Session 40 PD, How Would I Get Started With Predictive Modeling? Moderator: Douglas T. Norris, FSA, MAAA
|
|
- Agnes Miles
- 6 years ago
- Views:
Transcription
1 Session 40 PD, How Would I Get Started With Predictive Modeling? Moderator: Douglas T. Norris, FSA, MAAA Presenters: Timothy S. Paris, FSA, MAAA Sandra Tsui Shan To, FSA, MAAA Qinqing (Annie) Xue, FSA, CERA, MAAA SOA Antitrust Disclaimer SOA Presentation Disclaimer
2 How Would I Get Started with Predictive Modeling? #040PD - Society of Actuaries Annual Meeting Sandra To, VP and Deputy Chief Reserving Actuary October
3 Definitions: Let s start by agreeing on what we are discussing Predictive modeling a process used in predictive analytics to create a statistical model of future behavior Predictive analytics the area of data mining concerned with forecasting probabilities and trends Data mining the practice of examining large databases in order to generate new information Big data extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations, especially relating to human behavior and interactions
4 Business Goals: Begin with the end in mind Many applications of predictive modeling. What will your model do? Source: Towers-Watson, The Future of Predictive Modeling, Emphasis
5 Perils of a Poorly Designed Plan
6 Model Relevancy 5
7 Things to Consider Define short-, mid- and long-term business goals. How can data modeling support these initiatives? What do you expect to get out of the effort? Reject unclear objectives Big Data is an expensive proposition. Do it for a purpose not just because it is trendy. Determine monetary investment sizing. How much are you willing to invest? How quickly must the initiative move forward? When must the initial phase be complete? Define internal data resources. Define external data opportunities. Identify internal talent. Build and invest in resources, contract or partner?
8 Skills Needed to Create Effective Modeling Projects Actuaries vs Data Science? Source: 7
9 Tools for Creating Effective Models Spreadsheets (Microsoft Excel) Neural networks Data mining Linear & logistic regression testing Business rules Cox regression Assumptions Clustering Historical data Scorecards Actuarial modeling platforms Association rules Prophet SAP Multiple models MoSes SQL Server Ensemble SAS AXIS Etc. Decision trees Segmentation Chaining Composition Rule set models Restricted Boltzamn Machine Industry benchmarks Behavioral metrics 8
10 Many Technologies and Potential Partners
11 Talent & Framework 10
12 Plan for success How did we determine that output make business sense? Active communication plan throughout development process Interactive process with business owners, technology team, sales, operations, etc. How do we make sure we deliver on our investments? Know size of opportunities How do we leverage what we have already built to achieve these opportunities Plan to operationalize what we have built How do we ensure that we meet our business objectives? Performance indicators Dashboards Owner for process Look for improvements, it should be an iterative process 11
13 How Would I Get Started with Predictive Modeling from a Newbie s Perspective
14 2
15 Newbie s Motto -Just Do It 3
16 Conferences Internet Meetings Coffee Chats 4
17 5
18 What s My Role? 6
19 R&D Client Markets New Solutions Costing IF Management Nitin Nayak Stephen Abrokwah JJ Carroll Li Lin Allen Pinkham Tommy Wade Jane Wang Brian Carteaux 7
20 What s in the beginning, in the middle, and in the end? Application Data Reports MIB, MVR, UW, Predictive Modeling Presentations Third-party Data 8
21 Where do we fit? Business Objective Data Insights Cost Benefit Business Strategy Consumer Experience Experience Study. Model Insights Feedback Loop 9
22 A Case Study Demonstrate predictive modelling process Identify factors associated with age 50+ life insurance ownership HRS2014 survey data 20,000 peopleage 50+ Marital status, education, #kids, job status,.. and Life insurance ownership Overall understanding Data Preparation Select interested subgroup Select potential predictors Multivariate logistic model Select predictors based on fitness measures Final Predictors Performance Metrics Close financial protection gap for pre-retirement population 10
23 Select potential predictors Univariate Analysis Years of Education Comparator Odd Ratio Post College High School Frequency Tables College Graduate High School Some College High School Less than High School High School
24 Select predictors x: for someone who does not own life insurance, it is the probability that he/she is predicted as a life insurance owner - false positive rate y: for someone who does own life insurance, it is the probability that he/she is predicted as a life insurance owner - true positive rate Age Age + Gender Age + Gender + Region 12
