology enterprises provid by experienced intermediaries, i.e. the venture capitalisDue to data limitations, all the results obtained here have be interpreted with caution. Indian markets for ventucapital differ considerably with respect to the industrisector invested in enterprises‘ early and expansion stages. InKarnataka, for example, early stage investments accountfor mainly in IT and IT enabled sector, while in Gujarat tearly stage investments are predominantly in infrastructudevelopment. Assam has a potentiality of VCF investmein biotech, agri-based, and pharmaceutical sectors.The Indian markets for venture capital differ with respecttheir sources of funds then US. In India, banks are the ma

contributors to entrepreneurial finance including ventucapital, while in US now a day; pension funds play significant role. Traditionally, pension funds havcontributed considerable amounts of capital to VCformation in the US, while in country as if India pensifunds have never been active as capital providers. FinancInstitutions have invested large amounts of capital venture capital in Karnataka and Maharastra, while in tUS banks have been getting less importance. In addition, Indian markets differ with respect to governments‘ role incomparison to US. Some states in India use tax incentivfor passive investors in order to ease the capital access fyoung high-technology enterprises, while others u

guarantees and co-investment programs in order to reduthe risk of young high-technology enterprises for VCF.In comparison to the United States, some states of India liKarnataka have invested in enterprises‘ early stages havingsimilar focused areas. US venture capital investments amore concentrated on high technologies than Indian VCinvestments. In the United States, almost 80 per cent of tventure capital investments went into communications acomputer-related enterprises in 1999, while only 27 per ceof the Indian VCF investments were invested in theenterprises.In addition to identifying the differences and similariti between different states of India in terms of VCF, the pap


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has also discussed the differences between VCF investorsacting in one national market by analyzing micro data onKarnataka and Assam. VCF investors acting in one nationalmarket can differ significantly with respect to theirinvestment behavior. The evidence of the Karnataka and theAssam market supports this view, while the results of theKarnataka market support it only to some extent in

comparison to US. Karnataka‘s VCF investo rs differconsiderably with respect to their investment strategies.Independent equity investors have a high degree oftechnological specialization compared to all other groups ofdependent equity investors. Moreover, independent equityinvestors are more willing than subsidiaries of banks toinvest capital in high-risk enterprises.The Karnataka market for VCF has not only experienced asignificant upswing in the last few years but also afundamental structural change towards financing high-technology enterprises. The Assam market, by contrast, hasmerely experienced a qualitative expansion. The number of private equity investors that are not legally connected to

another company (i.e. independent equity investors) hasincreased significantly in India. These equity investors, incontrast to their dependent counterparts, act more like USventure capitalists, and make more intensive use specificcontrol mechanisms such as convertible securities andcompensation systems.

VII EPILOGUE

From the above analysis, the following outcomes wereemerged:

i. Socioeconomic environment in India is notcompatible to American methodology of VCF.

ii. Control and ownership of enterprise is the inherentmanagement practice with investors‘ limited access(with few exceptions) to it in the corporate sector inIndia.

iii. There is lack of local market for high technology products in India.

iv. It has been observed that in case of the VCF withgovernment stake emphasize more on the overalldevelopment of the economy of the country/ regionthan emphasizing on ROI of the projects at themicro level. Which appears to the researchers asnot pragmatic in approach?

The characteristics of the American methodology for VCF

can be summed up as:i. More specific to high technology driven,envisaging fast growth.

ii. Long-term horizons classified into specific defined phases.

iii. Expectation of very high risks and return.iv. Focused on start up stage.v. Strict preference for equity financing and risk

sharing.vi. Pension fund is one of the major sources of VCF.

The differences between the US market and the Indianmarket for VCF with respect to the investments in young

high-technology enterprises although do not offemeaningful information on the development stage of tIndian venture capital markets but it provides many inpufor generating reforms in the Indian VCF market. Threason is that each market has its own, often-quite speciinnovation system, which determines the role of ventucapital in an economy. For example, when the innovati

system is dominated by in-house research and developmeone cannot expect a dynamic venture capital markeMoreover, the figures presented on venture capital activiin India do not include other financial sources for higtechnology enterprises such as business angels, which ahowever, important to determine the development stage venture capital markets.

