Effect of Asset Identification and Tracing on the Fight against Corruption in Kenya.

Effect of Asset Identification and Tracing on the Fight against Corruption in Kenya.

Ahmed Sadik¹, Solomon Muhindi, PhD²

¹Master’s Degree in Governance and Ethics, School of Social Sciences, Mount Kenya University, Kenya

²Lecturer School of Social Sciences, Institute of Security Studies, Justice, and Ethics

DOI: https://dx.doi.org/10.47772/IJRISS.2024.806194

Received: 13 May 2024; Accepted: 14 June 2024; Published: 19 July 2024

ABSTRACT

The general objective was to examine effect of asset identification and tracing, on the fight against corruption in Kenya. This research used a pragmatic research approach and hence it adopted both qualitative and quantitative approaches. The research employed a descriptive design. Population targeted was 320 staff working in Ethics and Anti-Corruption Commission (EACC), Asset Recovery Agency (ARA), and Office of Directorate of Public Prosecution (ODPP). Slovin’s Formula was utilized to establish the size to be sample. Stratified random sampling method was adopted to choose 177 staff from the population targeted. The research employed primary information, which will be gathered using semi-structured questionnaires. The questionnaires produced both quantitative and qualitative information. The outcomes from data analysis were presented in form of a narrative. The study found that asset identification and tracing had a positive and significant effect on the fight against corruption in Kenya. The study recommends that it is imperative for relevant agencies to continue investing in and strengthening their capacity for asset identification and tracing. This includes providing ongoing training and resources to staff members involved in these processes to ensure they remain competent and effective in their investigations. Given the high level of effectiveness, reliability, and competency demonstrated in detecting and tracing illicitly acquired assets, there is a need for continuous improvement and innovation in the methods employed by these agencies. Embracing technological advancements and data analytics tools can enhance the speed and accuracy of asset tracing processes, enabling authorities to stay ahead of increasingly sophisticated methods used by corrupt individuals to conceal their assets.

Key Terms: Asset Identification and Tracing, Fight against Corruption, Work Ethics

INTRODUCTION

Corruption is a complex and pervasive problem that exists across the globe. However, corruption is common in developing nations than developed nations (Usman & Supanto, 2016). United Nations Office of Drugs and Crime (2023) assert that corruption-related losses in developing nations amount to $20 to $40 billion annually through bribery, money-laundering, and other illegal activities. Corruption is a burden on economic development programs and social services, which contributes to the additional plight of the world’s poorest nations. It erodes public trust in institutions, hinders development efforts, distorts market mechanisms, perpetuates inequality, and violates human rights (Tajudin, Norziaton & Ismail, 2021). In addition, when public institutions are corrupted, they become less effective, inefficient, and prone to abuse of authority. This lessens adherence to the law and functioning of democratic systems. Also, when corruption is widespread and systemic, it erodes public confidence in the government, breeds social discontent, and can lead to political upheavals (Ziouvas, 2018).

Sustainable Development Goals (SDGs) are a group of 17 international goals established by United Nations in 2015 as part of Sustainable Development Agenda for 2030. These goals seek to address different environmental, economic and social issues to obtain more equitable and sustainable society by 2030 (Zagaris, 2020). While corruption is not explicitly mentioned as a standalone goal, it is recognized as a significant barrier to achieving several of the SDGs. Therefore, in the increasing global complexity, fighting corruption, promoting transparency and strengthening institutions are critical to improve development, economic growth and public trust (Roussell & Dunbar, 2018). In both developed and developing countries, asset recovery strategies play a crucial role in combating corruption by targeting the illicitly acquired assets of corrupt individuals and returning those assets to their rightful owners, which could be the state or victims of corruption (Sittlington & Harvey, 2018).

An asset recovery strategy is a systematic and coordinated approach to identifying, tracing, freezing, confiscating, and returning assets that have been acquired through corruption or other illicit activities (Pacini, Hopwood & Sinclair, 2016). An effective asset recovery strategy requires strong political commitment, adequate resources, skilled investigators and prosecutors, international cooperation, and a robust legal framework. By recovering and returning stolen assets, asset recovery strategies contribute to dismantling corrupt networks, deterring future corruption, and promoting rule of law, accountability and transparency (Moiseienko, 2018). Asset recovery strategy has been adopted in different regions of the world in addressing issue of corruption.