25 Final Model # Predictors 1 CURRENT JOB STATUS 2 1ST ADDRESS STATE 3 OWN-RENT HOME 4 REGULAR USE OF WEB FOR 5 PENSION INCOME 6 YEARS OF EDUCATION 7 COUNT OF KIDS 8 INCOME TAX RETURN 9 MARITAL STATUS 10 SEX OF INDIVIDUAL 11 NUMBER DRINKS- PER DAY 12 WHAT PERCENT TAKE RISKS 13 CURRENT AGE 14 SMOKE CIGARETTES NOW Correctly classified life insurance owners: 75% Correctly classified no life insurance owners: 63% 13
26 Newbie s Motto -Just Do It 14
27 15
28 Legal notice 2016 Swiss Re. All rights reserved. You are not permitted to create any modifications or derivative works of this presentation or to use it for commercial or other public purposes without the prior written permission of Swiss Re. The information and opinions contained in the presentation are provided as at the date of the presentation and are subject to change without notice. Although the information used was taken from reliable sources, Swiss Re does not accept any responsibility for the accuracy or comprehensiveness of the details given. All liability for the accuracy and completeness thereof or for any damage or loss resulting from the use of the information contained in this presentation is expressly excluded. Under no circumstances shall Swiss Re or its Group companies be liable for any financial or consequential loss relating to this presentation. 16
29 Timothy Paris, FSA, MAAA Session 040 How Would I Get Started With Predictive Modeling? Variable Annuity Case Study October 24, 2016
30 Industry Model Development 2
31 By Company By Quarter By Guarantee Type Moneyness Distribution Channel Contract Size Interaction with Partial Withdrawals 3
32 Interpreting Experience Data Translating to assumptions is very difficult using traditional methods! Avoid missing important factors? Adequacy of company-level data? Interactions between factors? Avoid double counting? Changes over time? Process transparency and consistency? 4
33 Industry Data Traditional Analysis Statistical Techniques Expert Judgment 5
34 y x E(y x) Classical Linear Modeling g[e(y x)] Generalized Linear Modeling (GLM) Flexible framework Non-normal Non-constant variance Simple Linear Modeling 6
35 Generalized Linear Modeling 7
36 Logistic Regression Model ln μμ 1 μμ = ββ 0 + ββ ii xx ii Log of odds is a linear function of key factors Binary values, such as surrenders or deaths 8
37 Goodness of Fit Predictive Power 9
38 Aikake s Information Criterion Actual-to-Expected Ratios Expert Judgment Much More 10
39 Aikake s Information Criterion AAAAAA = 2kk 2ln(LL) Metric to compare relative quality of alternative models. Lower is better. Rewards goodness of fit (L), but with penalty for more model factors (k) to mitigate risk of overfitting the model on train data. 11
40 Actual-to-Expected Ratios AA/EE Develop E using train data, compare to A from test data Examine in aggregate, by cohorts, and over time Look at range of outcomes and tails 12
41 Expert Judgment Business context, sensibility, materiality, parsimony More data usually beats more complex models Let the data speak Use simples models for complex data, and complex models for simple data 13
42 Factor Exploration 14
43 Factor Exploration 15
44 Factor Exploration 16
45 Factor Exploration 17
46 Factor Exploration 18
47 Aikake s Information Criterion Actual-to-Expected Ratios Expert Judgment Model Selection Much More 19
48 Factor Exploration 20
49 Company Customization and Benchmarking 21
50 22
51 Actuarial good practice Benchmarking Stakeholders want to know Early warning for management actions 23
52 Company Customization Similar to traditional actuarial credibility theory Avoid unnecessary and speculative guesswork whenever possible Balance between industry and company data 24
53 Benefits Goes beyond the endless series of reactionary point estimates to quantify range of behavioral values Consistent mathematical framework for assumption setting and review/updates Allows for company-level customization from max data set (industry) 25
54 Industry Data Traditional Analysis Statistical Techniques Expert Judgment 26
Session 63 PD, Annuity Policyholder Behavior. Moderator: Kendrick D. Lombardo, FSA, MAAA
Session 63 PD, Annuity Policyholder Behavior Moderator: Kendrick D. Lombardo, FSA, MAAA Presenters: Eileen Sheila Burns, FSA, MAAA Kendrick D. Lombardo, FSA, MAAA Timothy S. Paris, FSA, MAAA Timothy Paris,
More informationBehavioral Analytics for Annuities. Timothy Paris
Equity-Based Insurance Guarantees Conference Nov. 6-7, 2017 Baltimore, MD Behavioral Analytics for Annuities Timothy Paris Sponsored by 2017 Equity-Based Insurance Guarantees Conference Session 2B Behavioral
More informationSession 97 PD, Variable Annuity Guaranteed Living Benefit Utilization Studies and Benefit Utilization in Fixed Indexed Annuities
