Predictive Modeling Survey

Predictive Modeling WorkshopTraining for development and deployment

The following presentation outlines a introductory training course for actuaries, and quantitative analysts to learn basic approaches and tools to create predictive model solutions in Property & Casualty Insurance

Francis Analytics and Actuarial Data Mining

Actuarial Data Mining Services

Francis Analytics

www.data-mines.com

2Francis Analytics www.data-mines.com


Francis Analytics

Introduction

Predictive Modeling is an important new development for modifying traditional actuarial approaches to risk in P&C insurance

Actuaries and Quantitative Analysts can help advance their company’s competitive position with a greater understanding of analytical methods and tools

Learning opportunities in advanced actuarial modeling area not widely available.



Francis Analytics

Predictive Modeling Survey Course

A two day hands-on workshop Delivered by experienced practitioners Includes case study learning approach Includes instructions in using software and the latest

statistical methods being deployed by industry leaders.

Custom course can be designed to fit specific needs

Participants will be able to conduct a Predictive Modeling project in their organizations and present the business case to non-technical management



Francis Analytics

Course Agenda

Session Description

Introduction to P&C Actuarial Data Introduction and review of actuarial data for property & casualty insurance including basic operational view

Introduction to Predictive Modeling Methods Survey of Predictive Modeling approaches and current state of the art in P&C insurance

Walk-through model development phases Walk-through of the project process for delivering successful predictive modeling capabilities

Focus: Data Preparation Techniques Focus teaching on data discovery and preparation steps used in the model development process

Focus: Mathematical Methods Focused teaching of the key statistical algorithms used in Predictive Modeling

Focus: Statistical Software Focused teaching and hands on tutoring of an statistical modeling package software

Hands-on Case Study workshop Live end-to-end walk through of a predictive modeling project

Validation Methods Teaching and illustration of model validation approaches to present to management

Industry Leading Innovation Discussion of industry leading innovation in development and deployment of Predictive Models



Francis Analytics

Case Study Approach

Actual P&C example Sample Actuarial Dataset provided Explore challenges throughout the

exploration/model/deployment life-cycle

Practitioners can design a custom case study with a specific modeling need or data-set provided by the company sponsor or organization.



Francis Analytics

Leading Statistical Methods Covered

Generalized Linear Modeling including Logistic Regression

Neural Network Classification and Regression Trees Benchmarking with Naive Bayes Tree ensemble method Random Forest Support Vector Machines



Francis Analytics

Software

Excel Access Free Software

R Web based software

S-Plus (similar to commercial version of R) SPSS CART/MARS Data Mining suites

Participants will download, install, tour and model in R, a freeware modeling tool



Francis Analytics

Learning Outcomes

Working knowledge of the major statistical methods used for Predictive Modeling

Practical knowledge of advanced data mining techniques ready to be applied

General knowledge of Property & Casualty insurance data and related operations

General knowledge of Predictive Modeling project life-cycle management

Working knowledge of modeling software packages and review of leading software solutions and proprietary methods

The ability to manage the validation of models and present the validation results to laymen



Francis Analytics

Logistics

Item

2 days

Overnight Homework as assigned

Course materials and Data Set Berry, M. and Linoff, G. Data Mining Techniques 2nd Edition, Wiley, supplied to all students

Software ‘R’ statistical programming language, including download and install instructions

Session Schedule

Limit of 25 participantsClass Size

California Department of Insurance public (CAARP) data on private passenger auto will be supplied to all participants as a download

Arranged by agreement Customized Content



Francis Analytics

Pricing

Item

Course Fee TBD

Course Materials Included

Follow-up Consultation Included

On-site/Group/Company Sponsored Priced by custom proposal *

* Pricing for customized workshop content and delivery by agreement



Francis AnalyticsWorkshop Presenters

Louise Francis, FCAS, MAAA

Louise Francis is the Consulting Principal and founder of Francis Analytics and Actuarial Data Mining, Inc. where she leads data mining and related actuarial projects and engagements. Ms. Francis has introduced insurance professionals to data mining methods both as a speaker at conferences and as an author of papers and articles on data mining topics. Three of her papers were awarded the Data Quality/Data Technology prize by the CAS (Casualty Actuarial Society) and IDMA (Insurance Data Management Association).

