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STAY TUNED! If you are anticipating additional search filters by attribute and level to align with the CAS Capability Model, it is coming later this Summer. As the CAS begins to code recorded sessions by specific attributes and levels (starting with the 2023 Annual Meeting), these will be tagged in the CAS database of presentations going forward and should be searchable.
But you may use the Capability Model now to help you identify topics. For example, if you want to move up one level under the content area “Functional Expertise,” you may search topics in the particular functional area to expand your knowledge.
Recorded content is searchable by Capability Model attribute and level in the CAS Online Library.
CS9: Creating Solutions through Location-based Analytics
Given accurate, complete and relevant data, any statistician, predictive modeler or data scientist can create a solid predictive model. This is very true for location based data that can be used primarily within Property Insurance products. Once you've proven the model is beneficial mathematically, the real challenge becomes establishing buy-in at all levels, and ultimately implementing within the appropriate workflows. To have a successful predictive model solution, one must address the business problem holistically rather than strictly as an exercise in numbers. This session will explore how modeling, analytics and actuarial can come together to create a complete solution rather than just a model.
Source:
2017 Underwriting Collaboration Seminar
Type:
Concurrent Session
Panelists:
Howard Kunst, Amy Gromowski
CS5: IoT for Insurance – Demystifying the Role of Telematics
The increased integration of 'smart' devices through internet of things (IoT) technologies are quickly changing the way we travel, the way we work, and way we live. Almost every day we hear of the next innovation in connected vehicles, smart home devices, and health-focused wearables making their way to the B2B and B2C market. As product designers and manufacturers identify secure, innovative ways to capture and use the data from connected devices and infrastructure, there exists a mature marketplace ripe for innovation eager to put that same data to use in insurance products.
The insurance industry is a fertile ground for early and innovative adoption of IoT technology. Personal and commercial property/casualty (P&C) insurance carriers are looking to propagate this business model into other products areas through data collection on connected homes, commercial buildings, machinery, vehicles, and even their human workforce. More importantly, they see these data sources as a channel to provide value-add services to win new customers and retain existing ones. And they're doing so for all lines of business including (but not limited to) auto, property, commercial, and life insurance. These data streams can be incorporated into risk models to price products more accurately - meaning better rates for those homeowners, drivers, and operators who use exercise risk-averse behaviors regularly.
Now is the time for 'smart' devices to drive 'smart' insurance products. Learn more about this innovative space, challenges presented in bringing the data and products to market, and best practices for defining a path to 'smarter' insurance.
Source:
2017 Underwriting Collaboration Seminar
Type:
Concurrent Session
Panelists:
Geoffrey Werner, Zack Schmiesing, Lamont Boyd
CS1: The Evolving Dynamics of Cyber Risk: What Behavioral Economics Can Teach Us About Cyber Liability and Related Emerging Risks
Cyber security risk is arguably the most visible emerging risk facing the property and casualty insurance
industry. Further, because it is constantly evolving, data captured just yesterday may quickly become
irrelevant. Behavioral Economics can teach us what 'blind spots' we may have towards this emerging
risk. We can only alleviate what we can perceive! Join Ben Goodman, CRISC, adjunct faculty member at
Drexel University, LeBow College of Business, and CEO of 4A Security & Compliance, and Michael
Solomon, FCAS, MAAA, CERA for a lively, multidisciplinary discussion on what you need to know in this
rapidly changing area.
Source:
2017 Underwriting Collaboration Seminar
Type:
Concurrent Session
Panelists:
Michael Solomon, Ben Goodman, Steven Zielke
GS3: Predictive Modeling - Psychology of an Underwriter
The emergence of data and predictive modeling has changed the way that insurance policies are priced and underwritten. There is a shift from seeing all policies and individually underwriting each to only seeing a smaller sample set and underwriting on a by exception basis. This session will review some of the natural human biases that both underwriters and actuaries need to be aware of to ensure that decision making remains sound in light of the changing environment. It is also touch on how to most appropriately introduce new models to underwriters to ensure greater acceptance and successful implementation.
Source:
2017 Underwriting Collaboration Seminar
Type:
General Session
Panelists:
Keith Holler, Michael Neubauer, Sarah Shine, Matt Walkowiak
GS2: How to Help Underwriters Make Decisions - Workflow and Process
With the evolving analytics and technology, the underwriter's job is constantly changing. Depending on the line of business, this can mean that the underwriter's work flow and processes have changed dramatically. Instead of individual underwriting, many have been asked become portfolio underwriters relying heavily on predictive models and additional analytics to help with underwriting. Alternatively, some companies have continued to have underwriters subjectively add their perspective in addition to the predictive models. This session will discuss the challenges with making sure that the underwriter is adding value, not using variables which are already contemplated in the models. Additionally, models become less reliable at some point and the underwriter must then use the variables that they have expressly been prohibited from using to underwrite these pieces of business. This session involve individuals who have led this transformation and designed the processes necessary to be successful.
