. ---
Factors Determining Consumer Fraud 
Reporting in Kenya 
Rodgers Anyanga Musamali 
Private Sector Development Division 
Kenya Institute for Public Policy 
Research and Analysis 
KIPPRA Discussion Paper No. 173 
2014 
Factors detennining consumer fraud reporting in Kenya 
KIPPRA in Brief 
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autonomous institute whose primary mission is to conduct public policy research 
leading to policy advice. KIPPRA's mission is to produce consistently high-quality 
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the public sector. KIPPRA therefore produces a body of well-researched and 
documented information on public policy, and in the process assists in formulating 
long-term strategic perspectives. KIPPRA serves as a centralized source from 
which the Government and the private sector may obtain information and advice 
on public policy issues. 
Published 2014 
© Kenya Institute for Public Policy Research and Analysis 
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ISBN 978 9966 058 43 o 
The Discussion Paper Series disseminates results and reflections from ongoing 
research activities of the Institute's programmes. The papers are internally refereed 
and are disseminated to inform and invoke debate on policy issues. Opinions 
expressed in the papers are entirely those of the authors and do not necessarily 
reflect the views of the Institute. 
This paper is produced under the KIPPR A Young Professionals (YPs) programme. 
The programme targets young scholars from the public and private sector, who 
undertake an intensive one-year course on public policy research and analysis, and 
during which they write a research paper on a selected public policy issue, with 
supervision from senior researchers at the Institute. 
KIPPRA acknowledges generous support from the Government of Kenya, African 
Capacity Building Foundation (ACBF), and the Think Tank Initiative of IDRC. 
� ThinkTank Initiative 
� Initiative Thinktank 
ii 
Abstract 
This study examines the factors determining consumerfr aud reporting in Kenya. 
It presents cross-sectional evidence from data collected by the United Nations 
Office on Drugs and Crime and KIPPRA in 2009/2010. Descriptive results 
show that the most prevalent consumer fraud in Kenya is the pJ-oliferation of 
counterfeit goods. Using the logit model, the study finds that consumer fraud 
reporting is affected by the type of fraud, where proliferation of counterfeit 
goods is important, but negatively associated to reporting. This connotes that 
the more people are victimized, the more they fail to report to the police or 
other relevant authorities. This finding puts the fight against counterfeits into 
perspective, perhaps underpinning the important attention it needs to continue 
receiving from the government and other relevant institutions. More awareness 
by the Anti Counterfeit Agency (ACA) and other relevant stakeholders, improved 
ACA capacity, and better collaboration would enhance reporting and aid in 
curbing trade in counterfeits. 
In addition, perception of victims towards the police' ability to control crime 
positively impacts the reporting behaviour of consumer fraud. Poor perception 
towards the police impacts consumer fraud reporting more significantly, hence 
improving how citizens perceive the police is important in fighting consumer 
fraud. An improved perception would create more confidence in the security 
systems and people would be willing to file reports on economic crimes such as 
consumer fraud. Initiatives of reforming the police to improve service delivery 
should be encouraged, while embracing their capacity building on consumer 
crimes to enhance reporting and response. 
KIPPRA LIBRARY 
ACC. ft> fJ tr !'Q.Q. . 5..5. .f.: .Q ............. .
, CALL,.,_. 3.f" .. ' .: -�.4.:5.�?J.0..?.J:-!:. .I). \
iii 
Abbreviations and Acronyms 
ACA Anti-Counterfeit Agency 
CAK Competition Authority of Kenya 
CCK Communications Commission of Kenya 
CMA Capital Markets Authority 
COFEK Consumer Federation of Kenya 
! i ClITS Consumer Unity and Trust Society 
ERC Energy Regulatory Commission 
ICVS International Criminal Victimization Survey 
IRA Insurance Regulatory Authority 
KAM Kenya Association of Manufacturers 
KEBS Kenya Bureau of Standards 
KCAA Kenya Civil Aviation Authority 
KIPPRA Kenya Institute for Public Policy Research and Analysis 
KNBS Kenya National Bureau of Statistics 
KPMG Klynveld Peat Marwick Goerdeler 
KRA Kenya Revenue Authority 
UNICR1 United Nations Inter-regional Crime and Justice Research 
Institute 
UNODC United Nations Office on Drugs and Crime 
WASREB Water Services Regulatory Authority 
' . 
Table of Contents 
Abstract ................................................................................................................. iii 
Abbreviations and Acronyms ................................................................................ iv 
1. Introduction ..................................................................................................... 1 
1.1 Situational Analysis of Consumer Fraud in Kenya. .................................... 4 
1.2 Problem Statement ..................................................................................... 7 
1.3 Objectives. ................................................................................................... 8 
1.4 Research Objectives. ................................................................................... 8 
1.5 Justification ................................................................................................ 9 
2. Literature Review ........................................................................................... 10
2.1 Theoretical Literature. .............................................................................. 10
2.2 Empirical Literature. ................................................................................ 12
3. Methodology. .................................................................................................. 14 
3.1 Conceptual Framework ............................................................................ 14 
3.2 Model Specification .................................................................................. 15 
3.3 Estimation Technique .............................................................................. 15 
3-4 Data and Variables Specification ............................................................. 17 
4. Results and Discussions ................................................................................ 19 
4.1 Descriptive Statistics ................................................................................ 19 
4.2 Diagnostic Tests .......................................................................................2 0
4.3 Estimation Results ................................................................................... 21
5. Conclusion and Policy Recommendations .................................................... 25 
5.1 Conclusion ................................................................................................ 25 
5.2 Policy Recommendations ......................................................................... 26 
5.3 Study Limitations ..................................................................................... 27 
5.4 Future Research ....................................................................................... 27 
References ......................................................................................................2 8 
Appendix ........................................................................................................ 31 
V 
1. Introduction
Fraud is knowing misrepresentation of the truth or concealment of material facts 
to induce the victim to act to their detriment (Holtfreter, Reisig and Blomberg, 
2005). In general, a fraud is an act of dishonesty that leads to deceit of the victim 
with an intention of benefitting at the expense of the deceived. Fraud occurs in 
various forms such as bank fraud, which comprises forged documents (cheques, 
letters of credit, and letters of instruction); theft of cash and goods; procurement 
fraud that involves over invoicing and fabricated invoices; bribery; inaccuracy and 
non-declaration in customs and excise duty; tax evasion; forged cheque signatures; 
false insurance claims; tender and contract fraud; electronic funds transfer fraud; 
and identity fraud. The effects of any form of fraud are detrimental and result 
into revenue loss both to government and in form of taxes, while individuals and 
corporations lose income. 
Consumer fraud is a form of economic crime that involves deception of the 
victim with the promise of goods, services or other benefits that are non-existent 
or are grossly misrepresented (Holtfreter, Reisig and Blomberg, 2005). There are 
various aspects of consumer fraud. According to the KPMG fraud survey of 2003, 
they include: ATM theft, check and credit card fraud, fraudulent classification 
of merchandise for customers, fraudulent merchandise returns, and identity 
fraud. The Kenya Crime Victimization Survey of 2010 categorizes consumer 
fraud into stolen or forged cheques, also referred to as financial fraud; fraudulent 
schemes such as pyramid schemes; payment for non-existent goods or services; 
and proliferation of counterfeit goods or provision of poor services. Consumer 
fraud may occur in construction or repair work (mainly through sub-standard 
work); in hotels or restaurants (through poor services); in supermarkets, shops 
and chemists (through counterfeit goods); and over the internet or e-commerce 
(through fraudulent transactions such as cyber crime). Other avenues may be 
through poor services in the medical, financial, and learning institutions. Issuance 
or obtaining of academic certificates through fraudulent means amounts to 
academic fraud, which is also a form of consumer fraud. In general, consumer 
fraud comprises a wide range of issues that affect and influence a consumer's daily 
operations. 
According to the International Criminal Victimization Survey (ICVS) conducted 
in 2000 as per Figure 1.1, consumer fraud, though hoped to be less prevalent in 
Africa appears to be more common in the continent than any other place besides 
Eastern Europe (Figure 1.1). Nearly 30 per cent of Africans surveyed responded 
that they had been defrauded in the previous year. The higher levels in Europe 
could hypothetically be because most people are educated, therefore they tend 
1 
Factors determining consumer fraud reporting in Kenya 
Figure 1.1: Survey respondents who suffered fraud in the previous 
vear 
•' 
East Europe - - ··--� - 49.9
South-East Europe - ... 38.2 
I 
Sub-Saharan Africa 28.6 
I 
Asia 22.8 
South-Central America 22.5 
I 
West-Central America 19.5 
North America - 9.5
Oceania - 9
0 10 20 30 40 50 60 
■%victims
Source: United Nations Interregional Crime and Justice Research Institute, 
2000 
to be open and report' more consumer fraud to the authorities. The situation in 
Africa could imply that it is a dumping ground that is also characterized by low 
levels of education. The effects of consumer fraud are diverse, depending on the 
type of fraud, and may range from loss of income, road accidents, deaths, and ill 
health. 