As an insurance professional, Ms. Francis has expertise in a variety of techniques for pricing and reserving insurance products, both on a traditional and leading edge basis. She also has experience planning and evaluating programs for claims loss cost reduction. Ms. Francis pioneered the application of data mining technologies such as neural networks and decision trees to insurance data to identify patterns useful for mitigating claims costs and making underwriting decisions. Ms. Francis introduced procedures for benchmarking individual customer's data to industry targets to assess the performance of third party claims administrators and to assist clients with cost reduction efforts.

Ms. Francis has over 20 years of experience in the actuarial profession. Prior to starting her own firm, she was Director and Associate Actuary for CIGNA Property and Casualty where she provided actuarial expertise to the Claims Division and ESIS, CIGNA's third party claims administrator. She was responsible for evaluating the overall performance of the Claims Division and measuring the effectiveness of specific Claims Division initiatives to reduce claims costs. Ms. Francis has also worked as a consultant with Towers Perrin and Sedgwick James.

Ms Francis is chair of the Casualty Actuarial Society's (CAS) Committee on the Theory of Risk, a committee charged with the sponsorship and dissemination of research efforts on risk measurement and analysis. She participates on an American Academy of Actuaries committee which develops standards of actuarial practice for the actuarial profession.

Ms. Francis received her Bachelor of Arts degree from William Smith College and a Master of Science degree in Health Sciences from the State University of New York at Stony Brook. She is a Fellow of the Casualty Actuarial Society and a member of the American Academy of Actuaries.



Francis Analytics

Workshop Presenters

RICHARD A. DERRIG, PH.D.

Dr. Derrig is President of OPAL Consulting LLC, established in February, 2004 to provide research and regulatory support to the property-casualty insurance industry.

Prior to forming OPAL, Dr. Derrig held various positions at the Automobile Insurers Bureau of Massachusetts and at the Insurance Fraud Bureau of Massachusetts over a twenty seven year period, retiring in January, 2004 as Senior Vice President at AIB and Vice President of Research at IFB. During the spring semesters of 1994 and 2002, he was a Visiting Lecturer and Research Fellow in the Department of Risk Management and Insurance at the Wharton School, University of Pennsylvania. Dr. Derrig has been appointed a visiting scholar at Wharton for 2004 and 2005.

Prior to joining the Bureaus, he taught graduate and undergraduate mathematics at Villanova University, Wheaton College (MA) and Brown for a total of thirteen years. He earned a Bachelor of Science degree in mathematics from St. Peter's College as well as Master's and Doctoral degrees from Brown University.

Dr. Derrig is the recipient of numerous awards and recognitions for his contribution to mathematics and actuarial sciences. He the author or co-author of numerous articles, review and contributions in the field.

He has lectured extensively on insurance topics to professional actuarial groups; the Casualty Actuarial Society, ASTIN, trade associations, and law enforcement personnel; and to seminars at the Universities of Barcelona, Hamburg, Montreal, Tel Aviv, Pennsylvania, Illinois, Texas, Minnesota, Wisconsin and others in the U.S. He was a director of the American Risk and Insurance Association (1992-1995) and a recipient of the President’s Award (1997). He is an academic correspondent of the CAS and a member of the Mathematical Association of America, American Statistical Association, and the Association of Certified Fraud Examiners. He serves on the Insurance Fraud and Auto Injury Study Committees of the Insurance Research Council and the CPCU Advisory Committee of the American Institutes. Since 1991, he has compiled an annotated bibliography of worldwide insurance fraud research that is made available at www.derrig.com/ifrr/ifrr.asp.



Francis Analytics

Contact

Ms. Louise Francis, FCAS, MAAA

Francis Analytics

215-923-1567

[email protected]

www.data-mines.com

mailto:[email protected]

http://www.data-mines.com/

Predictive Modeling Survey

Documents

Transcript of Predictive Modeling Survey