Source:
2017 Underwriting Collaboration Seminar
Type:
General Session
Panelists:
James Merz, Gary Ciardiello, Jana Ringwald, Greg Massey
GS1: Actuaries and Underwriters – The Experts
Kick off the seminar with a lively, interactive town-hall discussion with leaders from both the CAS and the Institutes. The leaders will discuss the partnership between the CAS and the Institutes as well as the CAS Institute. Bring your thoughts and opinions on the direction of this partnership and how actuaries and underwriters can collaborate more effectively. Additional topics to be added through a survey sent to all registered attendees.
Source:
2017 Underwriting Collaboration Seminar
Type:
General Session
Panelists:
Brian Brown, Rob Galbraith, Carl Ashenbrenner, Peter Miller
Data Visualization: GIS for Actuaries
Pre-registration is required for this workshop.
This workshop is intended to introduce actuaries to the wonderful world of geographic information science (GIS). GIS can be used to visualize insurance data at a range of scales all the way down to the policy or location level. Additional applications include appending third-party data, enhancing analysis using geographic relationships, and the creation of customized or granular rating territories.
The first part will be a lecture on GIS basics such as data types, geocoding addresses, locating and using third-party data, cartographic representation, and simple geoprocessing workflows.
The second half will be a hands-on tutorial taught in ArcGIS for Desktop. Instructions on software and data installation will be provided to all participants that pre-register.
Source:
2017 Ratemaking and Product Management Seminar
Type:
Workshop
Panelists:
Garrett Bradford
Basic Predictive Modeling
Pre-registration is required for this workshop.
This popular, hands-on, interactive predictive modeling workshop has been offered at the RPM seminar now for several years. It will be conducted exclusively in the R statistical computing language, which is widely adopted by statisticians and data scientists.
The course will provide a refresher of regression theory before proceeding to a variety of practical modeling applications and case studies. The focus will be on generalized linear models (GLMs) — their specification, interpretation, and validation. A variety of distributions will be covered, including classical, Poisson, logistic, gamma, and Tweedie. Other topics will be discussed and illustrated as time permits. All datasets will be distributed to attendees prior to the seminar.
Important note: familiarity with R is assumed. An "introduction to R" presentation will be distributed before the seminar which will contain a primer on basic features and statistical functions, as well as installation instructions, that will enable beginners to get up to speed. While R beginners are encouraged to attend, they should make some attempt to become comfortable with the language prior to the workshop. This workshop has been designed for beginning predictive modelers, but more experienced modelers seeking a refresher or a deeper working knowledge of R have attended past workshops and expressed satisfaction with the coverage of topics.
Source:
2017 Ratemaking and Product Management Seminar
Type:
Workshop
Panelists:
Mark Goldburd
Overview and Practical Application Machine Learning Methods in Pricing – Part 2
The term “machine learning” covers a range of methods that can be powerful, with very practical benefits, in pricing and other insurance applications. Such methods can aid in further improving GLM results or more broadly bring valuable insights to complex problems. There can also be a number of practical challenges in using these methods effectively. This is the second of two sessions reviewing a range of commonly used methods and illustrating different ways they are being applied in insurance. These sessions will focus on the high-level mechanics of each method and the benefits/challenges of their application – as opposed to the underlying technical details. Part 1 will focus on approaches such as penalized regression and other approaches more closely related to GLMs. Part 2 (this session) will focus on classification-based approaches, including trees, random forests, and GBMs. Each part can be attended without the other.
Source:
2017 Ratemaking and Product Management Seminar
Type:
Concurrent Session
Panelists:
Claudine Modlin, Duncan Anderson, Graham Wright
2017 NA Survey Results - Machine Learning and Advanced Analytics Practices
We live in a world surrounded by analytics. It is everywhere. Sports teams use it to get an edge on the competition, Netflix uses it to predict which shows you are most likely to like and Amazon uses it to introduce you to additional products you didn’t even know you wanted. The insurance world is no different. Machine learning and advanced analytics techniques are being used all across the industry for different parts of the pricing process. In this session we will review the interesting findings of a survey conducted around the extent of usage of machine learning and predictive analytics practices among insurance pricing practitioners. Besides learning about the current status of analytics usage, we learned what future insurers are seeing for analytics in the service of pricing. This session will also include live polling to dig deeper into some responses.
