Predictive Analytics World for Financial Las Vegas 2019
June 16-20, 2019 – Caesars Palace, Las Vegas
SVP of Claim Analytics Product Management
Gary Anderberg has worked in developing predictive analytic applications for workers' compensation insurance since 2007. He is a recognized expert in the use of PA outputs for guiding the handling of complex claims to drive improved claim outcomes. He is the "godfather" of the Waypoint system and its key role in improving overall decision making and the more effective use of claim resources at Gallagher-Bassett. He will speak to the business case for a system like Waypoint and the corporate cultural and practice issues involved in socializing potentially complex PA system outputs with deeply entrenched work patterns at the end user level. He knows first-hand how the most brilliant PA applications can founder when output and practice cultures clash.
Gary Anderberg is speaker of the following session:
Former Senior Director, California State Compensation Insurance Fund, now Founder and Principal, Analytics Ark Consulting
Mr Arora has 18+ years of experience in data and analytics function with focus on financial service and insurance industry. He led a variety of roles as leader of data products, reporting, analytics and predictive modeling services. With a deeper hands on predictive modeling experience, passion for mathematics and statistics, and knowledge of wide variety of software, Mr. Arora is an expert in founding, growing and transforming enterprise analytic capabilities.
Munish Arora is speaker of the following session:
Dyann Daley MD
Founder and CEO
Dr. Dyann Daley, MD, is an experienced pediatric anesthesiologist and child maltreatment prevention executive, specializing in location-based predictive modeling, systems thinking, and development of practical solutions for community-influenced children’s issues.
Dr. Daley founded and was the executive director of Cook Children’s Center for Prevention of Child Maltreatment in Fort Worth, Texas where she demonstrated the effectiveness of place-based predictive analytics for child maltreatment using spatial risk modeling. She went on to found Predict Align Prevent, a national nonprofit advancing geospatial machine learning predictions in child welfare, strategic alignment of prevention resources, and implementation of accountable prevention programs to prevent child maltreatment before it happens. Her organization is committed to open science for social good.
Dyann Daley MD is speaker of the following session:
Data Modeling Director
Brian Duke is a Director of Fraud and Identity Solutions at Experian Decision Analytics and has 12 patents related to modeling enterprise data either issued or pending. He provides technical leadership for data scientists and analysts who bring innovative identity protection and fraud detection products and custom analytical solutions to the North American market. Brian is expert in models and business strategies that integrate a large variety of data assets -- spanning credit and noncredit data, biometrics, behavioral metrics, email and phone intelligence, remote document verification, the dark web and more. He received both his Bachelor's degree in Mathematics and his Master's degree in Statistics from the University of California, San Diego and continues to reside in San Diego.
Brian Duke is speaker of the following session:
Chenyu (Jim) Gao
Advisory Manager, Machine Learning/Artificial Intelligence Accelerator
Jim is a consultant with many years of industrial experience, and currently is an Advisory manager from PricewaterhouseCooper (PwC), serving cross-sector, cross-Industry analytics practice to deliver statistical, machine learning, artificial intelligence consulting and solutions. He played different important roles in financial services, healthcare, hospitality and entertainment sectors which span across operations, marketing, IT and risk, etc. He has background in various machine learning algorithms and multiple AI/big data applications.
Throughout the past few years, Jim's experience includes:
- Built credit risk models to predict customer likelihood of default and revenue impact for fortune 100 fintech clients
- Developed marketing response model (to increase response rate) and revenue model (to identify 'profitable' customers) for a highly reputable marketing leader
- Analyzed Customer Elasticity to promotional offers and advised effective campaign strategy for a world-prestigious casino resort
Jim holds his master degree in Applied Statistics from Cornell University.
Chenyu (Jim) Gao is speaker of the following session:
Keith Higdon serves as President of ESIS, Inc., with overall management responsibility for this business. He is based in Chicago.
ESIS is one of the industry’s oldest and largest risk management services companies, providing claim and risk management services to a wide variety of commercial clients in the U.S. and globally. ESIS maintains a sharp focus on helping its clients manage their total cost of loss, offering comprehensive and flexible programs and innovative approaches to claims administration. ESIS is committed to achieving measurable results through consistently superior execution, and employing data analytic and predictive modelling capabilities to track progress.