According to Norway & Brummer (2020) indicates that having a wide range of Asset Recovery (AR) procedures such as, acknowledgement of civil law actions and proceedings based on non-convictions, as well as promoting global cooperation and having a dedicated unit of AR has a favorable impact on performance of AR.

Angola has established a legal framework to support asset recovery efforts, which enabled the National Asset Recovery Service to recover $15bn (Komminoth, 2023). The framework provides the basis for identifying, tracing, freezing, confiscating, and returning assets acquired through corrupt practices. Angola has mechanisms in place to ensure due process and adherence to legal requirements in the freezing and confiscation of assets. Sierra Leone has been implementing asset recovery strategies as part of its broader actions taken to thwart corruption and reclaim stolen property (Kamga, 2019).

Kenya has made significant strides in recent years in recovering assets stolen through corruption and other illicit activities. Abdulhamid (2021) indicates that multi agencies strategic intervention was crucial, and these factors affected asset recovery and corruption. Multi agencies strategic interventions in prosecution, investigations, coordination of justice administration and provision of resources led to an improvement in asset recovery. Similarly, Omondi (2021) observed that asset recovery strategy was among the methods used to combat corruption. However, strategy has been facing various strategies including institutional overlaps, antagonism, sibling rivalry, parallel investigations and lack of prosecutorial powers. In addition, legal framework Kenya for asset recovery across borders and internationally is insufficient, making it difficult for the Ethics and Anti-Corruption Commission Kenya to receive and provide enforcement cooperation in the context of international recoveries.

The outcomes of the research may be significant to the management of organizations dealing with corruption in Kenya, policy makers along with academicians and other researchers. To Asset Recovery Agency (ARA), management of EACC, and Office of Directorate of Public Prosecution (ODPP), the research will provide information that they can use to develop better strategies to improve asset recovery strategy and reduce corruption in country.

Problem Statement

Corruption undermines economic growth and development through manipulating market systems, deterring foreign investment, and directing government resources away from crucial industries. Over the years, prosecution has been used as the main way of fighting corruption in Kenya (Kichwen, 2017). However, since corruption is primarily motivated by money and material gain, prosecution alone is not deterring the corrupt from continuing with the vice. In the recent past, asset recovery has in Kenya been considered a crucial strategy in combating corruption and recovering ill-gotten assets (Kireri, Rintari & Gichohi, 2021). Instead of pursuing often time-consuming and legally complicated corruption prosecution, the law enforcement agencies changed tack to using asset forfeiture without a conviction and plea deals, which have assisted authorities to go after stolen assets. However, even with the adoption of the asset recovery strategy, corruption cases in Kenya are still increasing (Njeru & Moronge, 2018).

This study will seek to interrogate the effectiveness of the laws regulating the asett identification and tracing of proceeds of crime and property acquired corruptly by the institutions set up under the laws in achieving its objectives, the lapses and lacunas contained in the laws and possible recommendations, and ways to effectively achieve their intended purpose. In light of this context, the research seeks to examine the effect of asset identification and tracing on the fight against corruption in Kenya.

Objective of the Study

To examine the effect of asset identification and tracing on the fight against corruption in Kenya.

Theoretical Foundation of the research

Deterrence theory

The study was anchored in deterrence theory, it was developed from the work of Jervis (1979). Deterrence theory is a prominent framework in asset recovery, positing that the successful confiscation and return of stolen assets discourage future criminal activity. The success stories act as a stark reminder of the consequences of corruption and financial crime, potentially hindering potential offenders from venturing down that path (Piquero & Loughran, 2019). The rational choice assumption rests on the belief that criminals engage in illegal activities after weighing the potential benefits (financial gain, power) against the perceived costs (punishment, social stigma). Deterrence theory postulates that effective asset recovery significantly increases the expected costs of crime, pushing individuals towards lawful behavior.

EMPIRICAL LITERATURE REVIEW

Effect of Asset Identification and Tracing on Corruption

In United States, Pacini, Hopwood and Sinclair (2016) conducted a study on tracing domestic asset involving identification, tracking down, and freezing concealed and stolen assets. The study information was obtained from interviews, covert operations, surveillance, electronic databases and others. This research also looked at possible hiding places for assets and the many asset freezing tools available in the US, like injunctions, garnishment, replevin and attachment. The document includes a list of several helpful websites and resources. The results revealed that hidden or stolen property is frequently challenging to recover. When there is a great deal of uncertainty surrounding the results, asset recovery and tracking frequently require making difficult decisions.

