INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025  
Preventive Fraud Risk Management and Fraud Incidence: Evidence  
from Commercial Banks in Kenya (2020–2024)  
*David Kamau Mwai., Allan Kuria, and Lucy Wanjiku Musili  
Institute of Criminology, Forensics, and Security Studies, Dedan Kimathi University of Technology  
*Corresponding Author  
DOI: https://dx.doi.org/10.47772/IJRISS.2025.91100057  
Received: 10 November 2025; Accepted: 20 November 2025; Published: 28 November 2025  
ABSTRACT  
Fraudulent activities often undermine institutional stability, erode customer confidence, and damage reputations  
among players in the banking sector. In Kenya, commercial banks lose approximately Ksh. 13 billion annually  
to fraud despite substantial investments in internal control systems and fraud prevention technologies. This study  
examined the effect of preventive fraud risk management practices (FRMP) on fraud incidence among  
commercial banks in Kenya between 2020 and 2024. Anchored on the Fraud Management Life Cycle Theory  
(FMLCT), the study adopted a causal research design and a quantitative approach. Data were collected using  
structured questionnaires from 168 senior officers drawn from 28 randomly selected commercial banks in  
Nairobi, Kenya. Correlation and simple linear regression analysis was conducted using SPSS Version 28. Results  
revealed a weak but significant negative relationship between preventive FRMP and fraud incidence (β = -0.405,  
p = .022, R² = .046). Key preventive practices like audit committee empowerment, customer due diligence, fraud  
prevention training, and staff rotation were found to moderately reduce fraud occurrences in commercial banks.  
The study concludes that preventive FRMP are essential but insufficient in isolation; their effectiveness depends  
on integration with other measures within a strong organizational risk culture. It recommends strengthening audit  
committees, enhancing fraud awareness training, and leveraging emerging technologies such as AI and data  
analytics to reinforce preventive measures and minimize fraud risks in the banking sector.  
Keywords: preventive fraud risk management practices, banking fraud, fraud incidence, internal controls, audit  
committees, organizational risk culture, commercial banks  
INTRODUCTION  
Banking-related fraud has become one of the most widespread financial offenses globally that compromises the  
stability of institutions and public confidence (Mangala and Soni, 2023; Hussaini et al., 2019). High rates of  
technology advancements, the digitalization of financial services, and intricate processes of international  
transactions in the contemporary banking sector has widened the possibilities of fraudulent cases and made them  
more sophisticated (Nyakararimi et al., 2020). According to the Association of Certified Fraud Examiners  
(ACFE, 2022), companies receive losses of about 5% of annual earnings to fraud. The Nilson Report (2019) also  
indicated that in 2019, the amount of losses due to card fraud increased to USD 27.85 billion, which indicates  
the increased magnitude of financially motivated cyber-crime. Commercial banks in Kenya lose an estimated  
Ksh. 13 billion per year to identity theft, loan stacking and digital manipulation by the fraudsters (Anyanzwa,  
2021). Such incidences undermine customer trust, hurt institutional reputation, and put regulatory control  
mechanisms under pressure.  
Financial institutions all over the world have reacted with the tightening of their anti-fraud risk frameworks that  
lay greater stress on preventative, detective and corrective controls. Preventive Fraud Risk Management  
Practices (FRMP) are aimed at mitigating fraud risk before it takes place by employing internal controls,  
employee screening, ethical training, and customer due diligence (Halbouni et al., 2016; Omar and Bakar, 2012).  
Klynveld Peat Marwick Goerdeler (KPMG, 2020) established that 86% of banking executives across the world  
had deployed or intended to deploy augmented preventive FRMP. Also, PricewaterhouseCoopers (PwC, 2020)  
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observed that 56% of banks had augmented their investment in fraud detection technologies like AI and data  
analytics. Nonetheless, the level of fraud across the globe is increasing regardless of significant amounts of  
technological investments, an indication that there is a disparity between the implementation and adoption of the  
policies (Chepkoech & Rotich, 2017; Mwangi, 2020).  