Previously, Mr. Higdon served as Senior Vice President of Partnership Services for ESIS where he oversaw the management and development of client partnerships across all ESIS lines of business. In addition, he has accountability for new client implementations, ESIS University, ESIS construction practice, and ESIS global initiatives.
Mr. Higdon has 20 years of industry experience. He began his career in consulting conducting and managing auditing, program evaluation, and program design projects for workers compensation and integrated disability management programs to large employers and service providers. He left consulting for the third-party administrator (TPA) space where he held a variety of positions under information technology and client services developing and delivering differentiated products and services to clients. With a strong focus on information delivery, his previous TPA experience culminated in the management of four departments focusing on client reporting, predictive modeling, client-facing system enhancement and support, and loss control consulting and OSHA administration. Mr. Higdon holds two Bachelor of Science degrees in the social sciences from Northern Illinois University and a master’s degree in information technology and management from Illinois Institute of Technology. He is a board member, and former Chairman, for the Center for Employee Health Studies associated with the School of Public Health at the University of Illinois at Chicago. Mr. Higdon supports industry development through participation in regional and national conferences and has published on key topics including integrated disability management, the data lifecycle, and predictive modeling over the years. He is also a volunteer mentor and guest speaker at YearUp, a community college based program for economically disadvantaged students.
Keith Higdon is speaker of the following session:
Director of Data Science, US EOIT Advanced Analytics & AI
Richard Lee is Director of Data Science for John Hancock, the U.S. division of Toronto-based Manulife.
Richard leads the Advanced Analytics & AI group, which supports operations decision analytics across all U.S. businesses.
In his current role, Richard finds opportunities for efficiencies in Life Insurance as well as Long Term Care Insurance operations. Much of his focus is on innovation to enhance the relevance and understanding of analytics and its impact on operations decision-making.
Prior to his current role, Richard has spent 15 years at John Hancock in various analytics roles.
Richard Lee is speaker of the following session:
As Vice President of Product & Engineering at Big Squid Nick oversees the development and execution of the firm's machine learning software platform, Kraken. He has been with Big Squid since 2015, holds the Chartered Financial Analyst designation, AB from Dartmouth College, and is a former member of the Chicago Quantitative Alliance. When he's not at work he plays soccer, loves cheering at his son's snowboarding competitions and lives in Utah with his wife & two children.
Senior Data Scientist, Decision Analytics
Olaf serves as a Senior Data Scientist in the Decision Analytics team at Pacific Life in Newport Beach, California. He focuses on the design of data driven approaches to improve business decision making and customer experience. Most frequently, he uses tools from time series analysis, machine learning automation and data visualization. To maximize the performance of his models and the measurable impact of his analyses, he enjoys working with internal and external collaborators to formalize facts, to calculate new metrics and to explore new data sources.
Olaf started his career in academia, implementing scientific web tools and conducting research based on ecological, meteorological and geographical data. He has also worked as a Predictive Analyst in the Global Analytics department at Ingram Micro in Irvine, California. He received a M.Sc. in Bioinformatics from Friedrich Schiller University in Germany and a Ph.D. in Geographic Information Science from University of California, Santa Barbara.
Olaf Menzer is speaker of the following session:
GM & Head Of Analytics Services
Sean joined Enova as Head of Analytics Services for Enova Decisions in 2016. Prior to working at Enova, Sean served as Senior Director of Business Analytics for Leapfrog, where he led the development of the company’s predictive analytics capabilities. Before Leapfrog, Sean served as Director of Strategic Intelligence for TrendPointers, LLC, and Associate Portfolio Manager at Sarasota Capital Strategies. Sean is a CFP® certificant and holds the CMT designation. He received his B.S. in finance from the University of Illinois at Chicago and Financial Planning Certificate from Northwestern University.
Sean Naismith is speaker of the following session:
CSPA, Founder and Lead Data Scientist
Advanced Analytics Consulting Services, LLC
Mrs. Mei Najim, CSPA, Founder and Lead Data Scientist is the Co-Chair of PAW for Financial.
