Desktop Analytics

Edward H K Ng

Chapter 13 in Risk Analytics:From Concept to Deployment, 2021, pp 169-197 from World Scientific Publishing Co. Pte. Ltd.

Abstract: So far, the book has advocated development of deployable risk analytics integrated with a database. One or more models can process new data and produce results without the need for manual extraction and subsequent reinsertion of outputs. Assigning a risk rating to a new credit applicant is a business process that this design is well-suited for. Not only does complete automation save time and effort, it reduces the possibilities for errors and enhance competitiveness if processing is time critical like in the retail credit business. There was a time when this was known as Decision Support System (DSS) when IT was leveraged to expedite decision-making. There is, however, a wide range of risk analytics that can be done at a more considered pace on a desktop and presented at meetings. These are used to support strategic and even tactical decisions that do not have to be made soon. In fact, such analytics benefit from the typical “what-if” analysis where parameters are tweaked to evaluate the range of outcomes possible, usually at a meeting of corporate planners. In most business environments, Microsoft Excel or spreadsheet equivalents have been widely used for this purpose. With R now embedded as a free add-in, Excel is a useful tool for risk analytics that are not time critical. This chapter will cover some of the common topics.

Keywords: Risk; Modeling; Basel II; Quantification; Data Management; Data Integration; Decision Support; Online Analytical Programming (search for similar items in EconPapers)
JEL-codes: D81 G32 (search for similar items in EconPapers)
Date: 2021
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