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DATA4000 Introduction to Business Analytics Report 3 Sample

Your Task

Consider below information regarding the Capital One data breach. Read the case study carefully and using the resources listed, together with your own research, complete:

• Part A (Industry Report) Individually by Monday 23: 55pm AEDT Week 12
Assessment Description

Capital One


Who is Capital One?

Capital One Financial Corporation is an American bank holding company specializing in credit cards, auto loans, banking, and savings accounts. The bank has 755 branches including 30 café style locations and 2,000 ATMs. It is ranked 97th on the Fortune 500, 17th on Fortune's 100 Best Companies to Work For list, and conducts business in the United States, Canada, and the United Kingdom. The company helped pioneer the mass marketing of credit cards in the 1990s. In 2016, it was the 5th largest credit card issuer by purchase volume, after American Express, JPMorgan Chase, Bank of America, and Citigroup. The company's three divisions are credit cards, consumer banking and commercial banking. In the fourth quarter of 2018, 75% of the company's revenues were from credit cards, 14% were from consumer banking, and 11% were from commercial banking.


Capital One is the fifth largest consumer bank in the U.S. and eighth largest bank overall(Capital One, 2020), with approximately 50 thousand employees and 28 billion US dollars in revenue in 2018(Capital One, 2019).Capital One works in a highly regulated industry, and the company abides to existing regulations, as stated by them: “The Director Independence Standards are intended to comply with the New York Stock Exchange (“NYSE”) corporate governance rules, the Sarbanes-Oxley Act of 2002, the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010, and the implementing rules of the Securities and Exchange Commission (SEC) thereunder (or any other legal or regulatory requirements, as applicable)”(Capital One, 2019). In addition, Capital One is a member of the Financial Services Sector Coordinating Council (FSSCC), the organization responsible for proposing improvements in the Cybersecurity framework. Capital One is an organization that values the use of technology and it is a leading U.S. bank in terms of early adoption of cloud computing technologies. According to its 2018 annual investor report (Capital One, 2019), Capital One considers that “We’re Building a Technology Company that Does Banking”. Within this mindset, the company points out that “For years, we have been building a leading technology company (...). Today, 85% of our technology workforce are engineers. Capital One has embraced advanced technology strategies and modern data environments. We have adopted agile management practices, (...).We harness highly flexible APIs and use microservices to deliver and deploy software. We've been building APIs for years, and today we have thousands that serves as the backbone for billions of customer transactions every year.” In addition, the report highlights that “The vast majority of our operating and customer-facing applications operate in the cloud(...).”Capital One was one of the first banks in the world to invest in migrating their on-premise datacenters to a cloud computing environment, which was impacted by the data leak incident in 2019.

Indeed, Amazon lists Capital One migration to their cloud computing services as a renowned case study. Since 2014, Capital One has been expanding the use of cloud computing environments for key financial services and has set a roadmap to reduce its datacenter footprint. From 8 data centers in 2014, the last 3 are expected to be decommissioned by 2020, reducing or eliminating the cost of running on-premise datacenters and servers. In addition, Capital One worked closely with AWS to develop a security model to enable operating more securely. According to George Brady, executive vice president at Capital One, Assessment Instructions

Part A: Industry Report - Individual

Based on the readings provided in this outline, combined with your own independent research, you are required to evaluate the implications of legislation such as GDPR on the Capital One’s business model. The structure of your report should be as follows.
Your report needs to be structured in line with the Kaplan Business School Report Writing Guide and address the following areas:

• Data Usability

- Benefits and costs of the database to its stakeholders.
- Descriptive, predictive and prescriptive applications of the data available and the data analytics software tools this would require.

• Data Security and privacy

- Data security, privacy and accuracy issues associated with the database.

• Ethical Considerations

- The ethical considerations behind whether the user has the option to opt in or opt out of having their data stored.
- Other ethical issues of gathering, maintaining and using the data.

• Artificial Intelligence

- How developments in AI intersects with data security, privacy and ethics.

• Use the resources provided as well as your own research to assist with data collection and data privacy discussions.



