Type-Safe linking with recursive DLLs and shared libraries
ACM Transactions on Programming Languages and Systems (TOPLAS)
Assessing the Construct Validity of Risk Attitude
Management Science
Credit scoring system for small business loans
Decision Support Systems
Efficient prediction of exchange rates with low complexity artificial neural network models
Expert Systems with Applications: An International Journal
Portfolio value-at-risk forecasting with GA-based extreme value theory
Expert Systems with Applications: An International Journal
A hybrid fuzzy-probabilistic system for risk analysis in petroleum exploration prospects
Expert Systems with Applications: An International Journal
Narrative Networks: Patterns of Technology and Organization
Organization Science
Information Systems Research
An agent-based simulation model for analyzing the governance of the Brazilian Financial System
Expert Systems with Applications: An International Journal
Design science in information systems research
MIS Quarterly
Process grammar as a tool for business process design
MIS Quarterly
Hi-index | 12.05 |
Model risk has become an important risk that must be taken into account by financial institutions when they make the strategic-level decision of company's solvency control and risk management through simulating and analyzing company's financial situation. To effectively cope with the model risk, the strategic-level simulation system (SSS) that implements the business view and economic environment and generates various useful financial and risk management reports cannot be treated as a static information system. Rather, SSS represents a family of possibilities because the senior manager who performs the simulation has a role in how the simulation is actually carried out. The extent of these variations is likely to increase when the business environment changes, the relevant financial theories evolve, and the senior manager assesses the system flexibility of SSS. Hereby, the system flexibility of SSS means its users, normally the senior manager, can have the luxury of modifying themselves the embedded functions associated with certain risk factors through the (user-friendly) interface. Based upon the guidance of design science, this study proposes a systematical way of designing a SSS that can effectively cope with the model risk. Specifically, this study takes the Dynamic Financial Analysis system as an example to illustrate the proposed system design.