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Expert Systems in the Insurance Industry

Expert Systems in the Insurance Industry. Uses of Expert Systems in Insurance. Underwriting Policy Matching Benefit Querying Claim Processing. BenInq. A Benefit Inquiry tool. BenInq. helps customer service representatives determine what medical services a customer is covered for. Why?.

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Expert Systems in the Insurance Industry

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  1. Expert Systems in the Insurance Industry

  2. Uses of Expert Systems in Insurance • Underwriting • Policy Matching • Benefit Querying • Claim Processing

  3. BenInq A Benefit Inquiry tool

  4. BenInq • helps customer service representatives determine what medical services a customer is covered for

  5. Why? • Insurance companies have many products • Better searching • More detailed information • Easier to modify

  6. How It Works • Knowledge representation • Rule Representation • Reasoning Methods

  7. Knowledge Representation • Services • Benefits • Coverage • Business Rules • Cost sharing • Access • Administrative and Medical

  8. External Representation • Both Services and Benefits are organized in semantic networks • Services are organized in a multiple-inheritance hierarchy • Benefits are shown by using ‘covered’ and ‘excluded’ links between benefits and services nodes

  9. Internal Representation • Represented as a Formula-Augmented Semantic Network (FAN) • A FAN allows us to attach rules to nodes using well formed formulae • These rules allow us to apply regulations to each of the nodes

  10. Internal Representation

  11. Rule Representation • Rules are represented using well-formed formulae • translates to: Patients in Drug Rehabilitation programs lose all rehab benefits for one year if they are non-compliant Drug-rehab(p)  enrolled(x,p,i)  j sub(j,i)  non-compliant(x,p,j)  ((Drug-rehab(p2)  enrolled(x,p2,i2)  time(start(i2)) – time(end(j)) < 1year)  ~covered(x,p2))

  12. Reasoning Methods • Determining if a service is covered or excluded by a benefit • Determining which rules apply to a node

  13. Reasoning Methods

  14. Reasoning Methods • Well-Formed Formula Inheritance problem • Since nodes can inherit from multiple parents which rules apply? • Maximally Consistent Subsets (mcs) • Preferred Maximally Consistent Subsets (pmcs)

  15. PMCS • First remove conflicted and pre-empted edges • Then, starting at the focus node traverse upwards • At each node take the pmcs of the set computed so far and the wff’s at the current node

  16. Implementation • System comprises of two tools • inquiry tool • authoring tool • Implemented using VisualAge Smalltalk

  17. Usage • Two main user groups • Customer Service Representatives (CSR’s) • Policy Modifiers (PM’s)

  18. CSR’s View • Shows services, coverage information, and rules

  19. PM’s View • Can add new benefits, modify services and benefits, or delete products

  20. Evaluation • Users found the system very user friendly and required little to no training • PM’s however did have one issue: modifying or adding wff’s was difficult

  21. Colossus

  22. What is Colossus? • Used in claims processing • Injuries are classified according to 600 injury codes • Using this information it provides an amount to cover the damages the person suffered

  23. Why? • A GIO study found that there was a standard deviation of 80% for the same claim by different assessors

  24. How it works • Assessors are asked up to 700 questions (usually less) • The system compiles the information from the questions into 5 categories • The system combines the 5 categories into a percentage value

  25. Issues • There are 3 variables which affect how Colossus reaches its recommended figure • Interpretations of the facts by assessors • How Colossus uses the data to construct the 5 categories • The algorithm to combine the categories into a percentage

  26. Results • After implementing the system GIO found that the standard deviation for claims dropped from 85% to 15%

  27. Use • Originally used by GIO of Australia • Colossus also is used by 13 of the top 20 US Property and Casualty insurers

  28. Bibliography • 1) Morgenstern, L., Singh, M., An Expert System Using Nonmonotonic Techniques for Benefits Inquiry in the Insurance Industry, Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence • 2) Morgenstern, L., Inheriting Well-formed Formulae in a Formula-Augmented Semantic Network, KR'96: Principles of Knowledge Representation and Reasoning • 3) Greenleaf, G., A Colossus come to judgement: GIO’s expert system on general damages, Law & Information Technology column, Australian Law Journal 26 November 1992

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