Capital One Financial Corporation is known to be a popular American bank holding company. It is capitalizing in credit card, auto loans and saving accounts. The bank does come with branch strengths of 755 inclusive of 30 café style locations along 2,000 number of ATMs. For Assignment Help, This particular financial company has been ranked as 97th on the fortune list of 500 and even 17th on fortune out of 100 best companies to work. The company has even helped to become pioneer in terms of mass marketing of credit cards in the year 1990. In the year 2016, it has positioned as 5th largest card issuer in terms of purchase volume(GDPR Compliance Australia. 2021). Capital one is a firm which tend to value the use of technology and has evolved as leading U.S bank with respect to adaptation of cloud computing(Greve, Masuch and Trang 2020 p 1280). Amazon has listed Capital One migration right into their cloud computing environment for some of vital financial services. In addition, it does come up with a roadmap for reducing its data centre footprint in near future.

In the coming pages, an evaluation has been regarding implication of legislation on GDPR on the capital One’s business model. The next section reveals data usability, data security and privacy, ethical consideration and artificial intelligence.

Data Usability

Benefits and costs of database to its stakeholders

Database is considered to be an important tool for handling various digital processes within the system. The main aspect of storing, organization and analysis of critical data of business for different aspects like staff, customer, accounts, payroll and inventory. Database management system will allow access to various kinds of data. This will again help in creating and management of huge amount of information with respect to use of single software(Novaes Neto 2021). Data consistency is also ensured within database as there is no kind of data redundancy. All the required data appears to be much more consistent in nature with database. Here data is found to be same for various users to view the database(Lending, Minnick and Schorno 2018 p 420). Any kind of changes within database are reflected on immediate basis for users and thereby ensuring that there is no kind of data consistency.

Database do automatically take care of both recovery and backup. User’s does not need any kind of backup of data on periodic basis due to the point that care is taken by database system. In addition, it also helps in restoring database right after or even failure of system. Data integrity helps in ensuring that store data is accurate and consistent within database(Spriggs, 2021). The fact should be noted that data integrity is vital parameter when data is accurate and consistent within database. It can be noted that database do comprises of data being visible to range of users(Vemprala, and Dietrich 2019). As a result, there is need for ensuring that collected data is correct and consistent in nature for database and its users.

Descriptive, predictive and prescriptive applications of the data

Capital One can make use of analytics to explore and examination of data. It will help in transform findings into the insights which can help manager, executives and operational employees to go for informed decision-making. Descriptive analytics is being commonly used as form of data analysis where various kind of historical data is collected(GDPR Compliance Australia. 2021). After this, the collected data is organized and presented in such a way that it is easily understandable. Predictive analytics is focused on predictive and proper understanding what can happen in near future. Predictive analytics is completely based on probabilities.

There are wide range of statistical methods which can be use for this purpose named as descriptive statistics. It does comprise of numerical and graphical tools which can help in summarizing collection of data and collect some of the vital information. IBM SPSS is known to be predictive analytics platform which can again help user to build right predictive model at quick rate(Giwah et al. 2019). All this will be used for delivery of predictive intelligence to groups, system, individual and different enterprises. Predictive analytics software tools do come up with some advanced analytical capabilities like text analysis, real-time analysis and statistical analysis, machine learning and optimization.

Data Security and privacy

Database Security Issues: Database can be easily hacked by making use of flaws within their feature. Hackers can easily break direct into legitimate and compel the given system by making use of arbitrary code. Although it is found to be bit complex one, the access can be collected by using some of basic flaws to accept features. Database can help in providing protection from the third party by using security testing(Poyraz et al. 2020). The database can easily protect from third party access by making use of security testing. The function of database is simple one as there is chance for ensuring proper protection from each of the database feature.

Data privacy: Increased in use of personal data puts the data privacy at the top on business risk management. It is found to be an acceptable challenge and even dangerous to completely ignore. Breaching GDPR and other kind of similar regulation like CCPA and HIPAA do come up with up some hefty fines(Rosati et al. 2019 pp 460). The damage to reputation can be biggest kind of threat to the business and even create a career limit on the blot for IT resume manager. Data privacy can be easily tracked down into IT security or disaster recovery plan. But this is not good enough due to the fact that data privacy aim to touch various section of the business.