She provides advanced analytics consulting services including developing full life cycle predictive modeling processes from raw data exploration to model implementation into IT data systems, thorough documentation, and related training. Mei has over 14 years hands-on advanced analytics and machine learning experience dealing with large and complex data sets in various types of predictive analytics settings (claims, underwriting, pricing). She also has extensive traditional actuarial analysis experience including pricing, reserving, and research & development in the insurance industry. She has presented at many conferences to share and discuss her papers and expertise in predictive analytics with industry analytics experts.
Mei holds a Bachelor of Science in Actuarial Science from Hunan University and two Master of Science degrees, in Applied Mathematics and in Statistics, from Washington State University. Mei is a member of the American Statistical Association and a Certified Specialist in Predictive Analytics (CSPA) of the Casualty Actuarial Society.
Mei Najim is speaker of the following sessions:
Mei Najim is moderator of the following session:
Senior Director in Global Decision Management
Yulin Ning is a Senior Director in Global Decision Management, a global strategy and analytic division in Citi's Global Consumer Bank. He currently leads next generation analytics efforts within Platform and Capability function, acting as a chief data scientist, aiming to accelerate global adoption of big data and machine learning for creative business solutions. He developed expertise in digital (clickstream), text mining, voice analytics, big data, and machine learning. His most recent interests are on deep learning and artificial intelligence.
Over 18 years at Citi, Yulin has been actively involved in building some of the key decision management disciplines in the areas of price management, stress test capabilities, optimization, big data / machine learning roadmap, and data scientist disciplines. He worked with a range of financial and technology companies, vendors, and universities specializing in analytics and emerging technologies. He holds a Ph.D. in Agricultural Economics.
Dr. Zeydy Ortiz is the co-founder & CEO of DataCrunch Lab, LLC. She has been helping teams and organizations transform data into value across many industries including IT, financial, retail, and the manufacturing sectors. Her team built an innovative, award-winning digital assistant that was recognized as 'Highest Potential Value to Manufacturers' for increasing visibility of real-time production and plant operations.
She started her career as a Performance Engineer at IBM building predictive models to inform business strategy. She worked on multiple projects focused on improving performance & efficiency. She earned recognition for innovation on Smarter Planet/IoT solutions and for her industry contributions defining resource efficiency metrics. Dr. Ortiz obtained her bachelor's degree from the University of Puerto Rico, master's from Texas A&M University, and Ph. D. in Computer Science from North Carolina State University.
Zeydy Ortiz is speaker of the following sessions:
Andreas is working as a Quantitative Researcher at Goldman Sachs Quantitative Execution Services, with an emphasis in machine learning techniques for execution algorithms. Andreas has received a PhD in Information Engineering at the University of Cambridge, focusing on the interface of stochastic control theory and Bayesian machine learning, where he developed graph theoretic tools for predicting the shapes of the probability distributions to arise in the observable time-series due to the underlying non-linear stochastic interconnections. Andreas’ teaching experience included several engineering undergraduate courses, including Inference and Machine Learning, Linear Algebra, Probability, Control and Signal Processing. During his PhD, he has also worked at Informetis Europe as a Machine Learning Algorithm Engineer, developing efficient Bayesian inference techniques for smart electricity meter applications. Andreas also holds a BA and an MEng degree in Electrical and Information Sciences from Trinity College, University of Cambridge, during which he has received the G-Research and The Technology Partnership (TTP) awards, while his Master’s thesis was done in collaboration with British Cycling, developing a racing cyclist fitness predictor.
Andreas Petrides is speaker of the following session:
Bill is responsible for the diwo product strategy and development. He is a graduate of Lawrence Technological University and brings more than 20 years of software product management experience in the retail, automotive, manufacturing and financial services verticals
Bill Rachilla is speaker of the following session:
Simon has been working at Trisotech for the last 15 years where he leads the software development team responsible for producing its SaaS digital transformation and automation suite. He also has been deeply involved the standardization of the Business Process Management domain by working on standards such as BPMN, CMMN, DMN, XPDL and BPSim. He received a bachelor’s degree in Software Engineering and is also an OMG Certified expert in BPM at the advanced level in both the business and technical tracks. Simon currently works at the Trisotech head office in Montreal, Quebec, Canada.