Source:
2017 Ratemaking and Product Management Seminar
Type:
Concurrent Session
Panelists:
Drew Lawyer, Dion Oryzak, Olivier Tessier
Ensembles and Combining Models
Ensembles are powerful analytical methods used commonly in the wider Predictive Analytics community outside of Insurance. We’ll describe the rationale and explain the effectiveness of Ensembles in general, as well as the basic approaches of bagging and boosting Ensembles of Trees. Advantages of Ensembles on insurance data will be shown and the issues surrounding complex models discussed. Finally, strategies for combining linear regression and ensemble models will be explored.
Source:
2017 Ratemaking and Product Management Seminar
Type:
Concurrent Session
Panelists:
Christopher Cooksey, Douglas Noe
Overview and Practical Application Machine Learning Methods in Pricing – Part 1
The term “machine learning” covers a range of methods that can be powerful, with very practical benefits, in pricing and other insurance applications. Such methods can aid in further improving GLM results or more broadly bring valuable insights to complex problems. There can also be a number of practical challenges in using these methods effectively. This is the first of two sessions reviewing a range of commonly used methods and illustrating different ways they are being applied in insurance. These sessions will focus on the high-level mechanics of each method and the benefits/challenges of their application – as opposed to the underlying technical details. Part 1 will focus on approaches such as penalized regression and other approaches more closely related to GLMs. Part 2 will focus on classification-based approaches, including trees, random forests, and GBMs. Each part can be attended without the other.
Source:
2017 Ratemaking and Product Management Seminar
Type:
Concurrent Session
Panelists:
Claudine Modlin, Duncan Anderson, Graham Wright
Comparing Machine Learning and Conventional Statistical Techniques In Claims Models
Machine learning methods are becoming popular in insurance modeling applications. In the session, the panelists will discuss a few machine learning methods (gradient boosting, random forests, neural network, LASSO, Elastic Net, etc.) and compare them with conventional regression methods (GLM, generalized mixed models, etc.) in the context of claims triage models. A case study will illustrate the pros and cons of those techniques.
Source:
2017 Ratemaking and Product Management Seminar
Type:
Concurrent Session
Panelists:
Cheng-Sheng Wu, Luyang Fu, Joshua Brady, Douglas Noe
Cyber Security
Eric O'Neill will discuss Cybersecurity in the Age of Breaches and Espionage (political and corporate). Mr. O'Neill will also provide in-depth coverage on how the insurance industry (and actuarial roles) are impacted by Cybersecurity policy, practices and some tips for prevention.
Source:
2017 Ratemaking and Product Management Seminar
Type:
Featured Speaker
Panelists:
Amy Juknelis, Eric O'Neill
Session 8B: ERM Call for Papers Award Winners
The 2017 ERM Symposium will present research from the academic community. This session focused on research will be offered where authors of the papers will present their research. Questions and comments from the audience will be encouraged to stimulate discussion.
Source:
2017 Enterprise Risk Management Symposium
Type:
Concurrent Session
Moderators:
James Ramenda, FSA, CERA
Panelists:
Steven Lane Craighead, ASA MAAA, CERA; Ben Goodman; B. John Manistre, FSA, CERA, FCIA, MAAA
Session 8A: Risk Appetite in Practice
This session will explore how to bridge the company's values, mission and a unique corporate and risk culture with its risk attitude, tolerance and appetite, investigate the link between corporate strategy and risk appetite and the link between risk appetite/tolerance/limits with specific strategic objectives. Practical consideration around time horizon, monitoring and recalibration will be addressed.
Source:
2017 Enterprise Risk Management Symposium
Type:
Concurrent Session
Moderators:
Anthony Dardis, FSA, CERA, FIA, MAAA
Panelists:
Anthony Dardis, FSA, CERA, FIA, MAAA; Damon D. Levine
Session 7C: Senior Risk Manager Interactive Forum (Part II)
Participants in the Forum will be organized into groups of six for an off-the-record discussion on a particular topic. Every 15 minutes, participants will circulate to a new group. Prior to the symposium, registrants for the forum will be surveyed to determine topics of greatest interest. Participants will be able to choose the discussion topics they participate in.
Attendees will build an awareness of how others are addressing mutual challenges, including struggles and successes. The forum will help attendees build a network of risk managers with a variety of experiences and views. Design of the Forum is based on a very popular session at the Valuation Actuary Symposium.
Source:
2017 Enterprise Risk Management Symposium
Type:
Concurrent Session
Moderators:
Mark W. Griffin, FSA, CERA
Session 7B: Developing Key Risk Indicators
What gets measured gets managed. This session will explore the attribute of a good metric and what makes it actionable.