Financial fraud, for instance, affects both the consumers of financial services 
and the financial service providers. According to Deloitte (2013), close to Ksh 
2.55 billion was lost in the region to fraud by banks and insurance companies in 
2013. Experts from Deloitte estimate this figure to be much bigger than reported, 
since most institutions underreport to protect their reputation. Pyramid schemes 
victims in Kenya lost money, property, and developed chronic diseases resulting 
from depression. In some instances, people committed suicide because of the 
associated losses. The report by the taskforce on pyramid schemes in 2010 indicates 
that close to Ksh 8.2 billion was lost by victims in Kenya. These were, however, 
'To lay a formal complaint to the authorities with intent to recover lost property, punish 
the offender, and prevent. 
2 
Introduction 
the estimated amounts in principle, without factoring in expected returns. The 
taskforce in its report admits that these were initial figures and that the loss could 
be much more, since all victims might not have come forth for registration by the 
time the report was released. 
Additionally, proliferation of counterfeit products affects many sectors of the 
economy, mostly in motor vehicle assembly and its components sector; energy, 
electrical and electronic sector; food, beverages and tobacco sector; chemicals 
and allied sector; and pharmaceuticals and medical equipment sector (Kenya 
Association of Manufacturers - KAM, 2012). The implications of counterfeit 
goods in the market are insurmountable and range from loss of revenue for 
manufacturers; loss of revenue to the government from taxes; adverse health 
effects caused by counterfeit foodstuff; drugs and medical-related equipment; 
increased insecurity resulting from counterfeit locks; and increased road accidents 
caused by counterfeit motor vehicle parts such as tyres and brake pads. KAM 
estimated that in 2012, the East African region lost about US$ 500 million on 
counterfeit products. In addition, KAM estimates that more than 30 per cent of 
the medicine sold in the Kenyan market is counterfeit. Kenyan manufacturers lost 
over Ksh 30 billion per year, while the government loses Ksh 6 billion per year in 
revenue due to counterfeits.2 
A lot of attention with respect to reporting, and enforcement and policy has 
focused on violence and property crimes victimizations (Mustaine and Tewskbury, 
2000; Tseloni, 2000), while economic crimes against consumers have received 
little attention despite their adverse socio-economic effects. This could be 
explained by the unavailable (scanty) data on consumer-related crimes (Kusic, 
1989; Moore and Mills 1990; Titus, Heinzelmann and Boyle, 1995). Another cause 
could be failure to report such cases by the affected people. While consumer fraud 
is clearly a public policy issue that requires attention from researchers and policy 
makers, the focus of legislation and victim assistance programmes has been on 
victims of violent and property crimes. The need to address issues of consumer 
fraud by policy makers is therefore paramount. To this front, the Kenyan situation 
has not been different; which validates the attempt of this research to profile a 
comprehensive understanding of consumer fraud victimization, and likely factors 
affecting reporting of these crimes in Kenya. 
• Keynote address by Hon. Amos Wako, former Attorney General of Kenya, during the
Third Global Conference on Combating Counterfeiting and Piracy at the International
Conference Centre in Geneva, Switzerland on 30 January 2007. Available at http://www.
ccapcongress.net/archives/Geneva/Files/Wako.pdf
3 
-
Factors determining consumer fraud reporting in Kenya 
1.1 Situational Analysis of Consumer Fraud in Kenya 
Consumer fraud tends to represent acts of omission or commission against 
consumer protection attempts. Article 46 of the Constitution of Kenya provides 
an elaborate understanding of consumer rights under which consumer fraud 
activities undermine. Some of the rights articulated in the Constitution that 
enhance consumer protection include: right to goods and services of reasonable 
quality; right to information which aids the consumers to gain full benefits from 
goods and services, protection of health, safety and economic interests; and right 
to compensation for loss or injury arising from defects in goods and services. Apart 
from the Constitution, issues of consumer protection are also elaborated in the 
Competition Act of Kenya Cap. 504, which provides for consumer representation 
and protection with well outlined redress mechanisms in case of violations. 
Another regulatory milestone on issues of consumer protection in Kenya is 
the enactment of the Consumer Protection Act No. 46 of 2012 by the National 
Assembly. The Act guarantees the consumers fundamental rights protecting them 
from false and misleading practices. Other pieces of legislation that advocate for 
issues of consumer protection are Fertilizers and Animal Foodstuffs Act Cap. 345 
that guarantees consumer safety by prohibiting the use of fertilizers and foodstuff 
that have either bone or other animal matter containing disease causing organisms 
in the production of fertilizers. 
In addition, the Weights and Measures Act Cap. 513 safeguards consumers 
against sale of goods with inaccurate quantities; the Food, Drugs and Chemical 
Substances Act Cap. 254 guards against the sale of unwholesome, poisonous or 
adulterated food to consumers; the Trade Descriptions Act Cap. 505 enhances 
honesty in business deals and deters false or misleading statements regarding 
various aspects of goods that involve their identity, quantity, size and gauge; and 
method of production, among others. The Standards Act Cap. 496 aims to guard 
against substandard and unsafe products and is enforceable by the Kenya Bureau 
of Standards (KEBS); the Sale of Goods Act Cap. 31 outlines the provisions for a 
sales contract between consumers and sellers of goods and services; the Medical 
Practitioners and Dentists Act Cap. 253 ensures that those who engage in the 
medical practice are qualified and can be relied upon by the consumers; and the 
Economic Crimes Act of 2003 prohibits intentional falsification or manipulation 
of information in order to confer benefits to oneself or other person(s) through 
dishonesty, deceit or trickery. The Trademark Act Cap. 506 prohibits importation, 
malting, selling or trading in goods that have been forged, replicated; or use a 
registered trademark that is likely to deceive or cause confusion to the consumers. 
Additional pieces of legislation include: the Customs and Excise Act Cap. 472,
which prohibits misrepresentation of trademarks, business names or addresses; 
4 
Introduction 
the Pharmacy and Poisons Act Cap. 244, which ensures that drugs have correct 
ingredients and are not falsely advertised or mislabeled; while the Alcoholic 
Drinks Act No. 4 of 2010 prohibits sale of adulterated alcohol, and protects the 
consumers from deceptive inducements. 
Under the financial sector, the Capital Markets Authority (CMA) through the 
Capital Markets Act Cap. 485A is mandated to undertake protection of investor 
interests to avoid financial losses arising from the failure of a licensed broker or 
dealer to meet their contractual obligations. On the other hand, the Insurance Act 
Cap. 487 mandates the Insurance Regulatory Authority to protect the interests of 
insurance policy holders and beneficiaries in any insurance contract. The Banking 
Act Cap. 488 establishes the Deposit Protection Fund Board whose principal 
objective is to provide a deposit insurance scheme for customers of member 
institutions. This is aimed at protecting the customers incase a member of the 
financial institution becomes insolvent and is liquidated. Consumer protection 
also takes place in the telecommunications sector with the Kenya Information 
and Communications Act Cap. 411A mandating the Communications Authority 
of Kenya (CA) to protect interests of all telecommunication users in terms of 
prices, quality and variety of services offered. The commission also maintains 
and promotes effective competition in the sector to ensure efficiency in service 
provision. 
In the energy sector, the Energy Regulatory Commission (ERC) is established 
under the Energy Act Cap. 314 and is mandated to protect the interests of 
consumers, investors and other stakeholders, among other functions. The water 
Act Cap. 372 establishes the Water Services Regulatory Board (WASREB), which 
determines standards of water services and ensures efficient, affordable, and 
sustainable services to consumers, among other duties. A review of the Anti­
Counterfeit Act Cap. 130A shows that the Anti-Counterfeit Agency (ACA) engages 
largely in consumer welfare and protection activities from combating counterfeits 
to creating awareness on matters of counterfeiting in Kenya, among others. 
The mandate of the agency is inclined to the intellectual property right holders. 
An investigation about a violation can only be instituted by the agency if an 
intellectual property holder reports it. The agency can also institute investigations 
into a violation, if it is necessary to do so. Generally, there is no incentive for the 
intellectual property holder to report a violation to the agency. 
While the Anti-Counterfeit Act has a provision on consumer protection, it 
does not provide information on avenues of reporting or redressal for consumers 
affected by counterfeits. This is inconsistent with the Consumer Protection Act 
No. 46 of 2012, which identifies reporting as an important ingredient in enabling 
consumers get redress incase of any violation. ACA also lacks a national presence, 
5 
- I 
Factors detennining consumerfr aud reporting in Kenya 
with offices located only in Nairobi and Mombasa; furthermore, the officers 
are incapacitated, with the Nairobi and Mombasa offices having six and two 
enforcement officers, respectively. This hinders reporting for the victims who 
might want to physically file a complaint. Lack of a national presence and adequate 
staffing are probable indicators that the agency lacks enough financial capacity to 
run its activities in the fight against the vice. 