Simon Ringuette is speaker of the following session:
Rob Rolleston is the Manager, Data Science at Paychex. Previously Rob worked at Xerox in the areas of Information Visualization, Strategy & Planning, and Color Management. He has 47 issued patents, and numerous technical publications and presentations.
He received his B.S. in Computational Physics from Carnegie-Mellon University, and his M.S. and Ph.D. in Optics from the University of Rochester. Rob recently completed an MPS Degree in Information Visualization from Maryland Institute College of Arts, and is now an instructor for the program where he teaches statistics and data analysis. Rob has also been an adjunct professor and instructor at Rochester Institute of Technology. He has served on the Executive Advisory Board for the New York State Center for Electronic Imaging Systems, the Advisory Board for the Rochester Institute of Technology Center for Imaging Science, and was chair of the Xerox University Affairs Committee.
Rob Rolleston is speaker of the following session:
Senior Data Scientist
Mohammad is currently a Senior Data & Applied Scientist at Microsoft, and Instructor at Stanford University. He is a former Data Scientist at Apple and previously worked for Samsung, Bosch, General Electric and UCLA Research Labs. He received a PhD in Computer Science from the University of California, Riverside and B.Sc. from University of Tehran. Mohammad is the author of the book, ‘Applications of Mining Massive Time Series Data'. He has also been a keynote speaker at more than 40 Data Summits/Conferences around the globe.
Mohammad Shokoohi-Yekta is speaker of the following session:
Michael Steliaros is the global head of Quantitative Execution Services at Goldman Sachs. He is responsible for the research, development and implementation of quantitative processes for portfolio and electronic trading as well as managing the bank's relations with the quantitative client base. Previously, Michael held a variety of senior roles at BofAML in London and New York, most recently running the global agency portfolio trading and quantitative equity businesses. Earlier in his career, he spent a decade on the buy-side (most notably BGI and Winton) building quant stock-selection models and managing global market neutral equity portfolios. Michael received a bachelor's degree in Economics & Econometrics from the University of Nottingham, and an MSc and PhD in Finance from City University (CASS) Business School in London
Michael Steliaros is speaker of the following session:
Vice President, Data Science Manager
Nathan Susanj is a data scientist on the Wells Fargo Enterprise Analytics and Data Science team. He leads a small team as head of Natural Language Processing (NLP) and Speech Capabilities Development, where he is focused on building out Wells Fargo's capabilities in areas related to NLP, deep learning and data science product design. Nathan holds a Masters in Predictive Analytics from Northwestern University and is working on his second Masters in Computer Science from Georgia Tech. He has been with Wells Fargo for the past five years and worked in marketing analytics prior to his current role.
Nathan Susanj is speaker of the following session:
Chief Risk and Data Analytics Officer
William (Bill) Wilkins is a multi-purpose actuary for the Safety National Casualty Corporation(SNCC). He is a CERA, FCAS, ASA and MAAA. While his main focus is on Enterprise Risk Management and Predictive Analytics, Bill has experience in pricing insurance, reinsurance, credit risk products, risk management, reserving and broker management. He is currently Co-Chair of the SNCC Data Analytics Committee. The Data Analytics Committee is a cross-functional group tasked with all aspects of data for SNCC. The Committee works on data to be collected, how it is collected, where it is collected from, how it stored, standards and practices of usage, etc. This includes the populating items like benchmarking reports or how best to create and use predictive analytics. The goal is to establish a process that is repeatable and adaptable so SNCC can deliver both internally and externally.
William WIlkins is speaker of the following session:
Vice President - Risk Analytics
Ted Ziton has worked in various aspects of analytics for insurance carriers, brokerages and managed care organizations for the last twenty five years. He joined Gallagher-Bassett in 2015 and is the point man for GB's first AI predictive system, Waypoint. The original Waypoint application was designed to help adjusters establish and monitor claim reserves on complex claims. Since Ted took the helm, Waypoint has gone through multiple upgrades and new functionalities have been added or are currently in development. Ted has the primary responsibility for turning the multiple predictive outputs of Waypoint into easily understood information which can be used by adjusters to make better decisions in handling claims and to better understand the cost drivers of individual claims.
Theodore Ziton is speaker of the following session: