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Pages:
7 pages/≈1925 words
Sources:
10 Sources
Level:
MLA
Subject:
Accounting, Finance, SPSS
Type:
Essay
Language:
English (U.S.)
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MS Word
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Total cost:
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Topic:

Cybersecurity in Financial Institutions (Essay Sample)

Instructions:

Cybersecurity in Financial institutions

source..
Content:


[Student Name]
University Name
May 13, 2021
Faculty
Director
Banking and Finance
Introduction
The financial services industry has grown at an alarming rate and it's significantly as a result of the migration to online services. However, the growth has attracted several cybersecurity issues. Therefore, with the pervasiveness of cyber threats in this industry, regulation is a necessity to aid in curbing the attacks. The banks and other financial institutions have sensitive information that can come in handy to hackers in terms of exploitation and manipulations as their endgame is acquiring the money. Therefore, knowledge of cyber threats is paramount and how to protect against them. The topmost cyberthreats used are Web Application Attacks, Bots, Ransomware, and Phishing among others (Abad 2020). According to Dupont (2019, 13), the unfathomable truth is placing air-tight security on financial institutions which is grim due to the erudite forms of cyberattacks. However, the adoption of resilience in cyber-combat such as withstand, recovering, and adapt to ripples after the fact can help battle cyber threats or attacks and emerge on the other side, somewhat unscathed and manageable.
Cybersecurity Issues
Financial institutions differ in size and structure; however, the ubiquitous fact is the effort of every institution to stay vigil on the challenges of staying on top of cybersecurity. There are so many cybersecurity issues that affect financial institutions and thus, considered to be a nationwide issue is vital to order to mitigate the consequences that might propagate from them. Consequently, the cybersecurity issues have to be addressed and the most common are insider threats (either disgruntled or ignorant employees), improper cyber-resilience investment, lack of updating legacy systems among others (Seqriet 2019). The solution to either issue doesn't cover all bases thus the need to prioritize all issues that might affect financial institutions on the cybersecurity front.
One of the issues is the legacy systems; updating them or the adoption of new systems because of the threat that lies through the dependency of such systems. Dropping such systems would be an issue for certain institutions because of the ROI the new systems will bring. New systems will require experts to keep them updated since it requires skilled people to offer a palatable solution to enhance their effectiveness. The adoption of new systems has to portray material risk reduction and/or risk avoidance. Also, the new systems will require competent personnel to maintain a higher execution speed (Friedman 2016). Subsequently, the institution will contemplate outsourcing such skill set or making it in-house depending on cost variation.
The modernization of financial systems to lobbied by risk mitigation in terms of obsolete technology and workforce, increasing revenue generation, and cost savings. Some institutions have tried to integrate new on the old to try and attenuate the cost of getting new technology altogether. The rudiment nature of the old system has to be supported by an aging workforce that is nearing retirement. Consequently, the layers added to the system will require different manpower to keep it in check (Ismail 2017). The approach shows significant traction in the world of financial institutions; however, new territories attract unforeseen threats and challenges which offer opportunities to hackers. Therefore, the need to accommodate the old methods as well as the challenge that needs addressing.
Cybersecurity Framework
The financial institutions' industry must comply with some frameworks that trickle down to cybersecurity regulations. One of the frameworks is PCI DSS (Payment Card Industry Data Security Standard) which is a security standard that ensures organizations that accept, process, store, or transmit payment card information maintains secure environments to protect consumers and merchants. This compliance is a requirement to financial services institutions that offer major card brands such as Visa, MasterCard, American Express, Discover, and JCB (Sabo 2020). Financial institutions that offer such cards to their customers to transact have to be PCI DSS compliant. There's a process to being PCI DSS compliant that includes assessing, remediate, and report. Most financial services institutions store critical information about their clients (Zhao 2021). Therefore, it's incumbent upon them to identify and take inventory of the data assets. Later analyze for vulnerabilities and fix and finally, submit reports in demonstrating compliance.
If the financial services institution in question doesn't offer the major card brands, then its compliance is not important. To be PCI DSS compliant means that they can combat credit fraud and that the institution stores credit card information for their clients. Therefore, such institutions which are hard to find are required by their clients to protect their information and not be stolen and used by hackers or unauthorized persons.
Many businesses today offer cashless payment services; therefore, a card would be the right choice. Also, a software developer has to be PCI DSS compliant if he/she processes, transmits, or stores cardholder data or his/her activities affect the security of the cardholder as the data is being processed, transmitted, or stored (Mateaki 2019). The scope of PCI DSS reaches as far as payment card information.
However, the framework can prove insufficient when information such as email addresses, usernames, social security numbers, passwords, and physical addresses are not canopied by the framework. Fortunately, it gives insight on what needs to be done to data that's beyond the scope of the framework through data inventory. This exercise is an eye-opener and extremely useful where it can shine a light on the data knowledge gaps in organizations leading to informed decisions made by the same

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