Keywords: risk management, shiny, automation, risk modelling, reporting
The typical risk management in a small-sized bank is heavily dependent on manual processes and using well-known spreadsheet applications even far beyond their original scope, like being used as a data storage tool. This has several reasons: First, spreadsheet applications (ie. Microsoft Excel) are well known and distributed throughout different countries and industries. Further risk management often receives data and information from all kind of different departments and hence has to deal with diverse data systems and data structures. Nevertheless, most of those systems are able to export their information to an Excel-compatible format. Finally, the costs to invest in systems and tools that would adequately replace classical spreadsheet applications are usually too high for small-sized banks.
Nevertheless, there are some problems attached to this procedure. This talk will show those weaknesses while proposing a different solution which allows to automate as much as possible and to integrate very important features to the risk management. This new approach which uses different functionalities of
R is focused on three major topics:
- Automation of reporting processes - increasing efficiency
- Risk modelling - one step ahead of spreadsheet applications
- Present and distribute the results - Impress your stakeholders
The first part focuses on different practical examples that were done by the reporting department in Excel (e.g. Margin Call reports, exposure calculations,etc.). Those processes were done mostly manually and are therefore very error-prone. An elegant solution is using the different functionalities in
R to connect to different systems (Salesforce, Oracle,.) and the possibility to run
R scripts as a batch in the task scheduler and hence free the time of the analysts to focus on the qualitative part of the topics. Further the usage of
shiny allows to standardize processes that need user inputs and helps to improve the user experience.
The second topic shows the usage of BI methods using similar methods as in the first part (data migration/ connecting systems). This includes the development of a rating model for SME and Corporate clients and a Value-at-risk model for FX derivatives as an example. Both cases are fully executable
R codes which provide full audit trail.
Part three focuses on the very important topic of presenting ‘results’ (ie. reports, models, etc.) to different stakeholders. Here some newer developments in the
R community like
shiny and
shinydashoard show its full potential. In addition to
shiny being used for rating tools it can be used to show different type of reports without ‘frightening’ other stakeholders with the typical
R environment.
To sum up there is a wide field of applications for using
R in the risk management which improves the overall performance. The talk will be accompanied by a live demo of the tools discussed.