1.1.1 Statistics on consumer fraud in Kenya 
While information about consumer fraud in Kenya is limited, data collected by the 
Kenya National Bureau of Statistics (KNBS) shows that economic crimes are on 
the rise. Figure 1.2 shows that economic crimes3 under which consumer fraud falls 
have been on the increase from 1,400 cases reported to the authorities in 2005 to 
3,400 in 2012. This represents a 142 per cent increment, which signals a worrying 
trend despite many cases going unreported. 
Various regulatory institutions such as the Competition Authority of Kenya 
(CAK); the Communications Authority of Kenya (CA); the Kenya Bureau of 
Standards (KEBS); the Department of Weights and Measures; the Energy 
Regulatory Commission (ERC); the Capital Markets Authority (CMA); the 
Fi e 1.2: Consumer fraud in Ken a 
4000 
• 3500
E 
3000
Ji! 
2500
I 2000.., 
l lSOO
1000
E 
soo
0 
2005 2006 2007 2001 2009 2010 2011 2012 
Source: KNBS (Various) 
3 Involves obtaining by false pretence, currency forgery, other fraud/forgery offenses and 
false accounting. 
6 
Introduction 
Insurance Regulatory Authority (IRA); the Water Services Regulatory Board 
(WASREB); and the Anti-Counterfeit Agency (ACA) engage themselves in 
consumer protection in their distinct fields despite consumer fraud trend being 
on the increase. The CAK is, however, mandated to promote and safeguard 
competition in the whole economy in order to protect consumers from unfair and 
misleading market conduct. It therefore provides a supervisory and coordination 
role to the other regulatory institutions. The regulatory agencies are also expected 
to liaise with CAK in advancing consumer protection issues and coordination 
amongst them. 
Consumers' agenda is also driven by advocacy institutions such as the 
Consumer Information Network, Consumer Unity and Trust Society (CUTS), but 
largely through Consumer Federation of Kenya (COFEK). COFEK is a non-profit 
federation mainly committed to issues of consumer protection, education, research 
and anti-counterfeit campaigns. CUTS is an international non-governmental 
organization which supports issues of consumer protection and governance, trade 
and training development. 
Despite the existence of a regulatory framework for articulating consumer 
protection issues, the levels of consumer fraud reporting are low in Kenya. 
According to CUTS (2012), there is lack of awareness on redressal mechanisms 
by the Kenyan consumers. In addition, the consumers lack confidence in seeking 
redress through the existing mechanisms on account of lack of information about 
how and whom to approach in lodging complaints. 
1.2 Problem Statement 
According to the victimization survey in Kenya of 2010, consumer fraud 
contributed 21.9 per cent of the total crimes committed, which represents the 
highest individual category. Out of this, only 2.8 per cent and 1.8 per cent of the 
cases were reported to the police and other authorities, respectively. The low 
level of reporting by victims is a cause of concern despite the social and economic 
adverse effects associated with consumer fraud. From the survey, the consumer 
frauds that were experienced include financial fraud, fraudulent schemes, 
provision of poor services, proliferation of counterfeit products in the market ,and 
other forms of consumer crimes. These crimes adversely affect the consumers 
through financial losses, social sufferings, health risks and road accidents. 
According to UNODC (2005), all forms of crime do not only impose human 
suffering, but also negatively affect economic development through low 
investments. For instance, consumer fraud, through proliferation of counterfeit 
goods and services in the market. reduces investor and consumer confidence, 
7 
Factors determining consumer fraud reporting in Kenya 
leads to loss of revenue and affects investments in business. Manufacturers 
experience reduced sales volumes, higher costs of production and depressed 
.. earnings since counterfeit products spoil the good name of genuine products 
(KAM, 2012). This will affect income generation and employment, which slows 
down economic growth and development of the economy. They also have negative 
effects on consumers' health and safety through treatment failures and deaths. 
Increased road accidents are also closely associated to counterfeited motor vehicle 
and motor cycle spares. 
Consumers also feel deprived economically when they fail to get value for their 
money as a result of consumer fraud. In addition, people who have been victims of 
any form of crime tend to be vulnerable future targets of the same. Understanding 
the demographics of victims of consumer fraud, both at household and individual 
levels, and the factors that determine reporting of such crimes will provide policy 
recommendations to assist in dealing with the problem. The study also seeks to 
contribute towards consumer fraud literature in Kenya. There is little documented 
evidence Jn consumer fraud in Kenya and the East African region, with the few 
studies done by KPMG, Deloitte and Touche, and Price Waterhouse and Coopers 
(PWC) delving more on financial fraud (which is a component of consumer fraud) 
and organizational fraud, especially for financial institutions. 
1.3 Objectives 
The general objective of the study is to explain the factors determining reporting 
of consumer fraud victimization in Kenya. Specifically, the study seeks to: 
(i) Identify the most prevalent forms of consumer fraud and reporting
behaviour in Kenya; and
(ii) Determine the factors that affect reporting of consumer fraud victimization
in Kenya.
1.4 Research Questions 
The study seeks to answer the following questions: 
(i) What are the most prevalent forms of consumer fraud and reporting
behaviour in Kenya?; and
ii) What are the factors that determine reporting of consumer fraud
victimization in Kenya?
8 
Introduction 
--------------------------
1.5 Justification 
The Constitution of Kenya, Article 46, under the Bill of Rights guarantees 
consumers fundamental rights and privileges that relate to reasonable quality of 
goods and services; information that relates to benefiting from goods and services; 
protection of health; safety and economic interests; and compensation for loss or 
injury that arises from defective goods and services. Subsequently, the consumer 
rights are enshrined in the Consumer Protection Act, No. 46 of 2012. Issues of 
fraud are also anchored in the Anti-Corruption and Economic Crimes Act of 2003, 
Cap. 65, which involves intentional falsification or manipulation of information in 
order to confer benefits to oneself or other person(s) through dishonesty, deceit 
or trickery. This study will therefore seek to provide information on consumer 
fraud victimization and the factors determining reporting of these crimes, which 
is generally not available in the official reported data on crime. 
9 
Factors determining consumer fraud reporting in Kenya 
2. Literature Review
2.1 Theoretical Literature 
Reporting any form of crime to the police or any other authorities has evolved 
because of its importance in the criminal justice system. Studies suggest that 
those who report crime to the police are interested in safeguarding the criminal 
justice system (Black, 1971; Hindelang, 1976). This study will be based on the three 
correlates that influence crime reporting as postulated in Zhang, Messner and Liu 
(2007), which comprise the victim-specific variables that consist of individual 
or household attributes; incident-specific variables; and environment-specific 
variables. The victim-specific variables encompass demographic characteristics 
attributed to personal victimization, which include gender, race, age, and 
education (Hindelang and Gottfredson, 1976; Skogan, 1984). On the other hand, 
household characteristics include number of members in the household, and the 
income of the household. The incident-specific variables address the features of the 
criminal t:vent, which may include injury, monetary loss and the victim-offender 
relationship (Hindelang and Gottfredson, 1976; Skogan, 1984). The environment­
specific variables investigate majorly the effects of neighbourhood characteristics 
such as neighbourhood disadvantage and social cohesion (Baumer, 2002). Two 
theories that have been developed on issues of crime reporting are advanced in 
Zhang, Messner and Liu (2007). These theories, though at their infancy stages, 
have been tested empirically on property and personal-related crimes. The field 
of consumer fraud is grey as far as theoretical frameworks are concerned and, as 
a result, this study will use the theories developed in the areas of property and 
personal-related crimes in its attempt to establish the reasons behind the low 
levels of reporting of consumer fraud related crimes in Kenya. 
2.1.1 General rational choice theory 
This theory was advanced by Skogan (1984); Gottfredson and Gottfredson 
(1987) and Felson et al. (2002). According to this approach, the victims weigh 
the potential benefits and costs to be incurred when considering whether to file 
a complaint about a criminal incident with the police. In most cases, the benefits 
of filing a complaint include the victims drive to have the offenders brought to 
justice through punishment, protection of the victims, and potential victims of 
future victimization (Felson et al., 2002). In the instances of property crimes, the 
benefits of reporting crimes are also based on the anticipation of recovery of stolen 
goods. People may, however, fear to report crimes because of fear of reprisal from 
the offenders, embarrassment at having been victimized, and fear of reprisal 
from others in groups where cooperation with governmental officials is looked 
10 
Literature review 
�:  
.·'/ .-c:, :-----� , • ....,;:_-., 
down upon (Zhang, Messner anq .Liu;,z607). Another challenge may be the long
adjudication process that may ,9i� · ura�e--1�tims froril r· ,�?prting serious crim
es
(Felson et al., 2002). ! r tJ
� , �;, ) _, ·�I \-. ·-'.!: ·-1i
I � ,:- '.',. i! 