The banking industry in Kenya, which consists of 39 commercial banks licensed (CBK, 2023), is especially  
susceptible to internal and cyber-fraud. The industry is further complicated by the ineffective governance  
systems, insufficient forensic ability, and incompatible risk culture (Ocansey, 2017; Mwangi, 2020). Despite the  
presence of preventive measures like staff rotation, audit committee empowerment, and whistle-blowing  
policies, the continued occurrence of fraud indicates that there are differences in implementation in various  
institutions. Furthermore, although some of the studies have been done to assess general fraud risk management  
frameworks in Kenya (Chepkoech & Rotich, 2017; Wangombe, 2017), the impact of preventive FRMP on actual  
fraud rates in commercial banks has been assessed in a limited number of studies. This loophole underscores a  
need to conduct empirical assessment to determine the effect of particular preventive measures on the prevalence  
and typologies of fraud within Kenya in its changing regulatory and technological environments. The present  
research is especially topical in view of the growing sophistication of fraud in Kenya financial system, the  
emergence of e-banking, and the necessity of data-based risk management. The study seeks to fill the gap that  
exists in the literature of fraud by determining the key FRMP that have a major impact in the prevention of fraud.  
Finally, the results are likely to drive policy changes at the Central Bank of Kenya and improve the institutional  
frameworks of promoting transparency, accountability, and resistance to financial crime in the banking sector.  
Specific Objective of the Study  
i.  
To examine the effect of preventive fraud risk management practices (strengthened audit committees;  
policy for reporting fraud; thorough customer due diligence; employee reference verifications; fraud  
prevention training; corporate ethical guidelines; staff rotation; whistle-blowing policy; password  
protection; and virus protection) on fraud incidence among commercial banks in Kenya.  
Research Hypothesis  
H01: Preventive fraud risk management practices (strengthened audit committees; policy for reporting fraud;  
thorough customer due diligence; employee reference verifications; fraud prevention training; corporate ethical  
guidelines; staff rotation; whistle-blowing policy; password protection; and virus protection) have no significant  
effect on fraud incidence among Kenyan commercial banks.  
LITERATURE REVIEW  
This section reviews existing studies on the variables under investigation and discusses the theoretical and  
conceptual foundations guiding the study.  
Preventive Fraud Risk Management Practices and Fraud Incidence  
Preventive FRMP encompass a range of organizational strategies and policies designed to stop fraud before it  
manifests. These include strengthening audit committees, enforcing customer due diligence, instituting fraud  
prevention training, conducting employee background checks, implementing whistle-blowing mechanisms, and  
enforcing corporate ethical codes (Hussaini, 2019; Omar & Abu Bakar, 2012; Halbouni et al., 2016). Empirical  
studies have consistently shown that effective preventive measures are associated with reduced fraud risk. For  
instance, Wangechi (2020) found a significant negative relationship between preventive controls and fraud levels  
in listed Kenyan firms, while Hussaini (2019) established that robust fraud prevention mechanisms enhance  
financial performance in Nigerian banks. Similarly, Bhasin (2016) noted that the implementation of anti-fraud  
programs, awareness campaigns, and periodic training fosters ethical decision-making and discourages  
fraudulent intent.  
Technological advancements have further expanded the scope of preventive practices. Banks increasingly  
employ automated monitoring systems, data analytics, and Artificial Intelligence to identify unusual transaction  
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ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025  
patterns and potential fraud triggers (Halbouni et al., 2016; McKinsey & Company, 2019). Cybersecurity tools  
such as virus protection, password authentication, and access control mechanisms act as technical barriers to  
internal and external fraud attempts. However, despite the adoption of these sophisticated tools, fraud persists  
largely due to human factors, poor implementation, or weak risk culture (Mwangi, 2020). A culture that tolerates  
unethical behavior or lacks accountability undermines even the most advanced control systems (Hussaini, 2019).  