VIII NOTES

1In the US, new funds raised for private equity grew atlower rate than new funds raised for venture capital2 Pfirrmann, O., U. Wupperfeld and J. Lerner (1997

Venture Capital and New Technology Based Firms: An UGerman Comparison. Heidelberg: Physica-Verlag.3 NVCA Report, Special Annual edn. 2003 available www.nvca.orgfirst accessed on July 23,20044SBIR (Small Business Innovation Research Programme)a highly competitive programme that encourages sma business to explore their technological potential a provides the incentive to profit from its commercializatioBy reserving a specific percentage of federal R&D funds small business, SBIR protects the small business anenables it to compete on the same level as larger businessSBIR funds the critical start-up and development stages ait encourages the commercialization of the technolog

product, or service, which, in turn, stimulates the Ueconomy.5Ministry of Finance (1988). Venture Capital GuidelinePress Release No. S.11(86)-CCI(11) / 87 Department Economic Affairs, Office of the Comptroller of CapitIssues, November 25.6Ramesh, S., & Gupta, A. (1995). Venture capital and thIndian financial sector. Delhi: Oxford University Press.7It is true that in the United States, banks have never been important source of venture capital, even through their SBsubsidiaries. For the most part, a bank‘s core competenciesare in evaluating and taking loans. The problem with loato small startups is that the capital is at high risk, so an

interest rate would have to be usurious. Moreover, since tnew firm is often losing money in its early days, payiinterest and principal would drain money from the firduring the period when it most requires the money finvestment.8Mittal R, 2005.; ―Karnata Boom‖, Business World, vol 25,issue 3,p.529ibid,p.5410Blau,J.R. and Alba, R.D.; 1982, ―Empowering nets ofParticipation‖. Administrative Science Quarterly, 27, 363-379.11 Carter, N.M., Williams, M. and Reynolds, P.D. 199Discontinuance among new firms in retail: the influence

http://www.nvca.org/http://www.nvca.org/


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initial resources, strategy and gender. Journal of BusinessVenturing, 12, 125-146.12Dossani R. & Kenney M., 2002; ― Creating an environmentfor venture capitalin India‖; World Development Vol. 30, No. 2, pp. 227 – 253

IX R EFERENCES

1) Blau,J.R. and Alba, R.D.; (1982), ―Empoweringnets of Participation‖. Administrative ScienceQuarterly, Vol. 27, pp. 363-379.

2) Carter, N.M., Williams, M. and Reynolds, P.D.1997, Discontinuance among new firms in retail:the influence of initial resources, strategy, andgender. Journal of Business Venturing, 12, 125-146.

3) Dossani R. & Kenney M., 2002; ―Creating anenvironment for venture capitalin India‖; WorldDevelopment Vol. 30, No. 2, pp. 227 – 253

4) Mittal R,2005.; ―Karnata Boom‖, Business World,

vol 25, issue 3,p.525) Ministry of Finance (1988). Venture CapitalGuidelines, Press Release No. S.11 (86)-CCI (11) /87 Department of Economic Affairs, Office of theComptroller of Capital Issues, November 25.

6) NVCA Report, Special Annual edn. 2003 availableat www.nvca.orgfirst accessed on July 23, 2004Pfirrmann, O., U. Wupperfeld and J. Lerner (1997).Venture Capital and New Technology BasedFirms: An US-German Comparison. Heidelberg:Physica-Verlag.