\ \ . -.;. 
2.1.2 Sociological theory �f , e behavi�ui\ofla,v i- 'I 
� ' ,;-_ \,,- / // 
This theory was advanced by Do\ri\.a ld"  Blac_ k in 1.9 7..6:'A/c)c o.'t/d ing to this approach, 
law is defined as government social·cont�fwbich_ _ is interpreted to mean a call 
or visit to the police, regulatory agency or a lawsuit. The quantity of law varies 
across time and space (societies, regions, communities, neighbourhoods, families 
and relationships). Black's theory carries implications for each of the three types 
of correlates of reporting: victim-specific, incident-specific, and neighbourhood­
specific. The theory brings forth various hypotheses that provide basis for the three 
correlates of reporting. The first hypothesis in the theory is that crime reporting 
is related to the socio-economic status of the victim. Under this hypothesis, lower 
ranks observe the law less than higher ranks, meaning that people of higher socio­
economic status are likely to report crimes than those of low status. 
The second hypothesis advanced by the theory is based on the relational 
distance on the quantity oflaw. Relational distance is said to be negatively related 
to law, whereby the closer the relationship between the victim and the offender, 
the less likely that the crime incident will be reported. On the other hand, the 
third hypothesis is about the 'radial location' concept where the level of social 
integration is positively related to law. This implies that people who are more 
integrated to mainstream society are more likely to report crimes than those 
who are less integrated. According to this hypothesis, employed people are more 
integrated in society than the unemployed people; married people are more 
integrated than the single people; hence employed people and married people are 
more likely to report crimes to the authorities than otherwise. 
To be able to study the effects of neighbourhood disadvantage, Black (1976) 
brings forth two theories: social stratification and social control, which provide 
some rationale for this. Under social stratification, the author postulates that law 
varies with the proportion of the population that is more or less wealthy. This 
implies an effect of community socio-economic conditions on crime reporting. In 
this case, people of higher socio-economic standing are expected to report crimes 
more often than those oflow wealth status.On the other hand, law varies inversely 
with social control, which is the normative aspect of social life. Law is said to be 
less important as a mechanism of social control since people are permitted to react 
to each other's conduct in a social context. The level of neighbourhood's social 
cohesion and informal control is, therefore, expected to be negatively related to 
crime reporting. 
11 
Factors determining consumerfr aud reporting in Kenya 
2.2 Empirical Literature 
Empirical literature on factors determining consumer fraud reporting is limited, 
just as the theoretical literature, with a majority of the available information 
dwelling much on personal and property crimes. According to Goldberg and Nold 
(1980) from whose work this study borrows, the analytical framework advances 
that the probability of reporting burglary depends on the loss involved, property 
damaged and the cost of reporting. The study uses the logit model and establishes 
that reporting, which is a victim-specific self protection mechanism, deters 
burglary victimization. MacDonald (1998) follows the same analytical framework, 
while addressing under-reporting of property crime in Britain using the probit 
model and establishes that unemployment reduces the probability of reporting 
burglary. While these may not be directly related to this study, they provide a good 
analytical framework for consumer fraud crime reporting, hence are worth being 
reviewed. 
Most of the studies on consumer fraud have focused on the factors determining 
victimization. Anderson (2006), while looking at the effect of demographics 
on identity theft in the United States of America using a multivariate probit 
regression, concludes that the risk of identity fraud generally appears to be 
related to demographics. Those with higher incomes are more likely to be victims 
of identity fraud. Older people, on the other hand, face a reduced risk of identity 
fraud victimization than younger people. A household with one adult and more 
children leads to increased identity fraud victimization. In addition, women are 
more likely to be victimized than men. 
Ippolito and Mathias (1989), while studying health claims in advertising 
and labeling of the cereal market in the United States of America, using both 
probit and tobit regression methodologies, suggest that more education of the 
consumers amounts to increased awareness. Educated people have a lower risk of 
identity theft crime victimization. This is also supported by McGhee (1983); and 
Jinkook and Horacio (1997). McGhee (1983) establishes that higher educational 
attainment improves the coping abilities of the elderly people to fraud, while 
Jinkook and Horacio (1997), using ordered logit regression in the USA, determine 
that less educated consumers are more vulnerable to consumer fraud. A contrasting 
finding is advanced by Titus, Heinzelmann and Boyle (1995) who establishe that 
younger as well as educated people are victimized more often by personal fraud 
in the USA. This is surprising since education seems not to provide a protective 
cover expected from this type of crime, generally characterized as being a battle of 
the mind. Jinkook and Horacio (1997) also establish that age, marital status and 
income also influence consumer vulnerability. 
12 
Literature review 
Macdonald (1998) and Zhang, Messner and Liu (2007) establish that offense 
seriousness is a significant predictor of reporting for both property and personal 
crimes. The former uses the probit regression method from the British Crime 
Victimization survey data for the years 1994 and 1996, while the latter uses a 
logistic regression method from the criminal victimization data for Tanjin, China 
in 2004. Zhang, Messner and Liu (2007) also note that victimization experience, 
which is an individual-specific variable, has a negative effect on reporting robbery/ 
assault, when other factors are controlled. The negative effect could imply that the 
victims are less hesitant to turn to the police as victimization increases. On the 
other hand, according to Macdonald (1998), the probability of reporting decreases 
if the victim is currently unemployed. 
Both regionally and locally, there is little documented evidence on consumer 
fraud, let alone on consumer-related crimes. According to Deloitte (2013), the 
most prevalent financial crimes in the East African region are cash theft, cheque 
fraud, and asset misappropriation. Most of these crimes◄ are committed as a 
result of weak internal control systems, which are incident-specific factors. On 
reporting, financial organizations prefer to understate figures on losses, and 
majorly deal with those crimes experienced internally without raising eyebrows 
to prevent negative effects of reduced investor confidence on their performance 
in the market. 
◄ It is a form of consumer fraud.
13 
Factors determining consumer fraud reporting in Kenya 
3. Methodology
The main aim of this study is to determine the factors that inform reporting of 
consumer fraud victimization in Kenya. From literature, several methods have 
been used to analyze data on issues of consumer fraud-related crimes, which 
mainly include the probit and logit methodologies. This study utilizes a logit 
model to carry out the analysis because of the binary nature of the dependent 
variable based on the decision to report or not consumer fraud to the police or any 
other agency. 
3.1 Conceptual Framework 
The general rational choice theory as well as the sociological theory of the behaviour 
of law is advanced in this study. As a result, the individual-specific variables, the 
incident-specific variables, and the neighbourhood-specific variables are used 
in the conceptualization of consumer fraud reporting. The study therefore seeks 
to establish if these variables influence consumer fraud reporting in Kenya. 
According to the two theories, the drivers of reporting consumer fraud are the 
individual-specific variables, including gender, marital status, location, income, 
age, occupation and employment status. For instance, it is expected that males, 
people who are married, people living in urban areas, people who have a higher 
Figure 3.1: Conceptual framework for consumer fraud reporting in 
Kenya 
lndMduakpedllc lttrlbutm: 
�ndff, eduution, marital status, 
loatlon, Income, •1•. 
_ocrupotton, employment. number 
. af meml»n in the hous.hokl 
fResiorti� 
■ f ot l 1----·- · 
i. consumer 
imud l 
L _ _ _j
......... ,w- sta� Income 
aftlle� 
Source: Author's construct 
14 
-
Methodology 
income, older people, and employed people are expected to report consumer 
fraud. 
In addition, incident-specific variables (mode of fraud, type of fraud, and the 
value lost) affect reporting behaviour of consumer fraud. For instance, the higher 
the value lost, the higher the probability consumer fraud will be reported to the 
authorities. Neighbourhood-specific status comprises of the wealth status of the 
victim; the wealthier the person, the higher the likelihood that a consumer fraud 
will be reported to the authorities and vice versa. 
Perception towards the police and other relevant agencies affects reporting 
behaviour of consumer fraud. It is expected that both the incident-specific, 
individual-specific, and neighbourhood-specific correlates influence the perception 
towards the police and other relevant agencies, which influence whether to report 
consumer fraud or not. A negative perception leads to lack of confidence in the 
police and other relevant agencies, which hinders consumer fraud reporting. 
3.2 Model Specification 
Goldberg and Nold (1980) model is on the household's probability of reporting a 
crime as a function of the loss involved, property damage, and the cost of reporting. 