Source:
2017 Enterprise Risk Management Symposium
Type:
Concurrent Session
Moderators:
Siew Chen Ow, FSA, CERA, MAAA
Panelists:
Amy Bridges; Marcus Weare
Session 7A: Capital Adequacy Assessment: Past, Present and Future
Capital adequacy assessment existed prior to the introduction of ORSA but this regulation triggered evolution. This session will present a panel of experts that will present their view of the capital adequacy assessment and will take numerous questions from the audience to create a dialogue between attendees and experts.
Source:
2017 Enterprise Risk Management Symposium
Type:
Concurrent Session
Moderators:
Matthew John Stahl, ASA, CERA, MAAA
Panelists:
David N. Ingram, FSA, CERA, MAAA; James Gillard; Danny Saenz
Session 6C: Senior Risk Manager Interactive Forum (Part I)
Participants in the Forum will be organized into groups of six for an off-the-record discussion on a particular topic. Every 15 minutes, participants will circulate to a new group. Prior to the symposium, registrants for the forum will be surveyed to determine topics of greatest interest. Participants will be able to choose the discussion topics they participate in.
Attendees will build an awareness of how others are addressing mutual challenges, including struggles and successes. The forum will help attendees build a network of risk managers with a variety of experiences and views. Design of the Forum is based on a very popular session at the Valuation Actuary Symposium.
Source:
2017 Enterprise Risk Management Symposium
Type:
Concurrent Session
Moderators:
Mark W. Griffin, FSA, CERA
Session 6B: Quantitative Economic Capital Calculation: Property & Casualty
This technical session will discuss a number of approaches to economic capital calculation. This will include example case studies of how proxy techniques can be used to accelerate the calculations.
Source:
2017 Enterprise Risk Management Symposium
Type:
Concurrent Session
Moderators:
Daniel B. Finn, FCAS
Panelists:
Daniel B. Finn, FCAS; Matthew Peters
Session 6A: Cyber Security Risks from an ERM and Insurance Market Perspective
This session will provide an overview of the cyber-security risks from an ERM and insurance market perspective: "Evolving global cyber security risks; managing cyber-security risk as a material operational risk in an ERM framework; understanding the current cyber insurance market, insurance pricing and underwriting process; and building programs that improve your own ERM defense, as well as allow you to take advantage of this new insurance field.
Source:
2017 Enterprise Risk Management Symposium
Type:
Concurrent Session
Moderators:
Brian Joseph O'Neill FSA, CERA, MAAA
Panelists:
Ben Goodman; Michael Ian Solomon, FCAS, CERA
Session 5C: Model Governance: What Could Possibly Go Wrong? (Part II)
Participants in this session will work through a hypothetical insurance company 'case study' and interactive role-play activities to gain a better understanding of the importance of model risk governance. This presentation will be split into two separate sessions. Part one will focus on what could go wrong in the absence of sound model risk governance practices and introduce a model risk management framework for insurers. Part two will focus on model validation techniques and tailored approaches for insurers. Participants are welcome to join either or both sessions. Attendance will be limited to facilitate discussion
Source:
2017 Enterprise Risk Management Symposium
Type:
Concurrent Session
Moderators:
Dwayne Allen Husbands, FSA, MAAA
Panelists:
James Russell Collingwood, ASA, MAAA; David Paul, FCAS, MAAA; Chad R. Runchey, FSA, MAAA
Session 5B: Developments in the Use of Proxy Generators for EC Calculations and Projection: Life Insurance
This technical session will discuss a number of approaches to economic capital calculation and projection for life insurance. This will include example case studies of how proxy techniques can be used to accelerate the calculations.
Source:
2017 Enterprise Risk Management Symposium
Type:
Concurrent Session
Moderators:
Dariush A. Akhtari, FSA, MAAA, FCIA
Panelists:
Aubrey Clayton
Session 5A: ERM Metrics That Answer "How Likely Are We to Achieve Plan?
Many ERM programs provide an array of quantitative metrics on extreme downside exposure, mostly related to financial and insurance risks. Unfortunately, this fails to engage key stakeholders, because it does not relate to their day-to-day responsibilities, which mostly involve overcoming strategic and operational obstacles to achieving Plan goals. In this session, we present a methodology and walk step-by-step through a case study implementation illustrating how to: (a) quantify all risks, including strategic and operational risks; (b) quantify both upside and downside volatility, by impact to Plan goals; and (c) connect ERM metrics to tangible goals about which the board and executives care most, such as the likelihood of achieving/exceeding Plan goals.
Source:
2017 Enterprise Risk Management Symposium
Type:
Concurrent Session
Moderators:
Shannon M. Patershuk, FSA, CERA, FCIA
Panelists:
David Michael Rasezja, FSA, MAAA; Sim Segal, FSA, CERA