Therefore, organizational culture acts as both a driver and moderator in the effectiveness of preventive controls.  
Prior research provides mixed evidence regarding the efficacy of preventive measures. Studies by Adetiloye et  
al. (2016) and Fynefaceph et al. (2013) highlight that internal controls are essential to fraud prevention, while  
Micheni (2016) and Wangombe (2017) reported that internal control systems often fail to prevent fraud in  
Kenyan public institutions. Likewise, Othman et al. (2015) and Ushad & Ramen (2017) confirmed that staff  
rotation and segregation of duties deter fraudulent acts, whereas Bierstaker et al. (2006) found such measures  
ineffective in U.S. firms. These contradictions suggest that preventive measures alone may be insufficient  
without aligning them with strong ethical norms and effective implementation within the risk culture framework  
(Levy et al., 2010).  
In the Kenyan context, preventive FRMP have become increasingly vital due to the surge in digital banking and  
electronic transactions, which heighten exposure to cyber fraud and identity theft (Anyanzwa, 2021; Chepkoech  
& Rotich, 2017). Banks have invested heavily in fraud management technologies, yet the persistence of fraud  
underscores the need for a comprehensive approach integrating both structural and behavioral interventions.  
Strengthened audit committees, employee training, customer due diligence, and periodic policy reviews remain  
core preventive elements. However, without embedding these within a culture of integrity, transparency, and  
accountability, preventive systems may only serve as formalities rather than deterrents.  
In summary, literature reveals that preventive FRMP significantly reduce fraud incidence in commercial banks.  
The integration of preventive measures within the broader fraud management lifecycle enhances organizational  
resilience against internal and external fraud threats. However, the inconsistency in findings across contexts  
highlights the need for empirical studies within developing economies like Kenya, where differences in  
regulatory capacity, technological infrastructure, and ethical climates may influence the effectiveness of  
preventive practices (Mwangi, 2020; Hussaini, 2019). This study, therefore, contributes to filling this gap by  
empirically examining the effect of preventive fraud risk management practices on fraud incidence among  
commercial banks in Kenya.  
Theoretical Framework  
The present study was based on the Fraud Management Life Cycle Theory (FMLCT) that was designed by  
Wilhelm (2004). The theory cuts directly to the point that the management of the fraud risk must remain  
continuous and cyclical so that the lessons learned out of each fraud case may shape the enforcement of more  
effective controls and policies in the next phases (Mwangi, 2020; Ocansey, 2017; Hussaini, 2019; Halbouni et  
al., 2016; ACFE, 2018). The preventive stage is what the present study is centered around, and it is the core of  
the cycle of managing fraud. The initial defense against fraud is preventive practice, which tries to remove  
conditions and opportunities that allow acts of fraud. FMLCT indicates that prevention is less expensive than  
detection and response due to the fact that it reduces financial and reputation losses (Wilhelm, 2004). In the case  
of commercial banks in Kenya, audit committee empowerment, fraud prevention training, staff rotation and  
customer due diligence are relevant preventive controls to help the company check internal and external fraud  
risks. Furthermore, effective ethical frameworks and whistle-blowing systems will create an atmosphere of  
transparency and responsibility, which will scare away the potential violators of ethical standards by deter them  
through the weakness of controls (Hussaini, 2019).  
The application of the FMLCT in this study provides a conceptual lens for examining how FRMP operate as  
proactive mechanisms in curbing fraudulent activities in the banking sector. It supports the hypothesis that  
preventive FRMP have a negative relationship with fraud incidence—meaning that stronger preventive measures  
correspond to lower levels of fraud within banks. By emphasizing prevention as an integral component of the  
life cycle, the theory underscores the importance of anticipating fraud risks rather than merely reacting to them.  