7) Ramesh, S., & Gupta, A. (1995). Venture capitaland the Indian financial sector. Delhi: Oxford

University Press.

http://www.nvca.org/http://www.nvca.org/


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Modelling Armed Robbery Crime Insurance Claimsin Nigeria

Dr Hamadu Dallah

Department Actuarial Science and InsuranceFaculty of Business AdministrationUniversity of Lagos, Akoka, Lagos, Nigeria

Email: [email protected]: +2348039094884

Abstract- The objective of modelling claims sizes ofinsurance policies was to be able to price premiums asaccurately as possible. In parametric modelling of lossdistributions in actuarial studies, an attractive candidate withtail weight intermediate between that of Gamma and Paretodistributions is the lognormal model. This paper investigatesthe distribution of claims of Nigerian armed robbery insurance

crime data. Using expert model mining system, the 3-parameter lognormal distribution demonstrated itself as thebest candidate. The result was quite revealing and inagreement with previous studies, recommending lognormalmodel for the analysis of right skewed general crime insuranceclaims data. In addition, it has also provided a good estimate ofthe deductible amount in claims management. Finally, theestimated data-based lognormal risk premium amount couldprovide the required basic framework for policy premiumunderwriting in Nigerian general armed robbery crimeinsurance market.

Keywords- General Crime Insurance, Armed RobberyClaims Data, Lognormal Model, Deductible, Expert ModelMining System.

I I NTRODUCTION

n insurance contract (policy) binds an insurancecompany in the occurrence of contractually defined

loss events to pay a specified amount (claim) to theinsurance holder. In return, the insurance holder pays a fixedsum (premium) to the insurance company. Since claimamounts usually depend on the dimension of losses,insurance companies offer uncertain future payoffs for acertain premium at present. This constellation generatesthree interesting phenomena studied in the literature:adverse selection (bad risks are likely to demand coverage

than good ones), moral hazard (insurance holders behavecareless as they do not have to bear the losses), andcalculation of premiums (Bohme, 2005). Therefore, eachform of insurance has its background of occurrences, whichresult in sudden and unforeseen financial shocks toindividuals or to groups of individuals, and, therefore, createcontingencies against which protection is desirable. Certaincrimes are the background for burglary, theft, and robberyinsurance and because these crimes are spectacular, andhave always had publicity value. Usually, in this context thestatistics published represent conditions at their worst. Theyare taken from congested centre like Lagos where propertyvalues are concentrated and burglaries and armed robberies

are, therefore, of mostly frequent; they represent thosetrades which are particularly the target of criminals. Thedata are compiled from the records of insurance companies,and consequently may be said to typify the experience ofthose who recognise the fact that they are peculiarly exposedto hazards against which protections are necessary.

Nevertheless, these information point to an alarmingsituation in case the complete crime records for Nigeriacould be compiled it will be of considerable magnitude bothin term of crimes and in loss of life and property. Nigeria isranked number one in “burglary and armed robbery crimes”in Africa even though this position is of recent beingchallenged by South Africa. In fact, a study on armedrobbery conducted in South Africa by Pretorius (2008) hasshown that “ the exper ience of being robbed and violentlyassaulted left the victims with feelings of ontologicalinsecurity, xenophobia and distrust for strangers, fear ofcrime and little confidence in the government and police tomaintain law and order. The manner in which short-terminsurance claims were negotiated and the amount of moneyeventually paid, was a final source of frustration and disgustfor many respondents”. The situation is not quite differentin Nigeria where everybody, firm, cooperation, and evengovernment valuable properties are subject to attached by

burglars and robbers. In fact, in Nigeria there is even passivesynonymy between burglary and armed robbery, whichusually carry capital punishment. Nowadays, it is commonto hear information that state government heavily

protected/guarded convey being attacked by robbers.Furthermore, it is a commonplace that everyday-armedrobbery crime in Lagos metropolitan city, causes immenseeconomic, psychological damage and even loss of life,although the true extend is still difficult to quantify. There isneed for urgent investigation in the covered claims paid byinsurance companies. The purpose of modeling claim sizesis to price premiums as accurately, and to estimate the riskof extreme claim events, which are unfortunately frequent inarmed robbery insurance. In this context, much attention has

been paid in the actuarial literature to alternativedistributions for claim sizes and some authors havedeveloped regression models (usually generalized linearmodels) for explaining claim sizes as a function of riskfactors (see Haberman and Renshaw, 1996). Jorgensen andde Souza (1994), Smyth and Jorgensen (2002) Heller,Stasinopoulos and Rigby (2007) have considered in their

