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handle: 1822/14384
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.
Artificial intelligence, Credit suggestion, Loan applications, Intelligent agents, Multi-agent systems, Credit scoring, Loans, Knowledge extraction, Financial risk assessment, Agent-based systems, Information assets, Data mining
Artificial intelligence, Credit suggestion, Loan applications, Intelligent agents, Multi-agent systems, Credit scoring, Loans, Knowledge extraction, Financial risk assessment, Agent-based systems, Information assets, Data mining
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