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SEP3701 MAY JUNE EXAM 2024
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SEP3701 MAY JUNE EXAM 2024
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CASE STUDYComputer Data Systems (CDS) is an emerging company that manufactures and
distributes computers to various businesses in and around Gauteng. In the 2022
financial year the company experienced a spike in hijackings of their delivery trucks
transporting computers. It is estimated that CDS lost a total of R25 000 000 of their
annual revenue, which is about 60% (impact factor).
During a recent hijacking incident, the driver and his two support staff members were
injured and hospitalised. As a result, the workers union has threatened to down tools
if the situation does not get resolved. The insurance company is also refusing to further
attend to the company’s claims due to a lack of proof that there were any attempts to
increase or implement the necessary security measures, to minimise the risks
mentioned above. The company policy does not accommodate or mention any aspects
of security-related matters.
There are about eight (8) delivery trucks and each one of them transports computers
worth R500 000 per delivery/route daily. The trucks do not have tracking devices and
there are no security escorts, or any security measures put in place to protect the
workers and the computers.
On-site orientation results revealed that the security backlog and weakness of security
measures for delivery trucks are estimated at 60% and the security risk factor is
estimated at 80%.
REMEMBER: To demonstrate understanding of this module, all your answers and
their examples must refer and relate to the case study provided above.
• Do not copy word for word from the study guide but write using your own words.
• Do not merely list facts; discuss and provide verifiable sources as proof of your
research. Apply the correct format, approach, and scientific techniques to compile a list
of references.
• Start every question on a new page.
Read SECMALB/301/4/2024 and SCHALL/301/4/2024).
, QUESTION 1
Discuss primary sources of obtaining information on crime which can be used
for crime risk analysis at CDS.
1. Insurance Claim History
Significance: Insurance claim history is essential for understanding past incidents and
financial losses due to crime. This data helps in identifying patterns and trends, allowing
for better risk management.
Application at CDS:
Identifying High-Risk Assets: analyzing the insurance claim history, CDS can
determine which assets (e.g., specific delivery routes or types of shipments) are most
prone to hijacking.
Quantifying Losses: The claim history provides a monetary value for the losses
incurred, which is critical for assessing the financial impact and prioritizing security
investments.
Claims and Security Correlation: The refusal of the insurance company to process
further claims due to inadequate security measures highlights the need for improved
security protocols. Understanding past claims can guide the implementation of these
measures.
Cost-Benefit Analysis: Analyzing the cost of claims versus the cost of implementing
security measures can help in making informed decisions to reduce future claims and
lower insurance premiums.
2. Internal Crime Statistics
Significance: Internal crime statistics offer detailed insights into all reported crime
incidents within the organization, enabling the identification of trends and the
development of targeted interventions.
Application at CDS:
Tracking Incidents: Maintaining detailed records of all hijacking incidents, including
date, location, and modus operandi, can help identify patterns and high-risk areas.
Modus Operandi Analysis: Understanding the methods used by hijackers can inform
the development of specific countermeasures, such as altering delivery routes or times.
Employee and Incident Correlation: Keeping a database of incidents and involved
employees (e.g., drivers and support staff) can reveal potential negligence or identify
employees who may require additional training.
Security Gaps: Analyzing internal statistics can highlight weaknesses in current
security practices, such as the absence of tracking devices and security escorts.
3. Community Policing Data
Significance: Community policing data involves collaboration between the police and the
community to enhance safety and security. This data can provide insights into local
crime trends and help in developing community-based crime prevention strategies.
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