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This chart illustrates the Monte Carlo simulation approach as used in Risk Integrated's specialized finance system (SFS) for analyzing credit risk. The simulation framework (macroeconomic scenario generation and data analysis) is common to all asset classes, and the cash flow model (CFM) is tailored to a specific asset class or to an individual loan.
Source publication
We present the solution that Hypo Real Estate Bank International (Hypo) implemented to perform Monte Carlo simulations of its commercial real estate credit risk. The solution uses Risk Integrated's proprietary software, the Specialized Finance System, which is supported by another Risk Integrated technology, the Enterprise Spread- sheet Platform. T...
Context in source publication
Context 1
... Carlo simulation is a well-established tech- nique for analyzing credit risk. As Figure 1 illustrates, the concept is to construct a cash flow model that captures the logic of the given loan, drive this model "into the future" with a set of randomized macro- economic variables, then perform the risk analyses on the outputs generated from all the iterations. ...
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Citations
Data analytics is a broader term that encompasses data analysis. Data analytics is a discipline that includes the management of the complete data lifecycle, which encompasses collecting, cleansing, organizing, storing, analysing and governing data (Thomas Erl, Wajid khattak and Paul Buhler, 2015) 1. The term includes the development of analysis methods, scientific techniques and automated tools. Data is used for advanced analytics in many domains in business by data scientists. This article hypothesizes that Big Data analytics can improve the efficiency and effectiveness of financial Services and Insurance in India. This study explains how Big Data analytics apply in financial Services and Insurance, also discuss the characteristics of Big Data analytics and its implications for practical implementation.
Spreadsheet optimization modeling plays an important role in the management of today's sophisticated supply chains. However, despite the advantages of spreadsheets (or in some cases because of these advantages) there are significant risks associated with spreadsheet models. Spreadsheet risk is defined as the chance of adverse operational or financial consequences due to erroneous creation, maintenance, and/or use of spreadsheet models. Such errors arise because the intrinsic complexity of optimization models is beyond the expertise of many non-technical managers. In this article we discuss procedures that we developed for managing the substantial risks associated with the use of spreadsheets for supply chain optimization. The issues we address go far beyond simple data entry mistakes, which are possible in virtually every aspect of business and can never be completely eliminated.