Session 97 PD, Variable Annuity Guaranteed Living Benefit Utilization Studies and Benefit Utilization in Fixed Indexed Annuities Moderator: Patrick David Nolan, FSA, MAAA Presenters: Jafor Iqbal Joseph
More informationSession 19PD: Behavioral Analytics for Annuities. Moderator: Dorothy L Andrews ASA,MAAA
Session 19PD: Behavioral Analytics for Annuities Moderator: Dorothy L Andrews ASA,MAAA Presenters: Dorothy L Andrews ASA,MAAA Timothy S Paris FSA,MAAA SOA Antitrust Disclaimer SOA Presentation Disclaimer
More informationSession 113 PD, Data and Model Actuaries Should be an Expert of Both. Moderator: David L. Snell, ASA, MAAA
Session 113 PD, Data and Model Actuaries Should be an Expert of Both Moderator: David L. Snell, ASA, MAAA Presenters: Matthias Kullowatz Kenneth Warren Pagington, FSA, CERA, MAAA Qichun (Richard) Xu, FSA
More informationModerator: Missy A Gordon FSA,MAAA. Presenters: Missy A Gordon FSA,MAAA Roger Loomis FSA,MAAA
Session 52PD: Financial Analysis: Impairment, Stress Testing and Predictive Modeling for Health Companies Moderator: Missy A Gordon FSA,MAAA Presenters: Missy A Gordon FSA,MAAA Roger Loomis FSA,MAAA SOA
More information2018 Predictive Analytics Symposium Session 10: Cracking the Black Box with Awareness & Validation
2018 Predictive Analytics Symposium Session 10: Cracking the Black Box with Awareness & Validation SOA Antitrust Compliance Guidelines SOA Presentation Disclaimer Cracking the Black Box with Awareness
More informationSession 2. Predictive Analytics in Policyholder Behavior
SOA Predictive Analytics Seminar Malaysia 27 Aug. 2018 Kuala Lumpur, Malaysia Session 2 Predictive Analytics in Policyholder Behavior Eileen Burns, FSA, MAAA David Wang, FSA, FIA, MAAA Predictive Analytics
More informationSession 84 PD, SOA Research Topic: Conversion Mortality Experience. Moderator: James M. Filmore, FSA, MAAA. Presenters: Minyu Cao, FSA, CERA
Session 84 PD, SOA Research Topic: Conversion Mortality Experience Moderator: James M. Filmore, FSA, MAAA Presenters: Minyu Cao, FSA, CERA James M. Filmore, FSA, MAAA Hezhong (Mark) Ma, FSA, MAAA SOA Antitrust
More informationMachine Learning Applications in Insurance
General Public Release Machine Learning Applications in Insurance Nitin Nayak, Ph.D. Digital & Smart Analytics Swiss Re General Public Release Machine learning is.. Giving computers the ability to learn
More information2017 Predictive Analytics Symposium
2017 Predictive Analytics Symposium Session 7, Risk Assessment Applications of Predictive Analytics Moderator: Priyanka Srivastava Presenters: Dihui Lai, Ph.D. Nitin Nayak, Ph.D., MBA Jason L. VonBergen,
More informationSession 5. Predictive Modeling in Life Insurance
SOA Predictive Analytics Seminar Hong Kong 29 Aug. 2018 Hong Kong Session 5 Predictive Modeling in Life Insurance Jingyi Zhang, Ph.D Predictive Modeling in Life Insurance JINGYI ZHANG PhD Scientist Global
More informationWe are experiencing the most rapid evolution our industry
Integrated Analytics The Next Generation in Automated Underwriting By June Quah and Jinnah Cox We are experiencing the most rapid evolution our industry has ever seen. Incremental innovation has been underway
More informationSession 55 PD, Individual Life Mortality Experience Study Results. Moderator: Cynthia MacDonald, FSA, CFA, MAAA
SOA Antitrust Disclaimer SOA Presentation Disclaimer Session 55 PD, Individual Life Mortality Experience Study Results Moderator: Cynthia MacDonald, FSA, CFA, MAAA Presenters: Roland Fawthrop, FSA, MAAA
More informationSession 88 PD, PBR: Practical Implementation and Governance Issues. Moderator: Helen Colterman, FSA, CERA, ACIA
Session 88 PD, PBR: Practical Implementation and Governance Issues Moderator: Helen Colterman, FSA, CERA, ACIA Presenters: Paul M. Fischer, FSA, MAAA Carrie Lee Kelley, FSA, MAAA Christopher Almer Whitney,
More informationSession 20, Professionalism and PBR: Adapting to a New Environment. Moderator: Jerry F. Enoch, FSA, MAAA
Session 20, Professionalism and PBR: Adapting to a New Environment Moderator: Jerry F. Enoch, FSA, MAAA Presenter: Mark William Birdsall, FSA, MAAA, FCA Arnold A. Dicke, FSA, MAAA, CERA Lorne W. Schinbein,
More informationCredit Card Default Predictive Modeling
Credit Card Default Predictive Modeling Background: Predicting credit card payment default is critical for the successful business model of a credit card company. An accurate predictive model can help
More informationSession 31 PD, Product Design & Policyholder Behavior. Moderator: Timothy S. Paris, FSA, MAAA
Session 31 PD, Product Design & Policyholder Behavior Moderator: Timothy S. Paris, FSA, MAAA Presenters: Michael Anthony Cusumano, FSA Timothy S. Paris, FSA, MAAA Product Design and Policyholder Behavior
More informationSession 176 PD - Emerging Trends in Model Risk Management for Small Companies. Moderator: Vikas Sharan, FSA, FIA, MAAA
