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For all sorts of financial institutions, fraud is a big problem. Analytics can discover fraud situations more rapidly and frequently, sometimes even before the fraudulent act occurs. Financial institutions, fortunately, already collect a large amount of data that may be utilized to combat fraud. The data sets don't have to be perfect to be valuable, but for most businesses, assessing existing data and its quality, as well as determining what other interesting data might be acquired, is a smart first step. Most banks prepare for the worst to prevent fraud based on best-case and worst-case scenario. Evaluate the best-case and worst-case scenario for the financial institutions. Then determine and explain the best decision-making approach that can improve the financial institutions' approach to decision making.
Identify the sources of data used in the analysis. Discuss how closely the approach correspond to the ideal model presented in the Blanchard and Thacker (2013) text.
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List some of your personal, social, and cultural identities. Are there any that relate? If so, how?
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