Springer is pleased to announce a new book series titled “Computational Risk Management”.

Click Here for Springer web

The ERM series will exploit the quick, reliable publishing infrastructure to achieve timely worldwide dissemination of the latest research results both in printed and electronic form. The ERM series will be benefiting from key indexing services such as EI (compendex) indexing, ISI Proceedings, DBLP, and Scopus.

Risks exist in every aspect of our lives. Risks by definition are surprises, causing a great deal of potential damage and inconvenience. Recent examples of disaster risks include terrorism leading to the gassing of the Japanese subway system, to 9/11/2001, and to bombings of Spanish and British transportation systems; The SARS virus disrupting public and business activities, particularly in Asia. More recently, the H1N1 virus has sharpened the awareness of the response system world-wide; the financial crisis results in recession in all aspects of economies (Olson and Wu 2009).

Risk management has always been a vital topic. The history of risk management has evolved since time immemorial.  Levantine and Chinese traders prior to A.D. undoubtedly coped with the risk of sailing trade, as the Egyptians and Babylonians did before them.  The coffee houses of Lloyds of London developed as a meeting place for the seeds of the insurance industry. Incorporating systematic thinking into risk management produces the-state-of-the-art business philosophies such as enterprise risk management.

Most computational techniques and tools have been used for optimizing risk management and the risk management tools benefit from computational approaches. For example, computational intelligence models such as neural networks and support vector machine have been widely used for early warning of company bankruptcy and credit risk rating. Operational research approaches such as VaR (value at risk) optimization has been standardized in managing market and credit risk. Agent-based theories are employed in supply chain risk management. Various simulation techniques are employed by researchers working on problems of environmental risk management and disaster risk management. Investigation of computational tools in risk management is beneficial to both practitioners and academic researchers.

The ERM series is a high-quality research book series with an emphasis on computational aspects of risk management and analysis.

The book series publish material including research monographs, conference and workshop proceedings, Postproceedings and other edited monographs such as project reports or invited volumes related to computational risk management and addressing in depth the following topics (the list is not exhaustive):

·      Enterprise risk management such as

o    Supply chain risks

o    Channel selection under risks

·      Financial risk management such as

o    Portfolio management and optimization

o    Market risk management and credit risk management

·      Environmental risk management such as

o    Environmental sustainability and risk reports

o    CO2, waste water and dust emission reports and analysis

·      Emergency management such as

o    Natural and technological disasters, emergency management structure

o    Risk management aspect of storms and flooding; nuclear power accidents; ferry, air and rail accidents; computer viruses; earthquakes

·      IT (information technology) risk such as

o    Outsourcing risks of IT systems

o    Operational risks in IT

·      Uncertain performance evaluation such as

o    Efficiency of financial institutions

o    Business performance in e-world

·         Artificial intelligence and risk analysis

·         Computer simulation in risk management

·         Game agents in risk management

Manuscript Preparation and Submission