Insurance Policy Advisor

CHAPTER ONE: Introduction
1. Background
  1. What is Insurance?
  2. What is Insurance Policy?
2. Problem Statement
  1. Customer with different backgrounds, economic conditions, risk preferences & needs
  2. Customer not clearly been informed about coverage
  3. Insurance company: challenge on adapting digital marketing strategies
3. Project Objectives
  1. To identify the variables for insurance consultant to make a decision making
  2. To apply decision tree in constructing rule based on given data set by expert
  3. To suggest the suitable insurance policy to the client
4. Scope of the Research
  1. User
    1. Customer
    2. Insurance Consultant
  2. Types of Insurance
    1. life
    2. health
    3. investment-oriented
    4. annuity
    5. accident
5. Project Significant
  1. reducing the number of customer who current over/under payments
  2. assisting customer to more understand the policy for future coverage
  3. Insurance company / expert consultant system has the intelligent techniques ability that able to do suggestion
6. Summary
CHAPTER TWO: Literature Review
1. Domain
  1. Insurance Policy
    1. Introduction to risk management and insurance, 10th ed Dorfman, Mark S. 1945 Cather, David A. 2013
    2. Understanding Health Policy, A Clinical Approach 6th ed Bodenheimer T., Grumbach K. 2012
    3. Foundations of financial management 14th ed Block, Stanley B. 2011
    4. Development of Knowledge Model for Insurance Product Decision Using The Associative Classification Approach Azuraliza Abu Bakar, Zalinda Othman, Mohd Saiful Nizam MD Yusoff & Ruhaizan Ismail, 2010
    5. Life Insurance Solomon Stephen Huebner, 1982
    6. Life, health & annuity reinsurance 3rd ed Tiller, John E. Tiller, Denise Fagerberg 2009
2. Technique
  1. Fuzzy Logic
    1. Applications of Fuzzy Classification in Insurance Industry: A Fuzzy Logic Based Approaches Rita Ganguly, Kajla Basu & Anirban Sarkar, 2011
    2. A Fuzzy Expert System Approach to Insurance Risk Assessment using FuzzyClips Luis A. Carreno & Dr Yashvant Jani, 1993
    3. An Overview Of Insurance Uses of Fuzzy Logic Arnold F. Shapiro, 2007
    4. A Fuzzy Logic Based Model For Life Insurance Underwriting When Insurer is Diabetic Sanjeev Kumar & Hemlata Jain, 2012
    5. A First Course in Fuzzy Logic Hung T. Nguyen, Elbert A. Walker
  2. Decision Tree
    1. Data mining concepts, models, methods, and algorithms Kantardzic, Mehmed. 2011
    2. Anytime Learning of Decision Trees Saher Esmeir, Shaul Markovitch, 2007
    3. Using decision tree for diagnosing heart disease patients Mai Shouman, Tim Turner, Rob Stocker, 2011
  3. Fuzzy Decision Tree
    1. Software Cost Estimation using Fuzzy Decision Trees Andreas S. Andreo & Efi Papatheocharous, 2008
    2. wFDT: weighted fuzzy decision trees for prognosis of breast cancer survivability Umer Khan, Hyunjung Shin, Jong Pill Choi, Minkoo Kim, 2008
  4. Case Base Reasoning
    1. Artificial Intelligence: A Guide to Intelligent Systems 2nd Ed Michael Negnevitky, 2005
3. Summary
CHAPTER THREE: Methodology
1. Preliminary Study
  1. Identify Project Domain
    1. Project titles
    2. Problem statements
    3. Objectives
    4. Scopes
    5. Significances
    6. Expected outcome
2. Knowledge Acquisition
3. Data Collection
4. Empirical Study
5. System Development
6. System Evaluation
CHAPTER FOUR: Analysis and Discussion
1. J48
2. Fuzzy Logic
  1. Matlab

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Insurance Policy Advisor

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