Session 176 PD - Emerging Trends in Model Risk Management for Small Companies Moderator: Vikas Sharan, FSA, FIA, MAAA Presenters: Brody D. Lipperman, FSA, CERA, MAAA Stefanie J. Porta, ASA, MAAA Vikas
More informationSession 2A: Risk Management Perspective in Predictive Modeling. Moderator: Mark W. Griffin, FSA, CERA
Session 2A: Risk Management Perspective in Predictive Modeling Moderator: Mark W. Griffin, FSA, CERA Presenters: Lloyd D. Milani, FSA, MAAA, FCIA Serhat Guven, MAAA, FCAS SOA Antitrust Disclaimer SOA Presentation
More informationExploring health data: From wearables to
Exploring health data: From wearables to personalized insights and engagement Swiss Re Institute Symposium, Boston 2017 Speakers: Andreas Caduff & Dave Wang Moderator: JJ Carroll Group 1: How might we
More information2017 Predictive Analytics Symposium
2017 Predictive Analytics Symposium Session 20, Marketing and Distribution Applications of Predictive Analytics Moderator: Priyanka Srivastava Presenters: Matt Olson Xiaojie Wang, FSA, CERA SOA Antitrust
More informationSession 5. A brief introduction to Predictive Modeling
SOA Predictive Analytics Seminar Malaysia 27 Aug. 2018 Kuala Lumpur, Malaysia Session 5 A brief introduction to Predictive Modeling Lichen Bao, Ph.D A Brief Introduction to Predictive Modeling LICHEN BAO
More informationExpanding Predictive Analytics Through the Use of Machine Learning
Expanding Predictive Analytics Through the Use of Machine Learning Thursday, February 28, 2013, 11:10 a.m. Chris Cooksey, FCAS, MAAA Chief Actuary EagleEye Analytics Columbia, S.C. Christopher Cooksey,
More informationPerspectives on European vs. US Casualty Costing
Perspectives on European vs. US Casualty Costing INTMD-2 International Pricing Approaches --- Casualty, Robert K. Bender, PhD, FCAS, MAAA CAS - Antitrust Notice The Casualty Actuarial Society is committed
More informationSession 2. Leveraging Predictive Analytics for ERM
SOA Predictive Analytics Seminar Hong Kong 29 Aug. 2018 Hong Kong Session 2 Leveraging Predictive Analytics for ERM Janice Wang, ASA, CERA David Wang, FSA, FIA, MAAA Leveraging Predictive Analytics in
More informationActuarial. Predictive Modeling. March 23, Dan McCoach, Pricewaterhouse Coopers Ben Williams, Towers Watson
Actuarial Data Analytics / Predictive Modeling March 23, 215 Matthew Morton, LTCG Dan McCoach, Pricewaterhouse Coopers Ben Williams, Towers Watson Agenda Introductions LTC Dashboard: Data Analytics Predictive
More informationSession 79PD, Using Predictive Analytics to Develop Assumptions. Moderator/Presenter: Jonathan D. White, FSA, MAAA, CERA
Session 79PD, Using Predictive Analytics to Develop Assumptions Moderator/Presenter: Jonathan D. White, FSA, MAAA, CERA Presenters: Missy A. Gordon, FSA, MAAA Brian M. Hartman, ASA SOA Antitrust Disclaimer
More informationUpcoming Changes to the SOA Education Requirements
Upcoming Changes to the SOA Education Requirements STUART KLUGMAN, FSA, CERA, PhD Senior Staff Fellow, Education SOCIETY OF ACTUARIES June 27, 2017 Today s Topics 2017 FM/MFE Changes ASA Changes Why ASA
More informationSession 03PD: PBR Reporting and Disclosures Thinking About the End at the Beginning. Moderator: James Russell Collingwood ASA,MAAA
Session 03PD: PBR Reporting and Disclosures Thinking About the End at the Beginning SOA Antitrust Disclaimer SOA Presentation Disclaimer Moderator: James Russell Collingwood ASA,MAAA Presenters: James
More informationPredicting and Preventing Credit Card Default
Predicting and Preventing Credit Card Default Project Plan MS-E2177: Seminar on Case Studies in Operations Research Client: McKinsey Finland Ari Viitala Max Merikoski (Project Manager) Nourhan Shafik 21.2.2018
More informationMaking the Link between Actuaries and Data Science
Making the Link between Actuaries and Data Science Simon Lee, Cecilia Chow, Thibault Imbert AXA Asia 2 nd ASHK General Insurance & Data Analytics Seminar Friday 7 October 2016 1 Agenda Data Driving Insurers
More informationSession 57PD, Predicting High Claimants. Presenters: Zoe Gibbs Brian M. Hartman, ASA. SOA Antitrust Disclaimer SOA Presentation Disclaimer
Session 57PD, Predicting High Claimants Presenters: Zoe Gibbs Brian M. Hartman, ASA SOA Antitrust Disclaimer SOA Presentation Disclaimer Using Asymmetric Cost Matrices to Optimize Wellness Intervention
More information2017 Predictive Analytics Symposium
2017 Predictive Analytics Symposium Session 24, General Insurance Applications of PA Moderator: Stuart Klugman, FSA, CERA, Ph.D. Presenter: Peter Wu, ASA, FCAS, MAA SOA Antitrust Compliance Guidelines
More informationPricing Analytics for the Small and Medium Sized Company
Pricing Analytics for the Small and Medium Sized Company The Road to Advanced Pricing Practices 2014 CAS RPM By: Len Llaguno April 1, 2014 2014 Towers Watson. All rights reserved. 0 Antitrust Notice The