Crime reporting may vary depending on individual attributes, experiences and 
personal circumstances specific to the incident. According to MacDonald (1998),
the model can be represented as follows: 
Pr(reporting)=f(incident involves loss, socio-economic factors, incident specific 
factors, attitudes to the police) .............................................................................. (!)
This can be expressed as: 
Pr(reporting CF)=/3 +{3,GEN+/3 LOC;+/3flD
i U;+f3J1A 0 R +/3/i YP +{32 i VAL +/36 i /E Ri 
+/3/vOH;+/3/NC;+/3 0CC;+/J t4GG;+er································································(2) 
10 1
where E\ represents the error term and CF is consumer fraud. 
3.3 Estimation Technique 
An individual's tendency to report a crime is not observable; rather the reporting 
outcome for each specific incident, which is a binary outcome is observed: either 
reported or not. These can be estimated through logit, probit or linear probability 
model (LPM). This study adopts a logit model in identifying the factors that 
determine reporting of consumer fraud victimization in Kenya. While the study 
takes cognizance of the fact that either LPM or probit models could be used in the 
15 
Factors determining consumer fraud reporting in Kenya 
analysis, there are certain weaknesses associated with the two. For instance, LPM, 
which is similar to ordinary least squares regression though applied to a binary 
dependent variable, has several weaknesses. It has a heteroskedastic error term 
that leads to biased estimates, and its fitted probabilities may lie outside the 0-1 
range. The preference for the logit model follows the assumption of the distribution 
of the error term, which follows a logistic distribution. The distribution of the 
error term for a probit model follows a normal distribution. Both distributions of 
the error term are similar in shape, though the logistic distribution has a heavier 
tail (higher kurtosis) than the normal distribution, which increases the robustness 
of the analysis. Since the dependant variable is binary in nature, the probability 
i; 
of reporting a consumer fraud crime to either the police or any other agents is 
coded as 1 or o otherwise. It is convenient to use and express the cumulative 
density function (cdf) and probability density function (pdf), respectively, of a 
logit distribution. The pdf is expressed as: 
-'
e
A.(/) • - 00 < I < 00 ................................................................................ 
(3) 
=
(I I +e- )2 
The cdf as: 
p= p(lsx;Pl=-- 1  . . ............................................................................................. (4) 
I +f'(,,.8) 
then Pr[y;=l/x;] and Pr[y;=o/x;], which represent whether a consumer fraud is 
reported to the police or other authorities and otherwise, respectively, can be 
expressed as: 
�
=[Pr(y, = x,] = tu' exp(x; ) .................................................................... (5)p II /J)= l+e(x;,D) and 
l-p=Pr[y;=0/x;)=I-A(x'/1;)=1 exp(x;�) Il+exp(x,P) 
= l+exp(,x; P) .................... (6)
Equation (5) represents the probability of reporting a consumer fraud to the police 
or other authorities by a victim, while equation (6) represents the probability of 
not reporting. 
The marginal effects are derived from equation (5), where interpretation for 
both sign nd significance is important. Equation (5) is differentiated to give the 
marginal effects as: 
ap
-[ �--] ' ={A(.t'.8,)(1-A(x'.8,))}.8, ............................................................................. (7)
ch-, 
16 
Methodology 
- -------------------- -
The odds ratio is given by ,--1L=exp(x;P)while the log odds ratio or logit is given 
b 1-p,y: 
In --1!L = exp(x;p) •··························································································(8) 
1-p;
Equation (8) can also be expressed as 
In !_�, = /3 + /3 x; 2 .......................................................................................... (9)1 1 
where /J,, /3 represent parametre vectors, while x·; represents explanatory 
2 
variables that are individual-specific, incident-specific and neighbourhood­
specific. Equation (9) can be transformed into the following using the explanatory 
variables in equation (2): 
In[ Pr(reportCF
= 1)]
Pr(reportCF = 0) 
=/3 +{3 GEN.+{3 LOC.+/3 EDU.+{34 M•-AR.+(3 TYP.+{3 VAL.+{3 PER.+{3 MQH.+{3 INC. 0 J I 2 I J I ...,.._I 5 I 6 I � I it' 'I' I 9 I 
+f3 OCC;+f3 t4GGr·······························································································(10)
10 1
The logit model is a fully linear function of the explanatory variables, x, and uses 
the maximum likelihood estimation technique, which maximizes the likelihood of 
an event occurring. 
3.4 Data and Variables Specification 
The study uses cross-sectional data obtained from the Crime Victimization Survey 
conducted by KIPP RA in collaboration with the United Nations Office on Drugs and 
Crime in 2010. This was a national survey targeting a sample of 3,000 households. 
The individuals were accessed and interviewed. The sampling process was carried 
out by the Kenya National Bureau of Statistics (KNBS) using the National Sample 
Survey and Evaluation Programme (NASSEP IV). An initial sample of 162 rural 
and 138 urban clusters spread in all the 67 districts in Kenya was drawn. The 
households were sampled systematically, with a random start. No replacement 
was to be allowed for 'away' or relocated households. This was because the specific 
households were drawn using the name and number of household as in the frame. 
17 
Factors determining consumer fraud reporting in Kenya
However, due to cost implications, the districts were narrowed down to 30, with 10 
households from each cluster. Consumer fraud contributes to about 21.9 per cent
,· of the total crimes, making it the largest individual category of crimes committed 
against persons. 
Table 3.1: Definition and measurement of variables 
•:variable I Description of variable Measurement of Apriori expectation 
,. 
I• I variable 
_!.. ___ 
; Report i Reporting of consumer fraud Dichotomized variable -
I j to the police or any other representing whether a 
i agency consumer fraud victim 
I reports to either the police 
! 
! I or any other agency (1) or 
I otherwise ( o) I 
. GEN ! Gender of the respondent Dummy variable (1 if Indeterminate 
l male, o otherwise) 
I 
;we Location of the respondent Categorical variable (1 if 
I Indeterminate i rural, 2 if urban) 
:EDU Education level of the Categorical Positive relationship: 
! respondent higher education means 
i likelihood to report 
MAR Marital status of the Categorical Indeterminate 
respondent 
[TYP Type of consumer fraud that Categorical Positive 
I the respondent experienced 
VAL Value lost by the respondent Continuous Positive 
in Kenya shillings 
;PER Perception of the victims Categorical Positive 
about the police' ability to 
t control crime 
NOH Number of members in the Continuous Indeterminate 
household 
'rINc Income of the victim Continuous Positive 
occ Employment status of the Categorical Positive 
victim 
-
u\GG Age group of the victim Continuous - - ��--• Indeterminate 
18 
4. Results and Discussions
4.1 Descriptive Statistics 
The population distribution in the sample set for people who experienced 
consumer fraud is almost uniform as far as gender is concerned, with 57 per cent 
females and 43 per cent males. For the people who experienced consumer fraud, 
29 per cent have no education or have not completed primary education, hence 
do not have a primary school certificate; 24 per cent have primary school level of 
education; 32 per cent have secondary school education; while 15 per cent have 
college or university education. Fifty one (51) per cent of the people in the sample 
who experienced consumer fraud live in urban areas, while 49 per cent are in rural 
areas. 
The most common consumer fraud in Kenya is the proliferation of counterfeit5 
goods or provision of poor services, which mainly occurs in shops. This accounts 
for 65.2 per cent of the total consumer fraud. Fraudulent schemes and other fraud 
account for 19.9 per cent, while payment for non-existent goods or services and 
stolen financial instruments or forged cheques accounts for 14.9 per cent of the 
total consumer fraud. From the sample of victims, 69 per cent lost between Ksh 
0-1,000, 26 per cent between Ksh 1,001-10,000, 3.4 per cent Ksh 10,001-100,000
and 0.9 per cent Ksh 100,001-1,500,000. Out of those people who experienced
consumer fraud, 13.7 per cent perceive the police to be doing a very good job, 41.9
per cent believe they are doing a fairly good job, 24.8 per cent believe it is a fairly
poor job, and 19.6 believe they are doing a very poor job.
From the sample of consumer fraud victims, 94-4 per cent had incomes of 
between Ksh o-<50,000; 2.5 per cent Ksh 50,ooo-<100,000; and 3.1 per cent 
Ksh>100,ooo. On marital status, 67.2 per cent represented the married people 
or people living as couples, 23.3 per cent were single, while 9.5 per cent were 
widowed, divorced or separated. Of the victims, 32.9 per cent had small families of 
between 1-3 family members, 49.7 per cent had medium family of 4-6 members, 
while 17.4 per cent had large families of 7-10 members. 
From the data, proliferation of counterfeit goods or provision of poor services 
are mostly reported to the authorities compared to other types of consumer fraud, 
accounting for 38.5 per cent of the reported consumer crimes. This could be due to 
the fact that most consumer fraud occurring in Kenya mainly involves counterfeit 
products and services. Reporting of fraudulent schemes accounts for 26.92 per 
cent; this might have been influenced by pyramid schemes that existed in the 
country in 2006-2007. A lot of focus was placed on how to address the problem, 
5 Referred to as fake goods in the data source. 
19 
Factors determining consumer fraud reporting in Kenya 
especially from the National Assembly by establishing a taskforce on pyramid 
schemes to collect views from the victims across the country. This might have 
influenced the reporting of this form of consumer fraud. Payment for non-existent 
goods or services accounts for 23.08 per cent of the reported consumer crimes, 
while reporting of stolen financial instruments and forged cheques accounts for 
11.54 per cent. 
The sample data on consumer fraud also shows that 43.8 per cent of the 
victims were employed; 10.9 per cent were unemployed or looking for work; 23.4 
per cent were homekeepers, retirees or disabled; and 21.9 per cent were either 
going to school or college. Additionally, 23.8 per cent of the sampled population 
that experienced consumer fraud was below 25 years in age; 32.9 per cent were in 
the 26-35 years age group; 31.8 per cent were in the 36-55 years age group; and 
11.5 per cent were above 55 years. 
4.2 Diagnostic Tests 
Reporting of consumer fraud to either the police or other agencies was modeled 
against eleven (11) explanatory variables that influence reporting of consumer 
fraud. The underlying hypothesis is that level of education, the value lost, 
perception of police about controlling crime, and victim's income influence the 
decision to report a consumer fraud. The logistic regression model was evaluated 
Table 4.1: Test for multicollinearity 
' 
Model Collinearity statistics 'II 
Variable VIF t/VIF (Tolerance) 
; 
l EDU 1.28 0.781 
LOC 1.21 0.828 
VAL 1.14 0.874 -� 
INC 1.12 0.894 
1YP 1.04 0.959 
GEN 1.17 0.856 
1 
NOH 1.07 0.935 
MAR 1.46 o.686
il. PER 1.06 0.94 
I 
occ 1.09 0.918 
AGG 
-- - . - 1.42 0.703 _,; 
20 
Results and discussions 
for muliticollinearity using the variance inflation factor (VIF)6 as reported in Table 
4.1, and heteroskedasticity using the White test7 (Table 4.2). The variance inflation 
factor indicated that collinearity among the analyzed variables was not high. The 
null hypothesis for homoskedasticity as per Table 4.2 was rejected, meaning the 
model contained the problem of heteroskedasticity. This was addressed by use of 
robust standard errors. 
4.3 Estimation Results 
From Table 4.3, the level of education of the consumer does not seem to influence 
reporting consumer fraud. This, even though surprising, is consistent with the 
findings of Titus, Heinzelmann and Boyle (1995) on issues of personal fraud. This 
means that both educated and non-educated people stand a chance of failing to 
report consumer fraud once they become victims. Income levels of the victims do 
not influence reporting of consumer fraud, which is not consistent with the social 
stratification strand in Black's theory of the behaviour of law. The victims who 
are well of as far as income levels are concerned do not seem to report consumer 
fraud more often than their counterparts who are of lesser income levels. Marital 
status, which is postulated in the third hypothesis of Black's sociological theory of 
law under the radial location concept as a determining factor of crime reporting, 
fails to be important. Other independent variables that are not important include: 
Table 4.2: White heteroskedasticity test 
White's test for H : homoskedasticity 
0
Against H.: unrestricted heteroskedasticity 
Chi2(75) = 106.62 
Prob > chi2 = 0.0096 
Cameron & Trivedi's decomposition ofIM-test 
. � � 
Source Chi2 df p 
' 
Heteroskedasticity 106.6 75 0.01 
Skewness 61.91 : 11 0 
I 
Kurtosis 31.51 1 0 
Total 200.1 87 0 l ' 
6 The variance inflation factor measures the impact of collinearity among independent 
variables in a regression model on the precision of estimation. It shows how the variance 
of an estimator is inflated by the presence of multicollinearity. A variance inflation factor 
will be 1, if there is no collinearity between any two independent variables, while it will rise 
as the extent ofc ollinearity increases, with a value of 10 being considered high. A tolerance 
value ofless than 0.1 is comparable to a VIF of 10. 
7 Since p=o.0024 and < than 0.05, the null hypothesis ofh omoskedasticity is rejected. 
21 
Factors detennining consumer fraud reporting in Kenya 
Table 4.3: Estimation results 
Variables Marginal z-values Odds ratio z-values
effects 
GEN (reference group is female) 
Male -0.0056059 -0.64 0.7168431 -0.65 
LOC (reference group is urban) 
i. Rural 0.011874 1.28 1.973972 1.24 Ii 
I EDU (reference group is no education/incomplete primary) 
,p,  ----- - -- ---
Primary -0.0075588 -0.84 0.611303 -0.76 
t--- ---- ·--- - ------
1· Secondary -0.0063293 -0.65 0.6755076 -0.61 
·---
I I University -0.0046019 -0.45 0.7434659 -0.42 
TYP (reference group is paid for non-existent services/goods or stolen forged/forged cheque 
--·-------- --· 
Given fake goods/poor services -0.0351567"* -2 0.218075•-- -2.69 
·------ ·--
Fraudulent schemes and others -0.0084102 -0.98 0.5659001 -0.96 
VAL (reference group is 0-1000) 
1,001-10,000 0.0232905• 1.73 2.805716** 1.98 
10,001-100,000 -- 0.1231821 1.49 9.732772*"• 2.95 
100,001-1,500,000 0.6655339 ... 3.21 126.3791••· 4.92 
PER (reference group is very good job) 
Fairly good job 0.0225064 0.78 3.127203 0.94 
Fairly poor job 0.0433323 0.85 4.910864 1.35 
Very poor job 0.1099935 1.11 12.84388** 2.19 
INC (reference group is o-<50000) -·
50,000-< 100,000 -0.0108165 -1.49 0.3915682 -1.07
>=100,000 _,_ 
MAR (reference group is single) 
Married/living as a couple -0.0022492 -0.19 0.8798812 -0.2 
Divorced/separated or widow/widowed -0.0144881 -1.54 0.2627063 -1.04 
NOH (reference group is 1 to 3) � 
4 to 6 (medium) 0.0101909 0.98 1.794272 1.11 
7 to 10 0arge) -0.0025396 0.17 1.151704 0.18 
OCC (reference group is working) 
Looking for work (unemployed) 0.0091705 0.52 1.5656 0.62 
Keeping home/retired/disabled -0.0127575 -1.44 0.4044933 -1-49 
, Going to school /college or other -0.0106147 -1.52 0.4781848 -1.22' 
AGG (reference group is <=25}'l"S) 
26-35yrs 0.0136711 0.9 2.007201 0.951 
36-55}'l"S 0.0033536 0.22 1.207642 0.22 
>ssyrs 0.0421268 1.12 3.99645• 1-77, 
..__. 
Number of Observations (N) 624 624 
Pseudo R"2 0.2419 
,·'• 0.2419 . . . 
*Significant level at 10%; .,. Significant level at 5%; *** Significant level at 1%
22 
Results and discussions 
location, gender, employment status and the size of the family in terms of the 
number of household members. 
The type of consumer fraud appears to influence the reporting behaviour, 
specifically fraud that occurs with respect to counterfeit products or provision of 
poor services. From the results, the direction of the relationship between reporting 
and the type of consumer fraud is negative, implying a marginal change in type 
of crime as far as counterfeits or poor services are concerned. This will lead to a 
decrease in the rate of consumer fraud reporting to the authorities. The result is 
statistically significant at 5 per cent, with the marginal effects showing that an 
increase in the proliferation of fake goods in the market by one unit reduces the 
probability of reporting consumer fraud to the authorities by 3.5 per cent from 
the mean (0.6458). This finding, apart from being consistent with the incident­
specific correlate of reporting crime, also lends insightful information to combat 
counterfeits in the country, with results showing that the more the people become 
victims, the less they are likely to report such crimes to the authorities. 
Value lost by the victims also positively impacts the reporting behaviour, 
especially with victims who lose large sums of money in consumer fraud likely to 
report more than those who lose less significant sums. The result is statistically 
significant at 1 per cent, with the marginal effects showing that an increase in the 
amount of money lost in consumer fraud by one unit will increase the probability 
of reporting the crime by 67 per cent from the mean (0.0096). This finding is in 
agreement with the incident-specific correlate, with the value lost in a consumer 
fraud being a determining factor as to whether the crime will be reported or not. 
It also agrees with the findings of Macdonald (1998) and Zhang. Messner and 
Liu (2007) who establish that offense seriousness is a significant predictor of 
reporting for both property and personal crimes. 
