The purpose of this assignment is to utilize secondary data to determine the problem facing a company, and create research objectives that align to the identified problem.
For this assignment, choose a marketing research scenario from the “Marketing Research Scenarios” document. Describe the current business problems and determine research objectives. Conduct secondary data research to understand the business problem and consumer attitudes that might affect the industry, company, or brand.
There is additional information on writing research objectives on page 58-71 in the textbook. Students can also utilize the Research Objective Mapping Tool for assistance related to writing clear objectives.
In a 250-400 paper, address the following:
Describe the general nature of the business problem(s).
Describe the major areas of opportunity. What could the organization accomplish if it knew how to address the business problem(s)? What major research questions need to be answered in order to sufficiently address those problems/opportunities?
Write the research objectives intended to address each one of the previously addressed problems. These will be the primary objectives that guide the design of research, the analysis of data gathered, and the writing of the market research report for the client. Students may revise their objectives as they work further on the research project.
Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

ANSWER

Data Confidentiality and Privacy

The general nature of the business problem

As a result of the paradigm shift in technology, many companies have been experiencing challenges associated with data confidentiality and privacy.  Financial institutions, especially banks, are some of the most affected institutions where they have to deal with financial data and other personal information regarding their clients. As a result of the enormous databases by financial institutions and the risk of attacks from external factors, data confidentiality, and privacy have been major challenges faced by financial institutions, negatively affecting the clientele base.

A primary reason why data confidentiality and privacy have posed a significant threat to financial institutions is due to its fast-growing nature. The financial institution’s responsibility is to protect non only its consumers’ personal information and ensure that sensitive information does not get to a third party without permission (Faccia, 2019). Despite the exponential growth of data in the last decade, security threats have been rising, with security practices below average. This hence puts the institutions at significant risk of a data breach (Earls, 2021).   One primary concern on data privacy in such an institution is Personal Identifiable Information (PII). This is due to the veracity and the volume of data in the technologically driven world. It is overwhelming to handle millions and possibly even billions of data records.

The major areas of opportunity

There are major opportunities that the financial institution could take advantage of to deal with the current problem it faces. First, there is a need to develop strong structures to ensure that there are mechanisms for dealing with any data breach event. There is also a need for the institution to have preventative measures in place, which will prevent any third party or hacker from accessing any private information from its systems. This will require hiring the most qualified technicians and experts who can help in updating the systems and ensuring that the institution’s security system meets the required standards (Singh, Halgamuge, Ekici, & Jayasekara, 2018). The company could also embark on constant training programs for the workers and more so the IT experts. This will ensure that they are continually updated on any changes within the security system and work towards preventing security breaches or attacks. There is also the opportunity of reviewing and mitigating risks from employees, especially those who work remotely (Earls, 2021). The remote working employees are some of the primary sources of the attacks due to private networks. Hence measures of ensuring that they are secure need to be undertaken to ensure that data hacking or invasion of privacy is tackled.

Research questions

1. What are the major issues leading to increased invasion of privacy and breaching of personal data?
2. What measures can companies, more so financial institutions, undertake to protect private information from consumers and many other stakeholders at the institution?

• Which best programs can companies adopt to ensure that consumers and employees are free of attacks or invasion of their data?

1. What is the role of the institutions’ stakeholders in ensuring that the customer data is protected against any potential attack from hackers and any other harm?

The research objectives

1. To establish the significant issues leading to the increased cases of invasion of privacy and breaching of personal data
2. To identify the most suitable measures can companies, more so financial institutions, undertake to protect private information from consumers

• To categorize the most appropriate programs that companies can adopt to ensure that consumers and employees are free of attacks or invasion of their data?

References

Earls, A. R. (2021). 5 common data protection challenges that businesses face. Retrieved from https://searchdatabackup.techtarget.com/tip/5-common-data-protection-challenges-that-businesses-face

Faccia, A. (2019). Data and Information Flows: Assessing Threads and Opportunities to Ensure Privacy and Investment Returns. In Proceedings of the 2019 3rd International Conference on Cloud and Big Data Computing . 54-59.

Singh, M., Halgamuge, M. N., Ekici, G., & Jayasekara, C. S. (2018). A review on security and privacy challenges of big data. In Cognitive computing for big data systems over IoT (pp. 175-200). Springer, Cham.