A

mailto:[email protected]:[email protected]


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various studies, models for claim sizes, including zeroclaims. Our study differs quite slightly of these since thezero claims were not compiled in our case study data. Onthe other hand, one of the more perplexing problemsencountered in the fitting of claim amount data to atheoretical probability distribution, is that caused by the

presence of deductibles. Claims are paid only on losses

whose severity exceeds the deductible amount. Severalauthors (Duval and Allen (1973), Schott (1979), Smith andHead (1978)) have investigated the implication ofdeductibles on both the insurer and the insured. In each ofthese cases, it is assumed that the distribution function of thetrue loss amount is known. This work deals with fitting thelog-Normal distribution to loss data with an unknownconstant deductible. For case, multiple deductibles seeMarlin (1984).

II DATA DESCRIPTION

In this paper, we consider armed robbery policy exposure

and claims experience data derived from general crimeinsurance portfolios of a major general insurance companyin Nigeria. Our data are from WAPIC Insurance, asubsidiary of Intercontinental Bank Plc. which wasincorporated in 1958 as a private limited liability insurance

business in Nigeria. WAPIC Insurance Plc is a compositefull-line insurance company offering a range of products andservices covering life and pension, general and special risk

businesses. The observations are from each policyholderover a period of four years: November 2000 until November2004. Thus, our data come from financial records of WAPICinsurance policies, we consider only the claims file, which

provided the record of each armed robbery crime claim that

have been filed with the insurer during the observation period, and the payment amount made.

III EXPLORATORY DATA ANALYSIS

Before tackling the method of fitting the enabling stochasticmodel to the data, it is important to perform an exploratory

data analysis (EDA) to our data. EDA as opined by Hoaglanand Tukey (1977) will provide not only preliminary insightsto the data, but also, guide us on the future choice of theappropriate model. In addition, it also brings out certainhidden features of data, which can go unnoticed by theinvestigator without performing in-depth EDA.The following table 3.1 shows the summary of mostimportant descriptive statistics of the armed robberyinsurance claims data.

From the table 3.1 above, the first striking observation onthe result is the dramatic difference between the mean claim(N 234, 452.71) amount and the median claim (N 43,316.25)

amounts which is of a ratio1 to 5. This positive skewednature of the data can be easily substantiated by themagnitude of the coefficient of skweness (4.368). Inaddition, the situation can be easily confirmed from theHistogram and Box-and-Whisker plots displayed in Figure3.1 and Figure 3.2 respectively.

Table 3.1: Summary of Some Important Descriptive StatisticsArmed Robbery Claims Amount Statistic Std. Error

Mean 234452.7129 39095.4878595% Confidence Intervalfor Mean

Lower Bound 157360.4680

Upper Bound311544.9577

5% Trimmed Mean 133450.6004Median 43316.2500Variance 307219891181.304Std. Deviation 554274.20216Minimum 106.72Maximum 4583716Range 4583609.40Interquartile Range 139761.26Skewness 4.368 .172Kurtosis 23.803 .341


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Figure 3.1: Distribution of Armed Robbery InsuranceClaim

Figure 3.2: Box-and-Whisker Plot of Armed RobberyInsurance Claim

Moreover, the median lies outside the confidence intervals

of the mean claim amount [N 157,360.47, N311, 544.96].These results coupled with the non-normality results of the

Q-Q and P-P plots of Figure 3.3 and 3.4 respectively, aresuggesting an appropriate choice of a right skewed andheavy tailed probability models. With the coefficient ofkurtosis of 23.80, the versatile choice between with tailweight intermediate between that of gamma and Paretodistributions will be the lognormal or loglogisticdistributions. We consider in this study the 3-parameter

lognormal as the choice model.

