Expert Systems

- Expert Systems.
- Expert Systems are computer systems which embody some of the experience and specialised knowledge of an expert and thereby mimic the expert and act as a consultant in a particular area.
- Knowledge is often represented in an Expert System in a knowledge base, which is a network of interconnected rules which represent the human expertise..
- Expert Systems fall into a field known as Artificial Intelligence.
- A major thrust of Artificial Intelligence is the development of computer functions normally associated with human intelligence, such as reasoning, learning and problem solving..
- The Expert System.
- Expert System Development Knowledge.
- The financial services industry has become a vigorous user of Expert System techniques.
- With their high level of accuracy and reliability, Expert Systems easily replace complex human decision-making.
- Expert Systems technology is normally introduced to bring consistency to the decision-making process, as well as to speed it up through semi-automation..
- Expert systems are increasingly being used in banking applications.
- Some of the areas where this technology is being applied are credit risk analysis, portfolio management and analysis, credit approval, loan application processing, money transfer processing, loan monitoring, teller training, financial planning services, and intelligent message understanding.
- These applications usually have a clear set of rules and regulations to be followed which can be implemented as an expert system.
- Insurance companies have come to use Expert Systems to assess the risk.
- Money Laundering Prevention could also take a giant’s step forward with the use of an appropriate Expert System.
- Extensive analysis has to be carried out with experts in this delicate field to develop the business rules before building the Expert System.
- The final aim of the system would be to provide a recommendation, based on the bank’s standard lending policy, on whether to loan to the client or not, and the size of the amount..
- The borrowing history of the customer in consideration could be a good place where the bank could concentrate.
- The computer is also given a description of the type of customers who defaulted on loans in the past.
- The Expert System will reserve a different treatment to a twenty-year old.
- youngster money, the Expert System must be sure that the client will be able to repay.
- Due to the young age of the prospective client, the checks carried out might be more thorough.
- Artificial Intelligence of Expert Systems may not be enough to fully automate such a system and therefore human intervention is a must.
- A too strict lending policy may result in a deterioration of the bank’s popularity with clients and hence result in loss of business.
- Such aspects cannot be measured objectively, and in such an aspect, human resources should amalgamate their knowledge with the one provided by the Expert System so as to come out with the best possible solution both for the bank itself and also for the client.
- This does not mean that the Expert System is an infallible way to secure that the loans given out are repaid in due time and without any problems.
- important resource which even an Expert System cannot replace completely.
- An expert and professional manager can assess situations in a different manner since he can actually talk to the clients and can draw conclusions which an Expert System would not be able to determine.
- Although the margin of error of Artificial Intelligence may be minimal, this should further be reduced by involving human intervention to examine and counter-check the work done by Expert Systems..
- Decision Support Systems.
- A Decision Support System too could have its various advantages in its utilisation for credit approval in banking, but most probably it would not be as powerful and as influential as an Expert System..
- A Decision Support System could provide correct and supportive results to the manager, but would not be able to learn from past experience so as to provide an even more accurate result when called into action again.
- Contrarily, Expert Systems can learn from experience, and increase their knowledge.
- Thus, the next time around the Expert System could provide even more accurate results..
- Unlike Decision Support Systems, Expert Systems provide answers to questions in a very specific problem area by making human-like inferences about.
- decision making, while for an Expert System, emphasis is based on replication of the reasoning of a human advisor.
- While in a Decision Support System, it is the user who queries the system, in an Expert System, the roles are inverted.
- It is the system who queries the user and takes decisions according to the inputted data..
- The major limitations of Expert Systems arise from their limited focus,.
- Expert Systems excel only in solving specific types of problems in a limited domain of knowledge.
- Expert Systems and the vital field of Artificial Intelligence are going from strength to strength

Xem thử không khả dụng, vui lòng xem tại trang nguồn
hoặc xem Tóm tắt