The perception of the victims to the police and other authorities positively 
impacts the reporting behaviour of consumer fraud. However, the poor perception 
of the victims towards the police and other authorities seems to impact consumer 
fraud reporting more and at 5 per cent significance level. The marginal effects are, 
however, positive but insignificant. On examining the odds ratio, the conclusion 
is that for every change in perception about the police and other authorities' 
performance in combating any form of crime, the odds of reporting crime 
improves by 12.8 per cent, holding other factors constant. This finding is consistent 
with Goldberg and Nold (1980) modeling of crime reporting as a function of 
the attitudes to the police. The finding, therefore, lends a lot of credence to the 
government efforts of reforming security agencies to tackle crimes effectively. 
These reforms of the security agencies, specifically the police, will increase citizens' 
confidence in the systems and improve levels of consumer fraud reporting. The 
23 
... 
Factors determining consumer fraud reporting in Kenya 
age group of the victim is also important in explaining consumer fraud reporting 
on examining the odds ratio. People who are above 56 years have improved odds 
of reporting consumer fraud by 4 per cent, holding other factors constant. This 
could be attributed to the fact that older people are wiser and careful in decision 
making than younger ones. For instance, older people are careful not to engage 
in risky investment ventures in anticipation of higher returns compared to the 
younger generations who have a higher affinity for quick money and shortcuts, 
hence becoming victims of consumer fraud. 
24 
5. Conclusion and Policy Recommendations
5.1 Conclusion
There is limited research on consumer fraud in Kenya, despite the negative socio­
economic costs associated with it. Victims are less interested in reporting these
crimes to the authorities as per the findings of the crime victimization survey of
2010 in Kenya. This research is an attempt to put this subject into perspective and
understand why victims do not report crimes to the authorities. Demographic,
incident-specific and neighbourhood indicators are examined to determine their
effects on low reporting of consumer fraud. 
Descriptive results show that the most common consumer fraud in Kenya is 
the proliferation of counterfeit goods or provision of poor services, which mainly 
occur in shops. The influx of counterfeit goods is, therefore, a policy challenge and 
the war against them by the government must be sustained, if not improved, since 
they are most prevalent and poses serious dangers as relates to consumer fraud. In 
addition, the study establishes that proliferation of counterfeit goods is the crime 
that is most reported to the security agencies though, in total, reporting is low. 
This could be attributed to the fact that most of the consumer fraud experienced 
by victims in the survey comprised of proliferation of counterfeit goods. Other 
consumer fraud experienced as per the survey include fraudulent schemes; 
payment of non-existent goods or services; and stolen financial instruments and 
forged cheques. 
Results from the study show that the type of consumer fraud (specifically, 
counterfeit products or provision of poor services) influences the reporting 
behaviour of victims. Victims who buy counterfeits repeatedly or receive poor 
services do not seem to be interested in reporting it to the authorities. This may 
imply lack of awareness on the rights and privileges of consumers when faced 
with counterfeits. The more they experience these crimes, the more they fail 
to report. This permissive attitude from the victims acts as a deterrence to the 
fight against counterfeits in the country. While levels of consumer awareness on 
what constitutes counterfeits may be a concern, the survey done in 2010 shows 
that most consumers were in a position to distinguish between counterfeits and 
non-counterfeits. More sensitization can be done to increase awareness amongst 
the consumers. High poverty levels may also be a probable indicator of low 
levels of reporting. Campaigns against counterfeits need to be stepped up both 
by government agencies such as ACA, KRA and KEBS; ·and private and non­
governmental or�anizations involved in consumer protection and advocacy. The
awareness campaigns should also place emphasis on the reporting avenues, where 
and how to report based on the type of offence. 
25 
Ii Factors determining consumer fraud reporting in Kenya 
I 
I 
l 
Perception about police performance in controlling crime influences the 
reporting of consumer fraud by victims, with those who believe they are doing 
a poor job less likely to report consumer fraud to them. This implies that there 
is need to improve confidence in the police service to foster crime reporting. A 
negative perception about the police deters consumer fraud (crime) reporting and 
hinders the fight against the vice. 
5.2 Policy Recommendations 
The study findings suggest that the most prevalent consumer fraud in Kenya 
involves proliferation of counterfeit goods, and provision of poor service to 
clients. This brings into perspective the fact that the fight against counterfeits 
remains a major challenge in the country. This fight should therefore be sustainM 
in momentum, if not improved, to deal with the growing trend of counterfeiting. 
To sustain this war, there is need to review the Anti- Counterfeit Agency (ACA) 
Act in order to address issues of consumer reporting. This will create consistency 
with the Consumer Protection Act No. 46 of 2012, which identifies reporting as an 
important ingredient in enabling consumers get redress incase of any violation. 
Second, the ACA should be strengthened in terms of capacity. More financial 
resources should be allocated to the agency to enable it hire more personnel and 
widen its presence across the country. A widened presence will ease consumer 
access to the ACA officers and enhance reporting. 
Third, the agency needs to carry out awareness campaigns through the available 
communication channels such as the radio, television sets, newspapers, posters 
and bill boards, internet, and mobile phones. The campaigns should be directed at 
creating awareness on: ability for the consumer to differentiate counterfeits from 
original goods, the dangers exposed in consuming counterfeits, and the reporting 
mechanisms available in case of victimization. Herein, the agency should embrace 
a digital reporting platform through the mobile phones and the internet for 
consumers. The awareness should also emphasize how and where to report based 
on the type of offence; for instance, counterfeiting should be reported to the 
agency, while issues of false advertising should be reported to the CAK. 
Fourthly, there is need for collaboration between various agencies engaged 
in the fight against counterfeits. These agencies include: the Kenya Bureau of 
Standards, the Kenya Revenue Authority, the Anti-Counterfeit Agency, and the 
Pharmacy and Poisons Board. These multiple agencies can be harmonized by 
establishing a common complaints platform. This can either be an internet or 
short message service platform that will enhance intelligence gathering, sharing 
and enforcement. 
26 
Conclusion and policy recommendations 
Similarly, the study finds that negative perception by the public towards 
the police influences the reporting behaviour of the victims of consumer fraud. 
Genuine attempts to improve service delivery by the police to the populace will 
improve public perception and confidence.The ongoing police reforms should, 
therefore, be sustained and fast-tracked to improve reporting of crime, which 
includes consumer fraud. There is also need to build the capacity of police on 
consumer crimes to facilitate response and enhance reporting. 
5.3 Study Limitations 
The questionnaire did not expressly contain questions on why consumer fraud 
was not reported to the police or any other agencies. In addition, the choice to 
report to the other agencies and not to the police, or to report to the police and not 
the other agencies needed to be interrogated further from the questionnaire. The 
aspects of consumer fraud that were considered in the study were limited to those 
highlighted in the survey. The study acknowledges that the subject matter is wide 
and more issues can be considered using comprehensive data. 
5.4 Future Research 
A deeper understanding of these issues will provide clear direction to policy 
implementers and future research encompassing the issues that should be 
undertaken. Future research should be carried out using new data capturing 
developments and evolution of consumer fraud, considering technological 
advancements in the digital space. 
27 
Factors detennining consumer fraud reporting in Kenya 
References 
Anderson, B. A. (2006), "Who Are the Victims of Identity Theft? The Effects of 
Demographics," Journal of Public Policy and Marketing, 25(2), 160-171. 
Baumer, E. (2002), "Neighborhood Disadvantage and Police Notification by 
Victims of Violence," Criminology, 40, 579-616. 
Black, D. J. (1971), "The Social Organization of Arrest," Stanford Law Review, 23, 
1087-111. 
Black, D. J. (1976), The Behaviour of Law, New York: Academic Press. 
Consumer Unity and Trust Society International (2012), State of the Kenyan 
Consumer Report, Nairobi. 
Deloitte (2013), Financial Crimes Survey Report: Where is the Exposure? East 
Africa. 
Felson, R. B., Messner, S. F., Hoskin, A. and Deane, G. (2002), "Reasons for 
Reporting and Not Reporting Violence to the Police," Criminology, 40, 
617-648.
Goldberg, I. and Nold, F. C. (1980), "Does Reporting Deter Burglars? An 
Empirical Analysis of Risk and Return in Crime," Review of Economics 
and Statistics, 62, 424-431. 
Gottfredson, M. R. and Gottfredson, D. M. (1987), Decision Making in Criminal 
Justice: Towards the Rational Exercise of Discretion (2nd ed.), New York: 
Plenum Press. 
Government of Kenya (Various), Laws of Kenya, Nairobi. 
Government of Kenya (2010 ), Constitution of Kenya (2010 ), Nairobi. 
Greene, W. H. (2002), Econometric Analysis (5th ed.), New York: Macmillan. 
Hindelang, M. J. (1976), Criminal Victimization in Eight American Cities: A 
Descriptive Analysis of Common Theft and Assault, Cambridge, MA: 
Balinger. 