Figure3.3: Q-Q Plot Normal Plot of Armed RobberyInsurance Claim

Figure 3.4: P-P Normal Probability Plot of Armed Robbery Insurance Claim Data

5000000.004000000.003000000.002000000.001000000.000.00

robbery

200

150

100

50

0

F

r e q u e n c y

Histogram

robbery

4000000.00

2000000.00

0.00

194

41

111

103

42

14145

98

15869

5,000,0004,000,0003,000,0002,000,0001,000,0000-1,000,000-2,000,000

Observed Value

3

2

1

0

-1

-2

-3

E x p e c t e d N o r m a l

Normal Q-Q Plot of robbery

1.00.80.60.40.20.0

Observed Cum Prob

1.0

0.8

0.6

0.4

0.2

0.0

E x

p e c t e d C u

m P

r o b

Normal P-P Plot of robbery


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Considering the following hypothesis statementH0: The data follow a specified distributionHa: The data do not follow the specified distribution

The Kolmogorov-Smirnov test statistic ( D) is defined

as

)7()(,1

)(max1

ii

N i

Y F N

i

N

iY F D

Where F is the theoretical cumulative distribution of thedistribution, being tested which must be a continuousdistribution.The hypothesis regarding the distributional form is rejectedif the test statistic, D, is greater than the critical valueobtained from a table. There are several variations of thesetables in the literature that use somewhat different scalingfor the K-S test statistic and critical regions.

There is no need for the K-S tables in the work since thesoftware programs used gives both the K-S test and thecritical probability values.

V A NALYSIS RESULTS

A. Summary Results and Discussion

The following Table 5.1 and 5.2 gives the summary ofresults of the best three competing models. The resultsinclude parameters estimates and goodness of fit thesimulated distributions. (For the full results, see AppendicesI and II):

Table 5.1: Summary of Parameters Estimates for the Best Three Fitted Distributions

Lognormal (3P) 9113.1 704.10 6732.5

Lognormal(P) 9128.1 703.10

Log-Logistic (3P) 88352.0 0.44571 72.106

Table 5.2: Summary of Kolmogov Sminov Goodness of Fit for the Best Three Distributions

Lognormal (3P) 0.02936 1

Lognormal (2P) 0.02941 2

Log-Logistic (3P) 0.03683 3

We can easily observe Tables 5.1 and 5.2 that, the three- parameter lognormal distribution is the best candidate forthe data. With Kolmogorov Siminov goodness of fitcoefficient of 0.02936, it ranks first and subsequently,outperforming other competing distributions. Closelyfollowing is as expected the two-parameter lognormaldistribution and the three-parameter log-logisticdistributions with goodness of fit coefficients of 0.02941and0.036 respectively. These findings support the theoreticalchoice of the model for the robbery claims data. In fact, byclosely examining the distribution and P-P Probability plotsin figures 5.1 and 5.2 the EDA results supports ouranalytical choice of the model. On the other hand, a closelook at the Q-Q plot displays in Figure 5.3 demonstrated theadequacy and suitability of the fitted model but also raiseda cautionary note on possible two possible outlying values

which in future call for the use of robustness in insuranceclaims management.


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Figure 5.1: Distribution of Fitted 3-parameter Lognormal Model to the Armed Robbery Insurance Data

Figure 5.2: P-P Plot 3-Parameter Lognormal Model to Armed Robbery Insurance Data

Figure 5.3: Q-Q Plot 3-Parameter Lognormal Model to Armed Robbery Insurance Data

Probability Density Function

His togram Lognormal (3P)

x4E+62E+60

0.960.88

0.80.720.640.560.48

0.40.320.240.160.08

0

P-P Plot

Lognormal (3P)

P (Empirical)10.80.60.40.20

1

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0

Q-Q Plot

Lognormal (3P)

x4E+62E+60

4.4E+6

4E+6

3.6E+63.2E+6

2.8E+62.4E+6

2E+6

1.6E+61.2E+6

800000

400000

0


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Thus, the estimated fitted lognormal mean is given asfollows