Data Accuracy:Business on global platform is increasing their lean on their data so that they can power day-to-day operations. It will help in providing enhanced data management being top directive for some of leading companies. Secondly, entry of three section blog series will help in looking towards more leading blog series. There is need for considering some of the popular data management challenges with cloud deployment, integration of various data sources along with maintaining accuracy(Zou et al. 2019 pp. 10). It emphasizes on data without any kind of disruptive analytics along with neglecting any possible impact. Issues related to data availability and security plague for enterprise of different size all around the verticals.

Ethical Considerations

In the infancy age of internet, data protection laws were created. Right before the advent of social media, no has ever heard about the term big data. General data protection regulation (GDPR) does come into effect right in the month of May. It will provide overhaul for legal framework for providing privacy and protection to some of personal data all across EU(Truong et al. 2019 pp, 1750). GDPR is getting much of attention due to the fact that organization aim to impose personal data which will help in to comply.

An opt-in completely depends on person so that they can actively reveal exact data about them which can be used properly. In general, the lighter touch in comparison to informed consent approach. On the contrary, opt-out system is possibility to result in much high coverage within population. It will provide the option of default assumption so that people can feel about data which can be used. It is possibly that only few people can actively take part for step-out(Goddard, 2017 p 704). It is more specifically to diverse population which has changing ethnicities as best tool for providing prevention. Some of the ethical responsibility for data which this patient can individually manage for opt-in depended system.

Taking into account opt-out availability,Capital One needs to consider some of the important points:

• It will help in providing meaningful, easy availability, together with clear information so that people can have well-informed regarding choices.

• Customers are not that much disadvantages if they come up decision to opt out.

• There is need for good and robust governance regarding data use. It does comprise of some independent sight and ability for auditing(Wachter, Mittelstadt and Russell 2017 p 841). This will ensure that data can be enhanced in certain methods.

Artificial Intelligence

Security, privacy and ethics are found to be of low priority problem for developers when modelling the machine learning solution. Security is considered as one of the serious blind spots. Here the respondents reveal that they do not check for any kind of security vulnerabilities at the instance of modelling building. There are various kind of regulations which tend to cover some vital areas of data protections. It will again have certain clause in relation to artificial intelligence(Zhang et al. 2021 p.106994). AI governance aim to post GDPR lessons learned and road ahead with a number of key areas to tackle to be identified to tackled down AI and privacy. It aims to list out on the following areas namely

• Incentivising compliance centred innovation AI.
• Empowering civil society by making use of AI
• Enhancing interoperability for AI-based governance structure.

European GDPR is such that law which does have special pull-on artificial intelligence to set out requirements which do comprises of its use. The report encourages both local and international level for resolving the possible challenges related to AI governance within privacy as being privacy being contextual in nature.

. This is found to be useful for manufacturing as it accepts latest technologies (Weinberg 2020). Due to the nature of this nature of technology, an individual needs more data so that they can enhance efficiency and smartness. In order to so, it creates certain number of privacy and ethical issues which needs to be dealt with policy along with careful design solution. Centre of Data Ethics and innovation will help in reducing any kind of barriers related to acceptance of artificial intelligence within society. Three areas namely business, citizen and public sector which require some clear set of rules and structure for providing safety and ethical innovation within data and artificial intelligence (AI)(Tomás and Teixeira 2020 pp. 220). Artificial intelligence depended solution will evolve to become much more ubiquitous in nature in upcoming days. As a result, there is need for acting ways to check that these solutions tend to evolve in ethical and privacy protecting ways.


From the above pages, it can be noted that this report is all about Capital One. Even Amazon has listed capital one migration in their cloud computing as the reputed case study. Capital One has evolved as one of prior banks on global platform so that they can invest to migrate its data centre on cloud computing-based environment. The report aims to evaluate possible implication of legislation like GDPR on Capital One business model. There are mainly four sections covered on report like data usability, data security and privacy, ethical consideration and artificial intelligence. The report covers data security, privacy and accuracy problem in relation to database. In the last section, an overview has been given how artificial intelligence aim to intersect with data security, ethics and privacy.


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