Information asset analysis : credit scoring and credit suggestion

• Author(s): Silva, Fábio ; Analide, César
• Date: 2011
• Persistent ID: http://hdl.handle.net/1822/14384
• Origin: RepositóriUM - Universidade do Minho
• Subject(s): Credit scoring; Artificial intelligence; Knowledge extraction; Data mining; Intelligent agents; Multi-agent systems; Agent-based systems; Credit suggestion; Information assets; Financial risk assessment; Loan applications; Loans
• Document Type: Article
• Language: English

Description

Risk assessment is important for financial institutions, especially in loan applications. Some have already implemented their own credit-scoring mechanisms to evaluate their clients' risk and make decisions based on this indicator. In fact, the data gathered by financial institutions is a valuable source of information to create information assets, from which credit-scoring mechanisms can be developed. The purpose of this paper is to create, from information assets, a decision mechanism that is able to evaluate a client's risk. Furthermore, a suggestive algorithm is presented to better explain and give insights on how the decision mechanism values attributes.