More informationSession 030 PD - PBR Stochastic Reserve - Challenges and Possible Solutions. Moderator: Sebastien Cimon Gagnon, FSA, CERA, MAAA
Session 030 PD - PBR Stochastic Reserve - Challenges and Possible Solutions Moderator: Sebastien Cimon Gagnon, FSA, CERA, MAAA Presenters: Timothy C. Cardinal, FSA, CERA, MAAA Andrew G. Steenman, FSA,
More informationPredictive modelling around the world Peter Banthorpe, RGA Kevin Manning, Milliman
Predictive modelling around the world Peter Banthorpe, RGA Kevin Manning, Milliman 11 November 2013 Agenda Introduction to predictive analytics Applications overview Case studies Conclusions and Q&A Introduction
More informationSession 5: Evolution of ORSA in the US. Moderator: Michael Anthony McComis Jr. MAAA,FCAS
Session 5: Evolution of ORSA in the US Moderator: Michael Anthony McComis Jr. MAAA,FCAS Presenters: S Douglas Caldwell FSA,MAAA,CERA Chad R Runchey FSA,MAAA Elisabetta Russo MAAA SOA Antitrust Disclaimer
More informationHow Advanced Pricing Analysis Can Support Underwriting by Claudine Modlin, FCAS, MAAA
How Advanced Pricing Analysis Can Support Underwriting by Claudine Modlin, FCAS, MAAA September 21, 2014 2014 Towers Watson. All rights reserved. 3 What Is Predictive Modeling Predictive modeling uses
More informationUPDATED IAA EDUCATION SYLLABUS
II. UPDATED IAA EDUCATION SYLLABUS A. Supporting Learning Areas 1. STATISTICS Aim: To enable students to apply core statistical techniques to actuarial applications in insurance, pensions and emerging
More informationMeasuring Policyholder Behavior in Variable Annuity Contracts
Insights September 2010 Measuring Policyholder Behavior in Variable Annuity Contracts Is Predictive Modeling the Answer? by David J. Weinsier and Guillaume Briere-Giroux Life insurers that write variable
More information2017 Predictive Analytics Symposium
2017 Predictive Analytics Symposium Session 29, Predictive Analytics for Inforce Management Moderator: Rohan Noel Alahakone, ASA, MAAA Presenters: Jenny Jin, FSA, MAAA Assaf Mizan Martin Snow, FSA, MAAA
More informationForecasting & Futurism
Article from: Forecasting & Futurism December 2013 Issue 8 PREDICTIVE MODELING IN INSURANCE Modeling Process By Richard Xu In the July 2013 issue of the Forecasting & Futurism Newsletter, we introduced
More informationSession 79 PD, FASB Targeted Improvements and IFRS 17. Moderator: Kyle Baxter Stolarz, FSA, MAAA
Session 79 PD, FASB Targeted Improvements and IFRS 17 Moderator: Kyle Baxter Stolarz, FSA, MAAA Presenters: Steven F. Malerich, FSA, FLMI, MAAA Gavin Thomas Stewart, FSA, MAAA Kyle Baxter Stolarz, FSA,
More informationSession 027 PD - Impact of New Mortality Tables for U.S. Pension Plans. Moderator: Julie A. Curtis, FSA, EA, MAAA
Session 027 PD - Impact of New Mortality Tables for U.S. Pension Plans Moderator: Julie A. Curtis, FSA, EA, MAAA Presenters: Irina Pogrebivsky, FSA, EA Lisa A. Schilling, FSA, EA, FCA, MAAA SOA Antitrust
More informationModeling Private Firm Default: PFirm
Modeling Private Firm Default: PFirm Grigoris Karakoulas Business Analytic Solutions May 30 th, 2002 Outline Problem Statement Modelling Approaches Private Firm Data Mining Model Development Model Evaluation
More information2017 SOA Annual Meeting & Exhibit
2017 SOA Annual Meeting & Exhibit MARC DES ROSIERS, FSA, FCIA Session 101, Methods to Evaluate Retirement Plan Designs October 17, 2017 SOCIETY OF ACTUARIES Antitrust Compliance Guidelines Active participation
More informationSession 110 PD - VM-20 for Senior Management. Moderator: Carrie Lee Kelley, FSA, MAAA
Session 110 PD - VM-20 for Senior Management Moderator: Carrie Lee Kelley, FSA, MAAA Presenters: Arnold A. Dicke, FSA, CERA, MAAA Amy J. Eby, FSA, MAAA Elinor Friedman, FSA, MAAA SOA Antitrust Compliance
More informationAgenda. Current method disadvantages GLM background and advantages Study case analysis Applications. Actuaries Club of the Southwest
watsonwyatt.com Actuaries Club of the Southwest Generalized Linear Modeling for Life Insurers Jean-Felix Huet, FSA November 2, 29 Agenda Current method disadvantages GLM background and advantages Study
More informationSession 161 PD - Best Practices & Considerations for Accelerated Underwriting. Moderator: Donna Christine Megregian, FSA, MAAA
Session 161 PD - Best Practices & Considerations for Accelerated Underwriting Moderator: Donna Christine Megregian, FSA, MAAA Presenters: Gregory A. Brandner, FSA, MAAA Lisa Hollenbeck Renetzky, FSA, MAAA
More informationSession 45 PD, Life Insurance for the Digital Consumer An Actuarial Perspective. Moderator: Craig E. Hanford, FSA, MAAA
Session 45 PD, Life Insurance for the Digital Consumer An Actuarial Perspective Moderator: Craig E. Hanford, FSA, MAAA Presenters: Stephen Abrokwah, ASA, CERA, MAAA Craig E. Hanford, FSA, MAAA Nathan P.
