Minimize risk & multiply returns with machine learning

Las Vegas

 

May 31-June 4, 2020

Join us at Caesars Palace for Predictive Analytics World for Financial, the leading data science event covering the deployment of machine learning and predictive analytics for financial services. Hear from the horse’s mouth precisely how banks, insurance companies, credit card companies, investment firms, and other financial institutions — both Fortune 500 analytics competitors and other top practitioners — deploy machine learning and predictive modeling. As part of Machine Learning Week 2020, PAW Financial will be held alongside PAW Business, PAW Healthcare, PAW Industry 4.0, and Deep Learning World.

PAW Financial Keynote Speakers

Richard Lee
Richard Lee

Director of Data Science, US EOIT Advanced Analytics & AI


Keynote Details

“Needle in the Haystack” – a Case Study on Defect and Fraud Detection
This keynote address will focus on real life “Needle in a haystack” problems and why these problems are becoming much more frequent. Two case studies: defect detection as well as fraud detection models from start to finish and their chances of implementation. We’ll discuss what works and what may be holding you back from a successful implementation. The need for several solution strategies and packaging them in one delivery will also be explored.

Keynote Details

“Needle in the Haystack” – a Case Study on Defect and Fraud Detection
This keynote address will focus on real life “Needle in a haystack” problems and why these problems are becoming much more frequent. