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Assessing the Preparedness of Law Enforcement Agents in Dealing with White-Collar Crimes in Kenya: A Case of Nairobi City County

Author

Listed:
  • Patrick Mwakio

    (Kenyatta University, P.O.BOX 42695, Nairobi, Kenya)

  • Dr. George Mathenge

    (Kenyatta University, P.O.BOX 42695, Nairobi, Kenya)

  • Dr. George Maroko

    (Kenyatta University, P.O.BOX 42695, Nairobi, Kenya)

Abstract

This study sought to assess the preparedness of Law Enforcement Officers in handling white-collar crimes within Nairobi City County. White collar crimes are seen as a major headache for all legitimate governments throughout the world. It also slows down economic growth by discouraging local and foreign investors. The preparedness of the law enforcement agents to combat white-collar crimes is therefore seen as a key element in reassuring members of the society and attracting foreign investment for developing countries The research objectives were to establish the adequacy of current resources available to effectively manage white-collar crimes in Nairobi City County, to explore the competencies of the law enforcement agents in investigating white-collar crimes in Nairobi City County, to examine the challenges encountered by Law enforcement agents face in thwarting white-collar crimes within Nairobi City County and finally to establish the strategies for enhancing the capacity of law enforcement agents in handling white-collar crimes in Nairobi City County. The target population was largely drawn from the Kenya police, Directorate of criminal investigations and the Kenya Anti-corruption commission with a sample size of 371 respondents drawn from the DCI and KPS. This study adopted quantitative and qualitative research methods it used a descriptive survey design. Data was collected through questionnaires and interviews. The study was guided by the Rational Choice Theory. Quantitative data was analysed through the SPSStool version 23. The reports from qualitative data were presented using descriptive statistics. This included frequencies, modes, means, variances and standard deviations. Qualitative data was first coded, patterns established themes and finally reported narratively. The study revealed that there was a significant and strong relationship between the four variables and preparedness level to deal with white collar crime, however the enforcement agents in Nairobi County-Kenya were found to be generally ill prepared to fight white collar crime. The study revealed that corruption, tendering and other acts of bribery; money laundering, embezzlement/misappropriation of public funds/resources as the most prevalent crimes. Cyber-hacking and other forms of internet fraud were also perceived to be problematic, yet security agents were inadequately prepared to deal with these kinds of crimes as they lacked resources and the relevant training to enable them to investigate, arrest, and prosecute the culprits. The study further recommended that the government should allocate more funds and resources to enable law enforcement agents procure modern gadgets that track internet activities; the officers/forensic experts need to have proper training and be recruited from the smart people in society who are perceived to be supper intelligent for them to be smart in their investigations; there is also need to strengthen the existing and establish relevant laws (legal and institutional frameworks) aimed at combating corruption related and other economic crimes.

Suggested Citation

  • Patrick Mwakio & Dr. George Mathenge & Dr. George Maroko, 2020. "Assessing the Preparedness of Law Enforcement Agents in Dealing with White-Collar Crimes in Kenya: A Case of Nairobi City County," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 4(7), pages 270-282, July.
    • Handle: RePEc:bcp:journl:v:4:y:2020:i:7:p:270-282
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    References listed on IDEAS

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    4. Burns, Ronald G. & Whitworth, Keith H. & Thompson, Carol Y., 2004. "Assessing law enforcement preparedness to address Internet fraud," Journal of Criminal Justice, Elsevier, vol. 32(5), pages 477-493.
    5. Gottschalk, Petter & Filstad, Cathrine & Glomseth, Rune & Solli-Sæther, Hans, 2011. "Information management for investigation and prevention of white-collar crime," International Journal of Information Management, Elsevier, vol. 31(3), pages 226-233.
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