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Conceptual Framework  
As illustrated in Figure I, the dependent variable in this study is fraud incidence conceptualized as the occurrence  
of various fraudulent activities within commercial banks. The independent variable is preventive FRMP as  
outlined in Figure I (Omar & Abu Bakar, 2012; Hussaini, 2019). Preventive FRMP were hypothesized to have  
a negative relationship with fraud incidence. The conceptualization aligns with the FMLCT’s preventive phase,  
where robust controls and vigilant oversight reduce opportunities for fraudulent behavior. Accordingly, the  
conceptual model posits that preventive FRMP (X₁) exert a direct influence on fraud incidence (Y).  
METHODOLOGY  
Design  
A causal research design was adopted to establish cause-and-effect relationships between preventive FRMP and  
fraud incidence. According to Apuke (2017), causal research determines the influence of one variable on another  
through statistical testing. This design was appropriate since the study sought to assess how preventive measures  
such as audit committee empowerment, customer due diligence, staff rotation, and fraud prevention training  
influence the level of fraud within commercial banks. Structured Likert-scale questionnaires were used to collect  
quantitative data from respondents, which were analyzed through inferential statistics.  
Figure I Conceptual framework for the study.  
Participants  
The target population consisted of senior officers in the risk management and internal audit departments, external  
auditors, and branch managers of all 39 licensed commercial banks in Kenya. These professionals were selected  
because they play a central role in implementing, monitoring, and evaluating fraud risk management systems.  
To ensure expertise, only officers with a minimum of three years’ experience were considered.  
Sampling Procedure  
The study employed stratified random sampling to ensure proportional representation across the three banking  
tiers (Tier I, Tier II, and Tier III). Using Taro Yamane’s (1967) formula with a 10% margin of error, a sample  
of 28 banks was determined. From each sampled bank, six respondents comprising two senior officers from risk  
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management, two from internal audit, one branch manager, and one external auditor were selected. This yielded  
a total sample of 168 participants as shown in Table I.  
Table I Sample Size Distribution  
Category of Commercial Bank Target Population (No. of Banks) Sample Size %  
Tier I  
9
6
21.43  
21.43  
57.14  
100  
Tier II  
Tier III  
Total  
9
6
21  
39  
16  
28  
Data Collection  
Data were collected using self-administered structured questionnaires comprising closed-ended questions  
measured on a five-point Likert scale (1 = Strongly Disagree to 5 = Strongly Agree). Content validity was  
established through expert review by senior bank managers and academic supervisors, followed by a pilot test  
involving 18 respondents drawn from three banks outside the main sampling frame. Feedback obtained during  
piloting led to refinement of ambiguous or redundant items. Construct validity was further assessed through  
factor analysis.  
Analysis  
Data analysis was performed using SPSS Version 28. Descriptive statistics summarized demographic  
characteristics, while Pearson’s correlation and simple linear regression tested the hypothesis. The regression  
model was expressed as:  
Y=β0+β1X1+ε  
where Y denotes fraud incidence, β0 is the constant, β1 the regression coefficient for preventive FRMP, and ε  
the error term. Tolerance (0.583) and VIF (1.716) confirmed the absence of multicollinearity ensuring model  
validity.  
RESULT  
Out of the 168 questionnaires administered, 114 were completed and returned, yielding a response rate of  
67.86%. After screening for completeness and consistency, all 114 questionnaires were retained for analysis.  
Respondents included senior officers from risk management (33.3%), internal audit/control departments  
(34.2%), branch managers (16.7%), and external auditors (15.8%) across 19 commercial banks.  
Demographically, 83 (72.8%) were male and 31 (27.2%) female, with most (75.4%) holding at least a bachelor’s  
degree. A majority (79%) had between 1–9 years of managerial experience, and over 90% held professional  
certifications such as CPA, CFE, CIA, or ACAMS, reflecting a highly qualified sample. The Kaiser–Meyer–  
Olkin (KMO) value for preventive practices was .791, and Bartlett’s test of sphericity was statistically significant  
(χ²(45) = 714.012, p < .001), confirming sampling adequacy and suitability for factor extraction. Reliability of  
the questionnaire was confirmed using Cronbach’s alpha coefficients. Preventive fraud risk management  
practices recorded an alpha of .87, while fraud incidence recorded .94. The overall reliability for the full scale  
was .90, indicating excellent internal consistency. These results confirm that the instrument used in the main  
survey was both valid and reliable for measuring the intended constructs.  