More informationSession 14 PD, The Search for Model Efficiency Through Data Compression. Moderator: Trevor C. Howes, FSA, FCIA, MAAA
Session 14 PD, The Search for Model Efficiency Through Data Compression Moderator: Trevor C. Howes, FSA, FCIA, MAAA Presenters: Dan (Danielle) Li, FSA Andrey Marchenko SOA Antitrust Disclaimer SOA Presentation
More informationSession 024 PD - Life Reinsurance in Bermuda. Moderator: Gokul Sudarsana, FSA, CERA, FCIA
Session 024 PD - Life Reinsurance in Bermuda Moderator: Gokul Sudarsana, FSA, CERA, FCIA Presenters: Manfred Maske Sylvia Martin Oliveira, FSA, MAAA Scott D. Selkirk, FSA, MAAA SOA Antitrust Compliance
More informationLending Club Loan Portfolio Optimization Fred Robson (frobson), Chris Lucas (cflucas)
CS22 Artificial Intelligence Stanford University Autumn 26-27 Lending Club Loan Portfolio Optimization Fred Robson (frobson), Chris Lucas (cflucas) Overview Lending Club is an online peer-to-peer lending
More informationThe analysis of credit scoring models Case Study Transilvania Bank
The analysis of credit scoring models Case Study Transilvania Bank Author: Alexandra Costina Mahika Introduction Lending institutions industry has grown rapidly over the past 50 years, so the number of
More informationUsing Internal Data for a Competitive Advantage. Isaac Mashitz Group Chief Pricing Actuary AmTrust Financial
Using Internal Data for a Competitive Advantage Isaac Mashitz Group Chief Pricing Actuary AmTrust Financial Using Internal Data for a Competitive Advantage: Applications 2 Using Internal Data for a Competitive
More informationXiaojie (Jane) Wang, FSA, CERA Predictive Analytics Lead Swiss Re Armonk, NY
PREDICTIVE ANALYTICS AND FUTURISM (Vote for up to three candidates) Xiaojie (Jane) Wang Wai (Ryan) Tse Michael Niemerg Jeff Huddleston Garfield L. Francis Bryon Robidoux Kathleen Wang Xiaojie (Jane) Wang,
More informationArticle from. Predictive Analytics and Futurism. June 2017 Issue 15
Article from Predictive Analytics and Futurism June 2017 Issue 15 Using Predictive Modeling to Risk- Adjust Primary Care Panel Sizes By Anders Larson Most health actuaries are familiar with the concept
More informationModerator: Robert T Eaton FSA,MAAA. Presenters: Bryn T Douds FSA,MAAA Robert T Eaton FSA,MAAA Robert K Yee FSA,MAAA
Session 27PD: The Impact of FASB Targeted Improvements on Health Products Moderator: Robert T Eaton FSA,MAAA Presenters: Bryn T Douds FSA,MAAA Robert T Eaton FSA,MAAA Robert K Yee FSA,MAAA SOA Antitrust
More informationMarket Insights. 1. Rice Warner Research Reports. Superannuation and Investments Reports. 1.1 Superannuation Market Projections
Market Insights 1. Rice Warner Research Reports This product list sets out a description for all regular research reports issued by Rice Warner. In addition, there are one-off reports such as, Member Direct
More informationSAS Data Mining & Neural Network as powerful and efficient tools for customer oriented pricing and target marketing in deregulated insurance markets
SAS Data Mining & Neural Network as powerful and efficient tools for customer oriented pricing and target marketing in deregulated insurance markets Stefan Lecher, Actuary Personal Lines, Zurich Switzerland
More informationPredictive Analytics for Risk Management
Equity-Based Insurance Guarantees Conference Nov. 6-7, 2017 Baltimore, MD Predictive Analytics for Risk Management Jenny Jin Sponsored by Predictive Analytics for Risk Management Applications of predictive
More informationModerator: Donna Christine Megregian, FSA, MAAA
Session 46 PD, Newly Proposed ASOPs: Pricing, Modeling and Setting Assumptions Moderator: Donna Christine Megregian, FSA, MAAA Presenters: Donna Christine Megregian, FSA, MAAA James A. Miles, FSA, MAAA
More informationSession 102 PD - Impact of VM-20 on Life Insurance Pricing. Moderator: Trevor D. Huseman, FSA, MAAA
Session 102 PD - Impact of VM-20 on Life Insurance Pricing Moderator: Trevor D. Huseman, FSA, MAAA Presenters: Carrie Lee Kelley, FSA, MAAA William Gus Mehilos, FSA, MAAA SOA Antitrust Compliance Guidelines
More informationArticle from The Modeling Platform. November 2017 Issue 6
Article from The Modeling Platform November 2017 Issue 6 Actuarial Model Component Design By William Cember and Jeffrey Yoon As managers of risk, most actuaries are tasked with answering questions about
More informationPredictive modeling developments: US Market. Dr. Brian Ivanovic Insurance Medicine Summit 2017
Predictive modeling developments: US Market Dr. Brian Ivanovic Agenda Origins of predictive models in L&H business Approaches to risk scoring State of the evidence on mortality experience and risk scores
More informationU.S. Multiemployer Pension Plan Contribution Indices
U.S. Multiemployer Pension Plan Contribution Indices By Lisa Schilling, FSA, EA, FCA, MAAA, and Patrick Wiese, ASA January 2018 Introduction and Executive Summary Funding multiemployer pension plans involves
More informationMortality Table Update on the 2015 VBT/CSO
Mortality Table Update on the 2015 VBT/CSO Joint American Academy of Actuaries Life Experience Committee and Society of Actuaries Preferred Mortality Oversight Group Actuaries Club of the Southwest November
More informationIn-force portfolios are a valuable but often neglected asset that
How Can Life Insurers Improve the Performance of Their In-Force Portfolio? A Systematic Approach Covering All Drivers Is Essential By Andrew Harley and Ian Farr This article is reprinted with permission
More informationEnterprise Risk Management (ERM) Module 3.0 (CERA/FSA)
FSA QFI, INDIVIDUAL LIFE AND ANNUITIES, RETIRMEMENT BENEFITS, GENERAL INSURANCE TRACKS CERA ALL TRACKS Enterprise Risk Management (ERM) Module 3.0 (CERA/FSA) SECTION 1: MODULE OVERVIEW Quick! Try to name
More informationSOA Exam Update. Mark Cawood School of Mathematical and Statistical Sciences Clemson University
SOA Exam Update Mark Cawood School of Mathematical and Statistical Sciences Clemson University Southeastern Actuaries Conference Annual Meeting November 15, 2018 History of ASA s Curriculum Changes The
More informationCalculating the Probabilities of Member Engagement
Calculating the Probabilities of Member Engagement by Larry J. Seibert, Ph.D. Binary logistic regression is a regression technique that is used to calculate the probability of an outcome when there are
More informationSession 73 PD, Predictive Modeling for the Marketing Actuary. Moderator: Maria Patricia Marcelo Arellano, FSA, CERA, MAAA
Session 73 PD, Predictive Modeling for the Marketing Actuary Moderator: Maria Patricia Marcelo Arellano, FSA, CERA, MAAA Presenters: Andy Ferris, FSA, FCA, MAAA Sarah R. Hinchey, FSA, CERA Patrick Sugent
More informationModerator: Sean Michael Hayward FSA,MAAA. Presenters: Joshua S Y Chee FSA Sean Michael Hayward FSA,MAAA Michael Porcelli FSA,MAAA
SOA Antitrust Disclaimer SOA Presentation Disclaimer Session 63PD: Modeling Function: To Centralize or Not To Centralize? Moderator: Sean Michael Hayward FSA,MAAA Presenters: Joshua S Y Chee FSA Sean Michael
More informationDeveloping WOE Binned Scorecards for Predicting LGD
Developing WOE Binned Scorecards for Predicting LGD Naeem Siddiqi Global Product Manager Banking Analytics Solutions SAS Institute Anthony Van Berkel Senior Manager Risk Modeling and Analytics BMO Financial
More informationSession 174 PD, Nested Stochastic Modeling Research. Moderator: Anthony Dardis, FSA, CERA, FIA, MAAA. Presenters: Runhuan Feng, FSA, CERA
Session 174 PD, Nested Stochastic Modeling Research Moderator: Anthony Dardis, FSA, CERA, FIA, MAAA Presenters: Anthony Dardis, FSA, CERA, FIA, MAAA Runhuan Feng, FSA, CERA SOA Antitrust Disclaimer SOA
More informationData Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing C. Olivia Rud, President, OptiMine Consulting, West Chester, PA ABSTRACT Data Mining is a new term for the
More informationAcademy Presentation to NAIC ORSA Implementation (E) Subgroup
Academy Presentation to NAIC ORSA Implementation (E) Subgroup Tricia Matson, MAAA, FSA Chairperson, Enterprise Risk Management (ERM) and Own Risk and Solvency Assessment (ORSA) Committee August 10, 2016
More informationArticle from. The Actuary. October/November 2015 Issue 5
Article from The Actuary October/November 2015 Issue 5 FEATURE PREDICTIVE ANALYTICS THE USE OF PREDICTIVE ANALYTICS IN THE DEVELOPMENT OF EXPERIENCE STUDIES Recently, predictive analytics has drawn a lot
More informationReserving in the Pressure Cooker (General Insurance TORP Working Party) 18 May William Diffey Laura Hobern Asif John
Reserving in the Pressure Cooker (General Insurance TORP Working Party) 18 May 2018 William Diffey Laura Hobern Asif John Disclaimer The views expressed in this presentation are those of the presenter(s)
More informationModerator: Stefanie J Porta ASA,MAAA. Presenters: Ingrid H Guttin FSA Scott D Haglund FSA,MAAA Scott D Houghton FSA,MAAA
SOA Antitrust Disclaimer SOA Presentation Disclaimer Session 30PD: Relationships Between Auditors and Valuation Actuary Moderator: Stefanie J Porta ASA,MAAA Presenters: Ingrid H Guttin FSA Scott D Haglund
More informationPractical Predictive Analytics Seminar May 18, 2016 Omni Nashville Hotel Nashville, TN
The Predictive Analytics & Futurism Section Presents Practical Predictive Analytics Seminar May 18, 2016 Omni Nashville Hotel Nashville, TN Presenters: Eileen Sheila Burns, FSA, MAAA Jean Marc Fix, FSA,
More informationMortality Table Development 2014 VBT Primary Tables. Table of Contents
8/18/ Mortality Table Development VBT Primary Tables and Society Joint Project Oversight Group Mary Bahna-Nolan, MAAA, FSA, CERA Chairperson, Life Experience Subcommittee August 14, 2008 SOA NAIC Life
More informationRED 2.1 & 4.2: Quantifying Risk Exposure for ORSA. Moderator: Presenters: Lesley R. Bosniack, CERA, FCAS, MAAA
RED 2.1 & 4.2: Quantifying Risk Exposure for ORSA Moderator: Lesley R. Bosniack, CERA, FCAS, MAAA Presenters: Lesley R. Bosniack, CERA, FCAS, MAAA William Robert Wilkins, ASA, CERA, FCAS, MAAA SOA Antitrust
More informationMarket Variables and Financial Distress. Giovanni Fernandez Stetson University
Market Variables and Financial Distress Giovanni Fernandez Stetson University In this paper, I investigate the predictive ability of market variables in correctly predicting and distinguishing going concern
More informationSession 188 IF - Inforce Management: Understanding and Increasing Its Value. Moderator: Donna Christine Megregian, FSA, MAAA
Session 188 IF - Inforce Management: Understanding and Increasing Its Value Moderator: Donna Christine Megregian, FSA, MAAA Presenters: Andy Ferris, FSA, FCA, MAAA Stephanie J. Koch, FSA, MAAA Jennifer
More informationSession 37 PD, Company Taxation Update. Moderator: Rob E. Baldwin, FSA, CERA, MAAA. Presenters: Jean Baxley, JD, LLM Sheryl Flum
Session 37 PD, Company Taxation Update Moderator: Rob E. Baldwin, FSA, CERA, MAAA Presenters: Jean Baxley, JD, LLM Sheryl Flum SOA Antitrust Disclaimer SOA Presentation Disclaimer 2018 SOA Life & Annuity
More informationMichael Clive Gibson Resume
Nationality: Australian/British Mobile: +44 (0) 7766642218 Michael Clive Gibson Resume www.gibsonactuarial.com Email: michael_c_gibson@hotmail.com Key Strengths Strong technical skills excellent understanding
More informationSession 70 PD, Model Efficiency - Part II. Moderator: Anthony Dardis, FSA, CERA, FIA, MAAA
Session 70 PD, Model Efficiency - Part II Moderator: Anthony Dardis, FSA, CERA, FIA, MAAA Presenters: Anthony Dardis, FSA, CERA, FIA, MAAA Ronald J. Harasym, FSA, CERA, FCIA, MAAA Andrew Ching Ng, FSA,
More informationSession 1B: Introduciton to Predictive Analytics. Moderator: Dariush A. Akhtari, FSA, MAAA, FCIA
Session 1B: Introduciton to Predictive Analytics Moderator: Dariush A. Akhtari, FSA, MAAA, FCIA Presenters: Mark William Birdsall, FSA, MAAA, FCA Matthew Forrest Gabriel, FSA, MAAA SOA Antitrust Disclaimer
More informationFE670 Algorithmic Trading Strategies. Stevens Institute of Technology
FE670 Algorithmic Trading Strategies Lecture 4. Cross-Sectional Models and Trading Strategies Steve Yang Stevens Institute of Technology 09/26/2013 Outline 1 Cross-Sectional Methods for Evaluation of Factor
More informationThe Crystal Ball of Safety
The Crystal Ball of Safety Dustin England Corporate Vice President, Safety/Compliance CR England Chris Orban Director, Technical Services FleetRisk Advisors 1 Baldwin & Lyons May Trucking Co. Spectrum
More informationHow Can YOU Use it? Artificial Intelligence for Actuaries. SOA Annual Meeting, Gaurav Gupta. Session 058PD
Artificial Intelligence for Actuaries How Can YOU Use it? SOA Annual Meeting, 2018 Session 058PD Gaurav Gupta Founder & CEO ggupta@quaerainsights.com Audience Poll What is my level of AI understanding?
More informationA Statistical Analysis to Predict Financial Distress
J. Service Science & Management, 010, 3, 309-335 doi:10.436/jssm.010.33038 Published Online September 010 (http://www.scirp.org/journal/jssm) 309 Nicolas Emanuel Monti, Roberto Mariano Garcia Department
More informationSession 80 PD, Model Validation Framework and Best Practices. Moderator: Joshua David Dobiac, JD, MS, CAIA
Session 80 PD, Model Validation Framework and Best Practices Moderator: Joshua David Dobiac, JD, MS, CAIA Presenters: James Stuart McClure, FSA, MAAA Zohair A. Motiwalla, FSA, MAAA SOA Antitrust Disclaimer
More informationSession 155 PD, Guaranteed Issue, Simplified Issue and Preneed Update. Moderator: Cynthia MacDonald, FSA, MAAA
Session 155 PD, Guaranteed Issue, Simplified Issue and Preneed Update Moderator: Cynthia MacDonald, FSA, MAAA Presenters: David B. Atkinson, FSA Jeffrey E. Johnson, ASA, MAAA Lloyd M. Spencer Jr., FSA,
More informationThe Big Change. 26th Annual Insurance Conference Tuesday, November 28, kpmg.ca/insuranceconference2017
The Big Change 26th Annual Insurance Conference Tuesday, November 28, 2017 kpmg.ca/insuranceconference2017 KPMG IFRS 17 Global Results Haven't started yet 7% Which IFRS 17 project phase is your company
More informationSession 51 PD, VM31 - PBR Actuarial Report - Which ASOPs Matter? Moderator: Leonard Mangini, FSA, FALU, FRM, MAAA
SOA Antitrust Disclaimer SOA Presentation Disclaimer Session 51 PD, VM31 - PBR Actuarial Report - Which ASOPs Matter? Moderator: Leonard Mangini, FSA, FALU, FRM, MAAA Presenters: Kerry A. Krantz, FSA,
More informationHow Can Life Insurers Improve the Performance of Their In-Force Portfolios?
Third in a series of four How Can Life Insurers Improve the Performance of Their In-Force Portfolios? A Systematic Approach Covering All Drivers Is Essential By Andrew Harley and Ian Farr In-force portfolios
More informationBetter decision making under uncertain conditions using Monte Carlo Simulation
IBM Software Business Analytics IBM SPSS Statistics Better decision making under uncertain conditions using Monte Carlo Simulation Monte Carlo simulation and risk analysis techniques in IBM SPSS Statistics
More information