Hindelang, M. J. and Gottfredson, M. (1976), The Victim's Decision Not to Invoke 
the Criminal Justice Process, Criminal Justice and the Victim (William F. 
McDonald), Beverly Hills, CA: Sage. 
Holtfreter, K., Reisig, M. D. and Blomberg, T. G. (2005), "Consumer Fraud 
Victimization: An Empirical Study," Thomas L. Rev., 18, 791. 
28 
References 
Ippolito, P. M. and Mathios, D. A. (1989), Health Claims in Advertising and 
Labeling: A Study oft he Cereal Market, ITC: Bureau of Economics Staff 
Report. 
Jinkook, L. and Horacio, S. B. (1997), "Consumer Vulnerability to Fraud: 
Influencing Factors," Journal of Consumer Affairs, 31(1), 70-89. 
Kenya Association of Manufacturers (2012), The Study to Determine the Severity 
of the Counterfeit Problem in Kenya, Nairobi. 
Kenya National Bureau of Statistics (Various), Statistical Abstract, Nairobi: 
Government Printer. 
K.IPPRA and UNODC (2010), Victimization Survey in Kenya, Nairobi: Kenya 
Institute for Public Policy Research and Analysis. 
KPMG (2003), Fraud Survey (Forensic). 
Kusic, J. (1989), White Collar Crime Prevention Handbook, Vienna, VA: White 
Collar Crime. 
Macdonald, Z. (1998), "The Under Reporting of Property Crime: A Micro 
Econometric Analysis," in Discussion Paper on Public Sector Economics, 
Department of Economics, University of Leicester. 
McGhee, J. L. (1983), "Vulnerability of Elderly Consumers," International Journal 
ofA ging and Human Development, 17(3), 223-246. 
Moore, E. and Mills, M. (1990), "The Neglected Victims and Unexamined Costs of 
White Collar Crime," Crime and Deliquency, 36, 408-418. 
Mustaine, E. E. and Tewksbury, R. A. (2000 ), "Comparing the Lifestyles of Victims, 
Offenders, and Victim-Offenders: A Routine Activity Theory Assessment 
of Similarities and Differences for Criminal Incident Offenders," 
Sociological Focus, 33(3), 339-362. 
PWC (2014), Economic Crime: A Threat to Business Processes (Global Economic 
Crime Survey: Kenya Report), Price Waterhouse Coopers. 
Pyramid Schemes Commission (2010), Nyenze Taskforce Report on Pyramid 
Schemes, Nairobi. 
Skogan, W. G. (1984), "Reporting Crime to the Police: The Status of World 
Research," Journal of Research in Crime and Delinquency, 21, 113-137. 
Titus, R. M., Heinzelmann, F. and Boyle, J. M. (1995), "Victimization of Persons 
by Fraud," Crime and Delinquency, 41(1), 54-72. 
29 
Factors determining consumer fraud reporting in Kenya 
Tseloni, A (2000), "Personal Criminal Victimization in the US: Fixed and 
Random Effects of Individual and Household Characteristics," Journal of 
Quantitative Criminology, 16(4), 415-442. 
United Nations Interregional Crime and Justice Research Institute - UNICRI 
(2000), International Criminal Victimization Survey, United Nations 
Interregional Crime and Justice Research Institute, Retrieved from 
http://www.unicri.it/ services/library_ documentation/p ublications/ 
icvs/data/ 
United Nations Office on Drugs and Crime - UNODC (2005), Report on Why 
Fighting Crime Can Assist Development in Africa. 
Zhang, L., Messner, S. F. and Liu, J. (2007), "An Exploration of the Determinants of 
Reporting Crime to the Police in the City of Tianjin, China," Criminology, 
45(4), 959-983. 
30 
Appendix 
Appendix Table 1: Correlation of reporting of consumer fraud and 
explanatory variables 
gen Joe edu mar typ val per noh inc 
gen 1.0000 
Joe -0.0220 1.0000 
edu 0.1729 -0.2818 1.0000 
mar -0.2034 0.1428 -0.2523 1.0000 I 
typ -0.0783 -0.0404 -0.0630 -0.0123 1.0000 
val 0.2368 -0.0703 0.2393 -0.0607 -0.1354 1.0000 
per 0.0382 0.1316 0.0348 -0.0240 0.0550 0.0198 1.0000 
noh -0.0739 0.2150 -0.1050 0.0250 -0.0001 -0.0150 0.0641 1.0000 
inc 0.0425 -0.1849 0.2156 -0.0465 -0.0195 0.1513 -0.1432 0.0399 1.0000 
occ -0.1579 0.0995 -0.1141 -0.0781 -0.0681 -0.0883 0.0665 0.0320 -0.1187� 
agg 0.0249 0.2015 -0.2078 0.4947 -0.0412 0.0434 0.0684 0.0306 -0.0577 I 
occ agg 
occ 1.0000 I 
agg -0.0953 1.0000 - - - j 
A_ p_J>end ix"  Ta  bl e 2 
: De sc riptiV e  statistics (N = 644) 
Variable Proportion Std. 95% Conf. lnte��l-,. 
Error. 
GEN 
Female 0.5729814 0.0195069 0.5343136 0.6107773, 
Male 0-4270186 0.0195069 0.3892227 0-4656864 
·-,
LOC 
i 
Urban 0.5108696 0.0197134 0-4721713 0.549438
Rural 0.4891304 0.0197134 0-450562 0.5278287\
EDUC 
No education/incomplete 0.2950311 0.0179851 0.2609812 o.3315304i 
primary 
Primary 0.2437888 0.0169326 0.2120897 0.2785508 
Secondary 0.3167702 0.0183464 0.2818886 0.3538413 ,, 
University/c ollege 0.1444099 0.013862 0.1192614 0.1738149 
TIP 
Paid for nonexistent services/ 0.1490683 0.0140454 0.1235366 0.1788004 
goods or stolen forged/forged 
cheque 
Given fake goods/poor services 0.6521739 0.0187827 0.6144406 0.688089 
31 
Factors detennining consumer fraud reporting in Kenya 
Fraudulent schemes and others 0.1987578 0.0157376 0.1696474 0.2314708 
VAL 
0-1000 0.6925466 0.0181974 0.6557092 0.727083 
1001-10000 0.2639752 0.0173829 0.2312808 0.2994906 
10001-100000 0.0341615 0.0071633 0.0225718 0.0513891 
100001-1500000 0.0093168 0.0037887 0.0041826 0.0206226 
PER 
Very good job 0.136646 0.0135453 0.1121575 0.1654847 
. Fairly good job 0.4192547 0.0194593 0.3815977 0.4578762 
Fairly poor job 0.2484472 0.0170409 0.21651 0.2833915 
Very poor job 0.1956522 0.0156444 0.1667413 0.228203 
INC 
0-<50000 0.9440994 0.0090597 0.9234072 0.9594469 
50000-<100000 0.0248447 0.0061383 0.0152551 0.0402163 
>=100000 0.0310559 0.0068409 0.020098 0.0476976 
-·
'MAR 
Single 0.2329193 0.0166693 0.2017963 0.2672353 
Married/Jiving as a couple 0.6723602 0.0185095 0.6350372 0.7076238 
Divorced/separated or widow/ 0.0947205 0.011548 0.0743463 0.1199545 
widowed 
NOH 
1 to 3 (small) 0.3291925 0.0185318 0.2938763 0.3665498 
4 to 6 (medium) 0.4968944 0.0197177 0-4582713 0.5355546
7 to 10 Oarge) 0.173913 0.0149477 0.1464836 0.2052436 
occ 
Working 0-4378882 0.0195653 0.3999137 0.4766047 
looking for work (unemployed) 0 .1086957: 0.0122748 0.0868332 0.1352472 
keeping home or retired, 0.234472 0.0167079 0.2032649 0.2688536 
disabled 
, going to school / college or 0.2189441 0.0163081 0.188606 0.2526428 
I 
.other 
AGG 
<25yrs 0.2375776 0.016784 0.2062041 0.2720884 
26-3syrs 0.3291925 0.0185318 0.2938763 0.3665498 
36-5syrs 0.318323 0.0183704 0.2833854 0.3554315 
>55yrs 0.1149068 0.0125766 0.0924235 0.1420038 
32 
_____________________________A �p_endix 
Appendix Table 3: Reporting of consumer fraud by type and mode 
- - ----------- - ·  
r 
Type % reported 
A stolen or forged cheque 11.54 
l Paid for non-existent services/goods 23.08 
Given fake products / poor services 38.46 
! A fraudulent scheme 26.92 
Others 0.00 
.Mode
Construction or repair work 7.69 
, Work done by a garage o.oo j 
A hotel, restaurant or pub 0.00 
I A shop of some sort 46.15 
An internet transaction/ e-commerce 15.38 
iOthers
�- - 30.77 
· -- . J 
33