Correlation between Preventive Fraud Risk Management Practices and Fraud Incidence  
As shown in Table II, the Pearson correlation coefficient (r= - .215, p = .022) revealed a weak but statistically  
significant negative relationship between preventive FRMP and fraud incidence. This implies that as preventive  
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practices are strengthened, incidences of fraud decrease modestly. This pattern is consistent with the conceptual  
framework, which posits that preventive mechanisms—aligned with the prevention phase of the Fraud  
Management Life Cycle Theory—should reduce opportunities for fraud before it occurs.  
Table II Correlation between Preventive Fraud Risk Management Practices and Fraud Incidence  
Preventive Practices  
Fraud Incidence  
Pearson Correlation  
Sig. (2-tailed)  
N
1
Preventive Practices  
Fraud Incidence  
-.215*  
.022  
114  
1
114  
Pearson Correlation  
Sig. (2-tailed)  
N
-.215*  
.022  
114  
114  
*. Correlation is significant at the 0.05 level (2-tailed).  
The study used Pearson correlation analysis to explore how different preventive fraud risk management measures  
relate to fraud occurrence levels. Results in Table III show that most preventive measures negatively correlate  
with fraud incidence, meaning they help reduce fraud. Empowered audit committees had the strongest effect (r  
= -.343, p < .001), emphasizing their crucial role in preventing fraud. Customer due diligence (r = -.307, p =  
.001), fraud prevention training (r = -.293, p = .002), staff rotation (r = -.251, p = .007), and employee reference  
checks (r = -.216, p = .021) also significantly lowered fraud risks. However, corporate ethical guidelines showed  
only a weak, non-significant link (r = -.179, p = .056), while whistle-blowing mechanisms, password protections,  
and virus protections had minimal or even positive correlations with fraud. These findings further reinforce the  
conceptual framework’s premise that preventive strategies exert differentiated impacts on fraud incidence  
depending on their alignment with core organizational controls and behavioral norms. Specifically, measures  
such as empowered audit committees and customer due diligence reflect structural elements explicitly captured  
in the study’s model, while weaker-performing measures suggest gaps between formal controls and practical  
risk culture dynamics. Overall, the findings highlight that empowering audit committees and enforcing due  
diligence, training, and staff policies are the most effective in reducing fraud.  
Table III Correlation between Preventive Fraud Risk Management Practices Metrics and Fraud Incidence  
Preventive FRMP Metrics  
Fraud Incidence  
-.343**  
.000  
The bank's audit committees are adequately empowered to Pearson Correlation  
oversee fraud risk management activities.  
Sig. (2-tailed)  
N
114  
The bank has a clear and accessible policy for reporting Pearson Correlation  
-.044  
fraudulent activities.  
Sig. (2-tailed)  
.643  
N
114  
The bank conducts thorough due diligence on customers to Pearson Correlation  
-.307**  
.001  
mitigate the risk of fraudulent activities.  
Sig. (2-tailed)  
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N
114  
The bank verifies employee references rigorously to minimize the Pearson Correlation  
-.216*  
.021  
114  
potential for fraudulent behavior.  
Sig. (2-tailed)  
N
The bank provides comprehensive training to employees on fraud Pearson Correlation  
-.293**  
.002  
114  
prevention measures.  
Sig. (2-tailed)  
N
The bank has well-defined corporate ethical guidelines that guide Pearson Correlation  
-.179  
.056  
114  
employee behavior to prevent fraud.  
Sig. (2-tailed)  
N
The bank implements staff rotation policies to mitigate the risk of Pearson Correlation  
-.251**  
.007  
114  
fraud through collusion or insider threats.  
