Integrated Case-Based and Rule-Based reasoning approaches for Insurance

1. Integrated Case-Based and Rule-Based reasoning approaches for Insurance Presented BY Palwencha Nagraj Krishna (04329801) Guided By Prof Rajendra M. Sonar

2. Content • Introduction to Expert Systems • Case Base Reasoning • Hybrid Systems • Different Integrated Approaches • Insurance Domain Application • Problem Definition • Application- A Hybrid Expert System Framework

3. Expert Systems • Expert systems are defined as an intelligent computer program that uses knowledge and inference procedures to solve problems those are difficult enough to require significant human expertise for their solution. • Knowledge-based expert systems, or simply expert systems, use human knowledge to solve problems that normally would require human intelligence. Dr. Peter R. Gillett, Associate Professor, Department of Accounting & Information Systems, Faculty of Management, Rutgers University

4. Software Inference Engine Knowledge Engineer Users Expert Knowledge Base Working Memory Spreadsheet Database Data Hardware ES Components James P. Ignizio, “Introduction to Expert Systems The Development and Implementation of Rule-Based Expert Systems”, McGraw-Hill International Editions, Computer Science Series, 2000.

5. Knowledge Acquisition and Validation • Knowledge Engineering (KE) • Acquire Knowledge • Validate Knowledge • Represent Knowledge • Inferencing Knowledge Representation • KR Type • OAV Triplet • Semantic Network • Frames • Rules

6. Introduction to CBR • Case base reasoning system use the technique to match a situation or problem description to a stored database. • Input is given by the user on the current situation and the output is case retrieval to the most similar match to the database. • The CBR engine first searches for case history that are similar to the given description. • The main intention is to reuse previous experiences for actual problems. . Diagnostic Stratrgies, “Expert System Development Series Introduction to Case- Base Reasoning”, www.DiagnosticStrategies.com.

7. The CBR cycle Ian Watson & Farhi Marir (1994), “Case-Based Reasoning: A Review”, Cambridge University Press, 1994. The Knowledge Engineering Review, Vol. 9, No. 4: pp355-381

8. Different methods • Nearest neighbor: The system would simply prefer cases that match more features to a case that matched fewer. • Induction: Inductive approaches to indexing are useful where the retrieval goal or case outcome is well defined. • The output of the induction process is in the form of a decision tress.

9. Different methods cont….. • Knowledge guided: • A knowledge-guided approach uses human knowledge to the induction process by manually identifying known case features that are considered important

10. Hybrid Intelligent Systems • Hybrid Intelligent System is a combination of multiple techniques • Almost every conceivable problem has been approached using some form of hybrid system. Suran Goonatilake, Sukdev Khebbal, “Intellegent Hybrid Systems “, Goonatilake Khebbal Editor

11. Integrated expert systems and case-based reasoning Indexed Case Library Indexing CBR Problem RBR Solution Combination Andrew R. Golding , Paul S. Rosenbloom, “Improving accuracy by combining rule-based and case-based reasoning”, ELSEVIER, Artificial Intelligence, Issue: November 1996, pages:215-254

12. ES and CBR in Insurance • It consist of three key process • data entry, • data revision and • evaluation of data by the expert • RuleMaster provides ways to develop the rules in the system. Dr. Gary A. Wicklund and Ms. Roberta M. Roth, “Expert Systems in Insurance Underwriting: Model Development and Application”, ACM ,Issue:1987, Pages: 129 – 139.

13. Problem Definition Field Officer Risk Assessment Agent Advice Policy Client

14. Hybrid approach for insurance Risk Assessment Parameter Indexed Case Library Indexing Problem CBR RBR Solution Combination Andrew R. Golding , Paul S. Rosenbloom, “Improving accuracy by combining rule-based and case-based reasoning”, ELSEVIER, Artificial Intelligence, Issue: November 1996, pages:215-254

15. Application format • Age: Date of birth ->Major, Minor -> age limit -> find available policy period • Education: 10, 12, ITI, Diploma, Graduate, Post-Graduate, PhD, Professional (engg/medical/lawer) …[Is education on questionnaire necessary] • Gender: Male, Female -> Female -> Housewife • Occupation: • Service: Government, Non-Government, Private, Professional, Military, Navy, etc • Business: Consultant, Industry, Retailing, Agriculture • Expected Period of Policy • Purpose of Policy: Investment, Child Education • Income (Rs.): Take-home Monthly/ yearly income • Assets (Rs.): Computer/House/Car/Bike etc -> Tentative value of Assets • Liabilities (Rs.): Loans and other financial liabilities • Present LIC Installment (Rs.): monthly/quarterly/half-yearly/yearly • Number of Dependents • Physical Inability: like handicapped/ Mental disorder • Diseases: HIV/ BP/ Diabetes • Loan Facility required on Policy? • Calculate Risk • Calculate Installment

16. Risk Assessment • Occupation • Income • Assets • Liabilities • Physical Inability • Diseases

17. Application-A Hybrid Expert System Framework • IIT has developed a Hybrid AI shell environment named as iKen Core • This shell has four techniques • Rule Based Reasoning • Case Based Reasoning • Genetic Algorithm • Artificial Neural Network

18. First Stage – Work Done • Background Study Expert Systems and Case Base Reasoning • Literature survey – Related work • Integrated approaches • Study of Expert System working • Analysis of Insurance Domain • Studied the potential applications of insurance domain. • Tried to define the prototype we are going to use

19. Future Study • Devising methodology for knowledge acquisition, presentation and retrieval. • Selection/customization of proper tool. • Developing prototype systems.

20. Thank You