4.651,276

)2/9113.1(704.10exp6732.5)2/ˆˆ

exp(ˆ

ˆ 22

B. The Risk Premium Estimate

The basis of the estimate of the risk premium risk premiumis the estimate of the total loss R. this is given as

556069314.276651201))2/ˆˆ

exp(ˆ

(ˆ

2 N R

With an estimated mean claim of N 276,651.4 yields anestimate risk premium of N 55,606,931

VI CONCLUSION

Motivated by the alarming rate of armed robbery crimesgenerally in Nigeria and Lagos state in particular, weinvestigated empirically the distribution of claim amounts

paid by Nigerian general crime insurance company to their policies holders‟ victims of armed robbery. The lognormalmodel was considered not based only on theoretical ground,

but also from preliminary EDA results. Using expert modelmining procedure, the 3-parameter lognormal distributiondemonstrated a superior level of adequacy and goodness offit over other stochastic claims distribution models. The

present findings provided good empirical reasons to support previous theoretical and empirical results, which favor thelognormal distribution as an appropriate model whenmodeling claims data specifically, with intermediate tailweight between the gamma and Pareto distributions. It isalso important to note the slight difference between the

usual two-parameter lognormal distribution popularly usedin modelling returns stochastic volatility in empiricalfinance and the three-parameter lognormal model, whichmake a strong case for an estimated deductible of about N1,140 in actuarial studies and practice. Finally, it isimportant to have a critical look at the financial implicationof the estimated lognormal data-based risk premiumamounts of about N55,606,931, in future premiumunderwriting for both existing policy holders and newcustomers in Nigerian emerging market economy.

VII R EFERENCES

1) Bohme, R. (2005), Cyber-Insurance Revisited.Workshop on the Economics of InformationSecurity (WEIS) 2005, Kennedy School ofGovernment, Cambridge, MA, USA.

2) Duval, R. M. and Allen, T. C. (1973), „Least CostDeductible Decisions‟, The Journal of Risk and

Insurance , 40, 495507.3) Haberman , S. and Renshaw, A. E. (1996),

„Generalized Linear Models and ActuarialScience‟, The Statistician , 45, 407-436.

4) Hill, B. M. (1963), „The Three -parameterLognormal Distribution and Bayesian Analysis of a

Point-source Epidem ic‟, Journal of AmericanStatistical Association, 58, 72-84

5) Hirose, H. (1997), „Maximum LikelihoodParameter Estimation in the Three-parameterLognormal Distribution Using the ContinuationMethod‟, Computational Statistical Data Analysis ,

24, 139-152.6) Jorgensen, B. and de Souza, M. C. P.(1994),„Fitting Tweedie‟s compound Poisson Model toInsurance Claims Data‟, Scandinavian ActuarialJournal, 69-93.

7) Omobola, J. (2008), „Transformatio9n andInsurance Growth in Nigeria ‟ Accenture 7April,2008.

8) Marlin, P. (1984), „Fitting the Log -NormalDistribution to Loss Data Subject to MultipleDeductibles‟, The Journal of Risk and Insurance,51, 687-701.

9) Schott, B. (1979), „Annual Losses for Straight

Deductible Cover age‟. The Journal of Risk andInsurance, 46, 619-635.10) Smyth, G. K. and Jorgensen, B. (2002), „Fitting

Tweedie‟s compound Poisson Model to InsuranceClaims Data: Dispersion Modeling‟, ASTINBulletin, 32, 143-157.

11) Smith, M. L. and Head, G. L., (1978), „Guide linesfor Insurers for Pricing Deductibles‟, The Journalof Risk and Insurance , 45, 217-238.

12) Wingo, D. R. (1984), „Fitting Three -parameterLognormal Models by Numerical GlobalOptimization- an Improved Algorithm‟,Computational Statistical Data Analysis, 2, 13-25.


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VIII APPENDIX Appendix I Fitting Results

# Distribution Parameters

1 Beta 1=0.14219 2=2.1991 a=106.72 b=4.5837E+6

2 Cauchy =33439.0 =27234.0

3 Chi-Squared =2.3445E+5

4 Chi-Squared (2P) =2.2474E+5 =98.183

5 Error Function h=1.2757E-6

6 Exponential =4.2653E-6

7 Exponential (2P) =4.2672E-6 =106.72

8 Fatigue Life =3.071 =40194.0

9 Fatigue Life (3P) =2.5141 =60735.0 =-902.16

10 Frechet =0.6352 =17808.011 Frechet (3P) =0.91368 =13843.0 =96.212

12 Gamma =0.17892 =1.3104E+6

13 Gamma (3P) =0.38085 =6.1617E+5 =106.72

14 Gen. Extreme Value k=0.69501 =70701.0 =37087.0

15 Gen. Pareto k=0.65115 =87102.0 =-15229.0

16 Gumbel Max =4.3217E+5 =-15000.0

17 Gumbel Min =4.3217E+5 =4.8391E+5

18 Inv. Gaussian =41949.0 =2.3445E+5

19 Inv. Gaussian (3P) =12663.0 =3.1867E+5 =97.787

20 Johnson SB =2.3157 =0.50188=5.9222E+6 =-20527.0

21 Laplace =2.5515E-6 =2.3445E+5

22 Log-Logistic =0.91777 =43489.0

23 Log-Logistic (3P) =0.88352 =44571.0 =106.72

24 Logistic =3.0559E+5 =2.3445E+5

25 Lognormal =1.9128 =10.70326 Lognormal (3P) =1.9113 =10.704 =-5.6732

27 Normal =5.5427E+5 =2.3445E+5

28 Pareto =0.16575 =106.72

29 Pert m=106.72 a=106.72 b=4.5837E+6

30 Power Function =0.06466 a=106.72 b=4.5837E+6

31 Rayleigh =1.8707E+5


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32 Rayleigh (2P) =4.6280E+5 =-127.0

33 Student's t =2

34 Triangular m=106.72 a=106.72 b=4.5837E+6

35 Uniform a=-7.2558E+5 b=1.1945E+6

36 Weibull =0.6351 =1.0622E+537 Weibull (3P) =0.54574 =1.1510E+5 =106.72

38 Erlang No fit

39 Erlang (3P) No fit

40 Johnson SU No fit


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Appendix IIGoodness of Fit – Summary

# Distribution Kolmogorov Smirnov

Statistic Rank

1 Beta 0.35471 21

2 Cauchy 0.28305 16

3 Chi-Squared 0.80099 36

4 Chi-Squared (2P) 0.79602 35

5 Error Function 0.50008 29

6 Exponential 0.36437 24

7 Exponential (2P) 0.36462 25

8 Fatigue Life 0.10061 8

9 Fatigue Life (3P) 0.12118 9

10 Frechet 0.084 5

11 Frechet 0.21106 15

12 Gamma 0.30964 18

13 Gamma (3P) 0.14627 11

14 Gen. Extreme Value 0.14724 12

15 Gen. Pareto 0.15504 13

16 Gumbel 0.38074 27

17 Gumbel 0.40507 28

18 Inv. Gaussian 0.19953 14

19 Inv. Gaussian (3P) 0.13214 10

20 Johnson SB 0.30158 17

21 Laplace 0.36295 2322 Log-Logistic 0.03965 4

23 Log-Logistic (3P) 0.03683 3

24 Logistic 0.34066 20

25 Lognormal 0.02941 2

26 Lognormal (3P) 0.02936 1

27 Normal 0.33622 19

28 Pareto 0.35501 22

29 Pert 0.61559 32

30 Power Function 0.58063 31

31 Rayleigh 0.548 3032 Rayleigh 0.72301 34

33 Student's t 0.99996 37

34 Triangular 0.71756 33

35 Uniform 0.37795 26

36 Weibull 0.08883 7

37 Weibull (3P) 0.08703 6

Source: EasFit Expert Model Mining

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