Sig. (2-tailed)  
N
The bank has established mechanisms for employees to report Pearson Correlation  
.072  
.448  
114  
suspected fraudulent activities without fear of retaliation.  
Sig. (2-tailed)  
N
The bank employs robust password protection measures to Pearson Correlation  
.170  
.070  
114  
safeguard sensitive information and prevent unauthorized access.  
Sig. (2-tailed)  
N
The bank employs effective virus protection measures to prevent Pearson Correlation  
.091  
.338  
114  
malware and cyber threats that could lead to fraudulent activities.  
Sig. (2-tailed)  
N
**. Correlation is significant at the 0.01 level (2-tailed).  
*. Correlation is significant at the 0.05 level (2-tailed).  
Regression Analysis and Hypothesis Testing for Preventive Fraud Risk Management Practices  
Hypothesis testing was done using simple linear regression analysis. A hypothesis was developed and tested to  
examine the effect of preventive FRMP on fraud incidence among commercial banks in Kenya. The null  
hypothesis was that:  
H01: Preventive fraud risk management practices (strengthened audit committees; policy for reporting fraud;  
thorough customer due diligence; employee reference verifications; fraud prevention training; corporate ethical  
guidelines; staff rotation; whistle-blowing policy; password protection; and virus protection) have no significant  
effect on fraud incidence among Kenyan commercial banks.  
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In Table IV, the analysis shows that preventive FRMP have a meaningful yet negative effect on fraud cases in  
Kenyan commercial banks. These measures explain about 4.6% of the changes in fraud occurrence (R² = 0.046).  
The results are statistically significant (F = 5.431, p = 0.022), with findings indicating that every increase in  
preventive FRMP reduces fraud incidents by roughly 0.405 units. The regression model (Y = 3.968 - 0.405X₁)  
confirms that stronger preventive measures lead to fewer fraud cases. Given the p-value is below 0.05, the null  
hypothesis is rejected. Moreover, this regression outcome directly supports the conceptual framework’s assertion  
that preventive mechanisms serve as foundational levers through which fraud risk is mitigated. By demonstrating  
a statistically significant negative effect, the model provides empirical validation for the prevention component  
of the FMLCT as operationalized in this study.  
DISCUSSION  
This study set out to understand whether preventive FRMP can help curb fraud in commercial banks across  
Kenya. Preventive FRMP refers to proactive strategies that banks put in place to stop fraud before it happens.  
These measures include empowering audit committees, training employees to detect fraud, screening new hires,  
performing thorough customer checks, strengthening cybersecurity defenses, and encouraging whistle-blowing.  
Previous research has long suggested that such measures reduce opportunities for fraud (Hussaini, 2019; Omar  
& Abu Bakar, 2012), but this study sought to test their real-world impact in Kenyan banks. To achieve this,  
researchers gathered data from senior risk management officers, internal and external auditors, and branch  
managers working in 19 commercial banks headquartered in Nairobi. Using correlation and regression analysis,  
they examined the relationship between preventive measures and actual cases of fraud reported by these banks.  
The results show that preventive FRMP have a statistically significant but relatively weak effect on reducing  
fraud (r = -0.215, p = .022). In other words, when banks strengthen their preventive controls, fraud cases tend to  
decline—but only slightly. Some practices were found to be more effective than others. Empowering audit  
committees had the strongest link to reducing fraud (r = -0.343, p < .001), followed closely by customer due  
diligence (r = -0.307, p = .001), fraud prevention training (r = -0.293, p = .002), and rotating staff between roles  
(r = -0.251, p = .007). On the other hand, some measures that are often considered essential—such as whistle-  
blowing mechanisms, password protections, and antivirus systems—showed little or no significant effect on  
fraud occurrence. This pattern suggests that while technical safeguards and reporting channels exist, they may  
be insufficient without strong governance oversight, behavioral reinforcement, and cultural alignment within  
banks (Halbouni et al., 2016; Bhasin, 2016).  
