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Data Privacy and Ethics: A Case Study on Santander Bank Polska S.A.

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Data Privacy and Ethics: A Case Study on Santander Bank Polska S.A.

Santander Bank Polska S.A. notified the Polish SA of a personal data breach when it discovered that a former employee had unauthorized access to the bank’s profile on the Electronic Services Platform of the Social Insurance Institution (PUE ZUS platform). This breach exposed the personal data of bank employees. The breach occurred when a former employee accessed the platform multiple times after termination of their employment contract. The breach posed a high risk to the rights or freedoms of the data subjects, including exposure of sensitive health data. The bank’s communication regarding the breach was deemed inadequate by the Polish SA. The Polish SA imposed a 120,000 EUR administrative fine on Santander Bank Polska S.A. and ordered the bank to communicate the breach to all affected data subjects, i.e., all employees employed during the unauthorized access period.

Report structure

Introduction 

  • State the aim and scope of the project
  • Analyze the complexities surrounding data privacy and ethics in the financial sector using the case study on Santander Bank Polska S.A.

Data Usability

  • Evaluate the benefits and costs of the database to stakeholders. 

(You must find ways in which customer data can be used to further assist Santander Bank Polska S. A. with its marketing campaigns and how Santander Bank Polska S. A. could potentially assist other vendors interested in the credit card history of its customers)

  • Explore descriptive, predictive, and prescriptive applications of data and required analytics tools

Data Security and Privacy Data security, privacy, and accuracy issues associated with the proposed database usage Ethical Considerations

  • Providing customers with the option to opt-in or opt-out of data usage
  • Addressing other ethical issues related to data gathering, maintenance, and usage

Artificial Intelligence Intersections of AI with data security, privacy, and ethics in the proposed analytics project Conclusion and Recommendation Summarize the key findings and implications of the case study on Santander Bank Polska S.A. and provide at least two recommendations from your findings References Minimum 10 references from company’s website, its annual reports, its news release, scholarly articles, books, research papers, consultancy agency reports, government publications etc in Harvard style

Key learning from this project

  • Evaluating data usability and stakeholder impacts
  • Understanding data analytics applications and tools
  • Addressing data security, privacy, and accuracy concerns
  • Exploring ethical considerations in data handling
  • Examining AI intersections with data security, privacy, and ethics
  • Presenting data usage benefits, ethical sourcing, security measures, and ethical usage

Answer to the question – How will you applying your learning in your future organization

Through this case study, I gained a comprehensive understanding of the critical issues surrounding data privacy, security, and ethics in the financial sector. I learned to evaluate the usability and potential benefits of customer data while considering the costs and implications for various stakeholders. Additionally, I developed expertise in assessing data security risks, privacy concerns, and accuracy challenges associated with data handling practices. I also explored ethical considerations, such as providing opt-in/opt-out options for customers and addressing ethical dilemmas in data gathering, maintenance, and usage. Furthermore, I gained insights into the intersections of artificial intelligence with data security, privacy, and ethics, which will be invaluable in navigating the evolving landscape of data-driven technologies. With these learnings, I can contribute to your organization’s data governance and privacy initiatives, ensuring compliance with regulations while upholding ethical standards and safeguarding customer trust. I can also assist in developing robust data security measures and implementing responsible AI practices

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