In United Kingdom, Harvey (2020) examined tracing the global revenues of corruption the difficulties presented by national borders and national agencies. The study adopted a systematic review of literature. Global efforts to combat corruption and deal with the proceeds of wrongdoing have drawn increased attention from around the world in recent years. It takes time to track down and retrieve the money obtained through corruption may have traveled via several different countries. The International Corruption Unit’s future is doubtful as a result of lack of “hard results.”

In Nigeria, Esoimeme (2020) conducted a study on institutionalizing war against corruption with approaches to recovery and tracing of assets. This study relied on information from primary and secondary sources derived from public sector. Additionally, it utilized documentary research. The analysis was conducted as a desk research, which examined a number of documents, including Financial and Economic Crimes Commission (Establishment) Act and Federal Republic of Nigeria’s 1999 Constitution. According to the research, asset recovery program in Nigeria will probably be more successful if Nigerian national government introduces a law to national parliament that would offer a precise framework for utilization of investigative authority by security, security agencies and law enforcement, as well as other public authorities.

In Thailand, Rudravanija (2022) examined financial inquiry and recovery of asset as a way to fight corruption. The study made use of secondary data and systematic review of literature. The findings indicated that the quick expansion of investment and trade opportunities, together with the unrestricted flow of wealth and individual across boundaries, also significantly contributes to the atmosphere in which corruption thrives unchecked and unpunished. To combat this threat, agencies that deal with law enforcement must be able to undertake monetary investigations to find corrupt assets, work with international partners, and have efficient systems in place for transferring assets seized with the required nations.

In Kenya, Musili and Olando (2022) conducted a study on tracing the effectiveness of Kenya’s continuum of anticorruption strategies. The study used a systematic review of literature. The findings indicated that knowing assets can be traced and confiscated discourages potential corrupt officials from engaging in illicit activities. When stolen assets are returned, it undermines the belief that corruption can be a “low-risk, high-reward” crime. In addition, successful recovery showcases commitment to tackling corruption, reinforcing public trust in institutions and the rule of law. Tracing allows authorities to identify and freeze stolen assets, preventing their dissipation or hiding. In addition, effective tracing leads to more successful asset recovery cases, returning stolen funds to the Kenyan government and potentially victims. Recovered assets are be used for public good, like infrastructure development, social programs, or healthcare, directly benefiting citizens.

Conceptual Frame Work

Figure 1 below shows the visual depiction of the theorized relation of variables

Fig 1. A Conceptual Model showing Asset Identification and Tracing and Corruption

A conceptual framework provides a link between the predictor and outcome variables in a study presented in a figure format. Figure 1 shows the conceptual framework for this study. The summary of variables are; independent variable is represented by Asset Identification and Tracing which include, Identification of Illicitly acquired assets, tracing the flow of funds, Examining financial while the dependent variable is Corruption

METHODOLOGY

Research Design

The research adopted a descriptive design. Descriptive design is the methodical gathering of information in a consistent format from a known group or representative (Devi, 2019). Descriptive designs are employed in exploratory and preliminary investigations to enable researchers to obtain information, synthesize, convey, and interpret it for clarity (Hair, Page & Brunsveld, 2020). The study used descriptive research design to assess the effectiveness of Asset Recovery strategy in the fight against corruption in Kenya.

Population of the study.

The population targeted consisted of people who are a part of group being studied by researcher. Krishna (2020) defines population as any collection of organizations, individuals, or items that share some traits. The population targeted for this research comprised respondents familiar with the asset recovery strategy. The respondents were drawn from Asset Recovery Agency (ARA), Ethics and Anti-Corruption Commission (EACC), Asset Recovery Agency (ARA), and Office of Directorate of Public Prosecution (ODPP). The target population was 320 staff working in EACC, ARA and ODPP.

Table 1: Target Population

Source: ODPP, EACC, and ARA

Sampling Technique and Sample Size

Latwal (2020) emphasis that selected sample size by the investigator should have the ability of providing complete information concerning population and one that is simple to analyze. Furthermore, Slovin’s Formula was utilized to establish the sample size. The formula was chosen since it puts size of the population into consideration. Stratified random sampling method was adopted to choose 177 staffs from population targeted

Table 2: Sample Size Distribution

Source: ODPP, EACC, and ARA

Data Collection

To examine respondents’ views of the influence of Asset Identification and Tracing on Corruption, a questionnaire based on a 5-point Likert scale was employed in primary data collection for this study.

Reliability Analysis

A Cronbach’s Alpha Coefficient of 0.70 was deemed satisfactory for this investigation. Table 3 displays the reliability results.

Table 3: Reliability Test Results

Source: Pilot Data, 2024

According to the results shown in Table 3, asset identification and Tracing had a Cronbach’s alpha coefficient of 0.856 and corruption had a Cronbach’s alpha coefficient of 0.807. This implies that asset identification and tracing as well as corruption were reliable.

Response Rate

The sample size of this study was 177 staff working in Asset Recovery Agency (ARA), Ethics and Anti-Corruption Commission (EACC), Asset Recovery Agency (ARA), and Office of Directorate of Public Prosecution (ODPP). The response rate was as presented in Table 4.1.

Table 4: Response Rate

Source: Researcher 2024

Out of 177 questionnaires that were distributed, 161 responses were obtained, which gives a 90.96% response rate. According to Latwal (2020), a response rate of 50% is sufficient for effective analysis and reporting, a response rate of 60% is good while a response rate of 70% is regarded as excellent. This implies that the response rate (90.96%) in this study was within acceptable limit for drawing conclusion and making recommendations.

Descriptive statistics

Table 5: Aspects of Asset Identification and Tracing

Source: Field Data, 2024

With a mean of 4.342 (Std. Deviation=0.734), the respondents agreed that the identification process effectively detects illicitly acquired assets. Additionally, with a mean of 4.248 (Std. Deviation=0.887), the respondents indicated agreement that the authorities responsible for identifying illicitly acquired assets are competent and thorough in their investigations. The respondents also agreed with a mean of 4.143 (Std. Deviation=0.660) that the methods used to identify illicitly acquired assets are reliable and accurate. Also, the respondents agreed with a mean of 3.944 (Std. Deviation=0.673) regarding their confidence in the effectiveness of the measures taken to identify and trace illicitly acquired assets.

In addition, with a mean of 4.149 (Std. Deviation=0.653), the respondents agreed that the authorities responsible for tracing the flow of funds are competent and thorough in their investigations. Furthermore, with a mean of 4.043 (Std. Deviation=0.744), the respondents agreed that the process of tracing the flow of funds is effective in uncovering hidden financial transactions. Also, with a mean of 4.043 (Std. Deviation=0.595), the respondents agreed that the process of tracing the flow of funds adequately covers a wide range of financial transactions and entities involved. Similarly, with a mean of 3.944 (Std. Deviation=0.808), the respondents agreed that the methods used to trace the flow of funds are reliable and accurate.

Additionally, with a mean of 3.702 (Std. Deviation=0.842), the respondents agreed that the authorities responsible for examining financial records are competent and thorough in their investigations. Moreover, the respondents showed slightly less agreement with a mean of 3.646 (Std. Deviation=0.793) regarding the effectiveness of the examination of financial records in uncovering evidence of illicit financial activities. Similarly, with a mean of 3.646 (Std. Deviation=0.793), the respondents showed agreement that the methods used to examine financial records are reliable and accurate.

Fight against Corruption

The respondents were asked to indicate their level of agreement with various statements on fight against corruption in Kenya. The results were as shown in Table 5.

Table 5: Aspects of Corruption

Source: Field Data, 2024

With a mean of 4.043 (Std. Deviation=0.744), the respondents agreed that public officers are capable of providing clear explanations for their accumulated wealth. Similarly, with a mean of 3.944 (Std. Deviation=0.673), the respondents agreed that public officers possess the necessary knowledge and skills to justify their wealth through legitimate means. However, the respondents showed slightly less agreement with a mean of 3.298 (Std. Deviation=1.100) regarding the transparency and openness of public officers in explaining the sources of their financial assets. Furthermore, with a mean of 3.143 (Std. Deviation=1.982), the respondents indicated some confidence in the ability of public officers to provide convincing explanations for their wealth.

Additionally, with a mean of 3.354 (Std. Deviation=1.959), the respondents indicated that the amount of assets recovered from corrupt individuals is sufficient. Moreover, with a mean of 3.739 (Std. Deviation=0.952), the respondents agreed that the efforts to recover assets from corrupt individuals have been somewhat effective. Additionally, with a mean of 3.944 (Std. Deviation=0.673), the respondents agreed that the current asset recovery mechanisms are successful in retrieving a significant portion of the ill-gotten assets.

However, the respondents showed slightly less agreement with a mean of 3.702 (Std. Deviation=0.953) regarding the accuracy of the corruption index in reflecting the level of corruption in society. Furthermore, with a mean of 4.199 (Std. Deviation=0.400), the respondents agreed that the corruption index is a useful tool for measuring and comparing corruption levels across different countries or regions, and they also agreed that it influences public perception and awareness of corruption issues.

Inferential Statistics

Table 6: Effect of Asset Identification and Tracing on the Fight against Corruption

ANOVA

Source: Field Data (2024)

The coefficient of determination (R Square) in the regression analysis measures the proportion of the variance in the dependent variable that is predictable from the independent variables. In this case, the R-Squared value of 0.709 indicates that approximately 70.9% of the variability in the effectiveness of the fight against corruption in Kenya can be explained by the linear relationship between the predictors (asset identification and tracing) and the outcome variable (fight against corruption). However, approximately 29.1% of the variability in the effectiveness of anti-corruption efforts remains unexplained by the model.

ANOVA is used to show whether the regression model as a whole is statistically significant in explaining the variability in the dependent variable. The F-calculated (149.883), was lower the F-critical (2.46) from F-distribution table. In addition, the p-value associated with the F-statistic was 0.000, which indicates that the overall model is statistically significant. Therefore, regression model can be used in explaining the effect of asset identification and tracing on the fight against corruption in Kenya.

The results show that asset identification and tracing had a positive and significant effect on the fight against corruption in Kenya (β₁=0.473, p-value=0.004). This indicates that for every unit increase in efforts related to asset identification and tracing, there is a predicted increase of 0.473 units in the effectiveness of combating corruption. This underscores the importance of robust mechanisms for identifying and tracing illicitly acquired assets in bolstering anti-corruption initiatives. The findings are in line with Pacini, Hopwood and Sinclair (2016) observation that asset identification and tracking down leads to a reduction in corruption. The findings are also in concurrence with Harvey (2020) findings that tracing the global revenues of corruption leads to a reduction in cases of corruption. Regression results show that asset identification and tracing had a positive and significant effect on the fight against corruption in Kenya.

CHALLENGES, CONCLUSION AND RECOMMENDATIONS

Challenges

The challenge in asset identification and tracing against corruption, is that Identification of Illicitly acquired assets mostly financial is not that easy the culprits move money from one account to the other, from one country to the other making it very difficult to identify and trace or detect the illicit funds

Conclusion

The study concludes that asset identification and tracing had a positive and significant effect on the fight against corruption in Kenya. The findings indicated that identification of illicitly acquired assets, tracing the flow of funds and examining financial records had an effect on the fight against corruption in Kenya. This implies that an improvement in identification of illicitly acquired assets, tracing the flow of funds and examining financial records would lead to an improvement on the fight against corruption in Kenya.

Recommendation

Given the high level of effectiveness, reliability, and competency demonstrated in detecting and tracing illicitly acquired assets, there is a need for continuous improvement and innovation in the methods employed by these agencies. Embracing technological advancements and data analytics tools can enhance the speed and accuracy of asset tracing processes, enabling authorities to stay ahead of increasingly sophisticated methods used by corrupt individuals to conceal their assets. Also, ARA, EACC, and ODPP should ensure that their teams have access to the latest forensic accounting techniques and resources necessary for comprehensive financial investigations. Regular audits and quality assurance mechanisms should also be implemented to uphold the integrity and accuracy of financial record examinations. The study also recommends Enactment and enforcement of laws that mandate the declaration of assets by public officials, enable the freezing and confiscation of illicit assets, and provide clear guidelines for asset recovery.

ACKNOWLEDGMENT

The research was conducted under Research Permit NACOSTI/P/24/33714 that was issued by the National Council of Science, Technology and Innovation (NACOSTI) Nairobi, Kenya

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