Table IV Linear Regression Results for Preventive Fraud Risk Management Practices  
Model Summary  
Model R  
R
Adjusted R Square  
.038  
Std. Error of the Estimate  
.76360  
Square  
1
.215a  
.046  
ANOVAa  
Model  
Sum of Squares  
df  
Mean Square  
F
Sig.  
1
Regression 3.167  
1
3.167  
.583  
5.431  
.022b  
Residual  
Total  
65.305  
68.472  
112  
113  
Coefficientsa  
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Model  
Unstandardized  
Coefficients  
Standardized  
Coefficients  
t
Sig.  
B
Std. Error  
Beta  
1
(Constant)  
3.968  
.780  
.174  
5.087  
.000  
Preventive Practices -.405  
-.215  
-2.330 .022  
a. Dependent Variable: Fraud Incidence  
b. Predictors: (Constant), Preventive Practices  
The findings broadly align with previous research showing that preventive mechanisms reduce opportunities for  
fraud (Hussaini, 2019; Kamaliah et al., 2018). However, they also reveal that prevention alone does not strongly  
predict fraud outcomes. One reason preventive FRMP explain only a small proportion of fraud variance (R² =  
.046) is that fraud in banking systems is multidimensional and often arises from collusion, circumventing  
controls that are purely procedural or technical (Olatunji & Dada, 2014; Vousinas, 2016). Moreover, preventive  
measures may be uniformly implemented across Kenyan banks due to regulatory requirements, which reduces  
variability and limits their ability to statistically explain differences in reported fraud levels (Mwangi, 2020).  
Further, evolving cyber-enabled fraud tactics often outpace routine preventive mechanisms, rendering them less  
effective unless paired with adaptive detection and responsive strategies (Micheni, 2016; Pandey et al., 2021).  
Some measures that showed strong effects in this study—such as audit committee empowerment and customer  
due diligence—emphasize structural governance and risk-based verification rather than reliance on technological  
solutions alone. The relatively weaker impact of whistle-blowing and system-level controls suggests  
organizational culture plays a significant mediating role. This interpretation is consistent with the FMLCT, which  
implies that preventive controls only function optimally when embedded within a culture that reinforces ethical  
behavior, accountability, and transparency (Wilhelm, 2004; Mwangi, 2020). Thus, preventive FRMP cannot  
independently suppress fraud; they require cultural conditions that normalize vigilance and reduce tolerance for  
unethical practices. These findings also help explain inconsistencies in the literature. While this study identified  
staff rotation as helpful, other studies in the Kenyan public sector and U.S. corporations found minimal benefits.  
This divergence likely reflects variations in institutional cultures, oversight strength, and enforcement rigor  
across sectors, as the conceptual framework anticipates. Where risk culture is weak or compliance is symbolic,  
preventive controls—even when formally adopted—may be bypassed, producing the limited predictive power  
observed in this study (Hussaini, 2019).  
Overall, the results indicate that preventive FRMP do help reduce fraud in Kenyan commercial banks,  
particularly when grounded in active oversight bodies, rigorous customer vetting, and structured fraud-awareness  
training. However, the modest effect sizes demonstrate that banks cannot rely on prevention alone. The evidence  
reinforces FMLCT’s assertion that prevention must be integrated with detection and corrective mechanisms to  
produce meaningful reductions in fraud. Moreover, strengthening risk culture—through leadership commitment,  
ethical norms, and consistent enforcement—is crucial for transforming preventive controls from procedural  
checklists into effective deterrents. In an environment where fraud schemes are increasingly sophisticated, a  
holistic, culture-driven approach remains essential.  
Limitations  
This study faced several limitations that should be acknowledged when interpreting the findings. First, the study  
relied primarily on self-reported data collected through structured questionnaires from senior officers, auditors,  
and managers in commercial banks. While anonymity and confidentiality were assured, respondents may have  
underreported or exaggerated their responses to align with socially desirable norms or institutional expectations,  
especially given the sensitivity surrounding fraud. Because respondents were directly involved in fraud risk  
management processes, their professional roles may have shaped how they portrayed their institutions’ practices,  
heightening the likelihood of institutional self-protection and socially desirable responding in a sensitive domain.  
