This book is written to empower risk professionals to turn analytics and models into deployable solutions with minimal IT intervention. Corporations, especially financial institutions, must show evidence of having quantified credit, market and operational risks. They have databases but automating the process to translate data into risk parameters remains a desire.Modelling is done using software with output codes not readily processed by databases. With increasing acceptance of open-source languages, database vendors have seen the value of integrating modelling capabilities into their products. Nevertheless, deploying solutions to automate processes remains a challenge. While not comprehensive in dealing with all facets of risks, the author aims to develop risk professionals who will be able to do just that.
Contents:
- Introduction
- Risk Typology and Data Implications
- Risk Analytics Landscape
- Embedded R
- Data Audit
- Data Warehousing
- Analytical Data Sphere
- Risks in Financial Institutions
- Common Risk Models and Analytics
- Internal Rating System
- Deployment
- Through The Cycle (TTC) Updating
- Desktop Analytics
- Resources
Readership: Risk management professionals, bankers, compliance officers as well as modelers and students who are interested in risk analytics.
Key Features:
- This book expedites risk-based decisions so that enterprises would be competitive
- The book makes it possible to automate data inputs, models and results using cost-effective R codes
- It fills a gap in the market, by integrating theory and concepts with industry realities
