Best practice in credit risk modelling and management cobines empirical data, research expertise, and technological capability. In this article, Geoff Fite and Jing Zhang identify and expound on these requirements and illustrate a sample solution that incorporates them
The state of credit risk measurement has been evolving rapidly since the last credit cycle. Best practice in credit risk modelling and management is now, more than ever and irrespective of portfolio size and institution characteristics, dependent upon three critical capabilities: empirical data, research expertise and technological capability. Successful management of credit risk begins with the measurement of individual obligors and instruments, culminating in the analysis of complex portfolios of varied exposures.
More on Risk Management
Market shocks are earthquakes, not a game of roulette
ABSTRACT This paper discusses the importance of operational risk management for the efficiency of Taiwanese banks. We demonstrate that by applying risk managerial strategies banks can improve their performance,...
ABSTRACT In this paper, we propose a copula-free approach for modeling correlated frequency distributions using an Erlang-based multivariate mixed Poisson distribution.We investigate some of the properties...
This is a special issue for The Journal of Operational Risk as we celebrate our tenth anniversary. In this milestone event for our young journal I think that it would be appropriate at this time to provide...
Sign up for Risk.net email alerts
Sponsored video: MarketAxess
Sponsored video: Tradeweb
Multifonds talks to Custody Risk on being nominated for the Post-Trade Technology Vendor of the Year at the Custody Risk Awards 2014
Sponsored webinar: IBM Risk Analytics
There are no comments submitted yet. Do you have an interesting opinion? Then be the first to post a comment.