Overview: The identification and measurement of risk is central to an operational risk management program. Organizations are increasingly turning to data analytics to support the risk identification and management process. This exercise introduces R (a popular data analytics tool) and positions it for use in risk identification and measurement. Prompt: You have been asked to evaluate unrecovered losses from Company XYZ’s legacy fraud identification process. To do so, you are required to identify an appropriate internal loss data set from Company XYZ’s special investigations unit. You will need to load this data set into an R environment and make a preliminary evaluation of the data for use in a formal analytic assessment of unaddressed risk of losses to fraud. Read the Auto Accident Personal Injury Claims file into R. Prepare a brief that describes the contents of the file. In that same brief, also describe how the claims file might be used to support the seven Basel II risk categories. Describe analytic methods available in R that support the operational risk framework described by the text. Guidelines for Submission: This submission must be two to three pages in length and must use double spacing, 12-point Times New Roman font, and one-inch margins. Citatiobcqns must use APA format.
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