Financial Risk Management
Financial Risk Management
FRM代写 Financial institutions are investing heavily in technologies that can be able to detect financial crimes and keep watch of the banking transactions.
The Use of Entity Analytics in Financial Crimes Risk Management a Case of Bank of America FRM代写
The last few decades, the world has witnessed dramatic changes in financial crimes that have exponentially increased. Financial crimes have not only increased in numbers but also in complexity and sophistication (Stulz,.2015; Atkins, & Huang, 2013). As a result, financial institutions have suffered losses coupled with the high cost of their inability to detect such crimes (Zeidan, 2013).
According to a report by IBM, over 89 per cent of the CEOs take financial analytics as their top priority so in the banking sector (Pramanick, 2013). Financial institutions are investing heavily in technologies that can be able to detect financial crimes and keep watch of the banking transactions. Such technologies are used to prevent, detect, investigate and report frauds in financial or assets transactions.
Entity analysis FRM代写
Entity analytics have increased use in banks to enhance services delivery and safeguard the bank assets in the process of financial risk management and compliance. Although many banks are for predictive and detective analytics to avert such crimes as money laundering and frauds, entity analytics is emerging as the most effective and current solution to modern financial crimes. In this regard, it is important to evaluate the use of entity analytics and their effectiveness of prevention, detection, investigation and reporting of financial crimes and frauds.
A case study of Bank of America (n.d) will be used to assess the use of financial risk management and how the banks have effectively integrated it in financial risk management. Bank of America is one of the largest banks in the U.S.A hence using it as a case study will give a bigger picture on the use of the entity analytics in financial institutions.
In so doing, the research will use qualitative and quantitative techniques in data collection, analysis, and presentation.
The target group will be the bank employees especially the senior managers concerned with risk assessment and management. In data collection, the use of semi-structured interviews and questionnaire are appropriate. The data will then be qualitatively and quantitatively analyzed and presented to get a detailed understanding of the use of the entity analytic.
Atkins, B., & Huang, W. (2013). A study of social engineering in online frauds. Open Journal of Social Sciences, 1(03), 23.
Bank of America. (n.d). Bank of America – Banking, Credit Cards, Home Loans and Auto Loans. Retrieved from https://www.bankofamerica.com/
Pramanick, S. (2013). Analytics in banking services. Retrieved from https://www.ibmbigdatahub.com/blog/analytics-banking-services
Stulz, R. M. (2015). Risk‐taking and risk management by banks. Journal of Applied Corporate Finance, 27(1), 8-18.
Zeidan, M. J. (2013). Effects of illegal behaviour on the financial performance of US banking institutions. Journal of business ethics, 112(2), 313-324.