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This reinforces the possibility that some responses reflect organizational positioning rather than objective  
assessments, thereby amplifying response bias. This reliance on self-reporting may have introduced response  
bias, limiting the objectivity of the data. Future research could mitigate this limitation through triangulation—  
integrating interviews, document reviews, and secondary data on reported fraud cases—to enhance data validity.  
Additionally, adopting mixed-methods designs incorporating interviews or case studies would help contextualize  
self-reported responses and reduce the limitations associated with single-method data collection.  
Second, the study was geographically confined to commercial banks headquartered in Nairobi County. While  
Nairobi hosts the majority of bank headquarters, the findings may not fully capture the fraud dynamics in branch  
networks across other counties where variations in risk culture, regulatory oversight, and fraud typologies might  
exist. As a result, the generalizability of the results to all banks in Kenya, particularly those in rural or semi-  
urban areas, remains limited. Expanding future studies to include a wider regional scope would provide a more  
comprehensive understanding of fraud risk management effectiveness.  
Third, the study’s cross-sectional design restricted the ability to infer causality between preventive fraud risk  
management practices and fraud incidence. Fraud is dynamic and evolves over time; thus, a longitudinal research  
design could provide deeper insights into how preventive measures influence fraud trends in the long run. Lastly,  
access to empirical fraud data was limited due to confidentiality constraints, which may have constrained the  
depth of analysis. The sensitivity of fraud-related information meant that banks were often reluctant to disclose  
detailed internal data, further restricting opportunities to compare self-reported information against objective  
fraud records. Moreover, the low explanatory power of the regression model, reflected in the modest R² value,  
indicates that additional factors—such as organizational culture, regulatory compliance strength, and  
technological capability—may play a significant role in shaping fraud outcomes and should be incorporated into  
future models to achieve a more comprehensive explanatory framework. Despite these challenges, the study  
offers valuable insights into preventive fraud risk management practices in Kenyan commercial banks.  
CONCLUSIONS AND RECOMMENDATIONS  
The section has highlighted the main findings of the study, provided practical, policy and research based  
recommendations. The researcher found that preventive FRMP affect the level of incidence of fraud among  
commercial banks in Kenya significantly and statistically. In particular, the regression analysis showed that the  
following preventive measures, audit committee empowerment, comprehensive customer due diligence, fraud  
prevention training, and staff rotation are useful in decreasing the probability of fraudulent activities. The low  
correlation coefficient ( -0.405, p =.022, R 2 =.046) however, shows that preventive measures mitigate the effect  
of fraud but not independently. This implies that perpetuation of fraud exists partly because of insufficient  
implementation of controls that are in place, risk culture inconsistencies, as well as low integration of  
technology-oriented prevention mechanisms among banks. Thus, commercial banks have to incorporate  
preventive controls into an adaptive risk culture that enhances ethical practices, accountability, and continuous  
observation.  
Using these findings, the study advises the banks to make audit committees more robust in order to have good  
control over the fraud control mechanisms and policy implementation. Ethical conduct and arising fraud risks  
capacity-building in the staff should be institutionalized through regular training and awareness programs. Bank  
also needs to further the practice of customer due diligence and the rotation of staff in sensitive jobs to minimize  
collusion opportunities. Compliance monitoring by regulators like the Central Bank of Kenya should also be  
enhanced and banks must be encouraged to implement more modern technologies, including artificial  
intelligence, machine learning, and blockchain, to detect and stop fraud.  
ACKNOWLEDGMENT  
We extend sincere gratitude to the faculty and administrative staff of the Institute of Criminology, Forensics,  
and Security Studies at Dedan Kimathi University of Technology for their guidance. Appreciation is also given  
to the senior officers, auditors, and managers from participating commercial banks for their cooperation during  
data collection.  
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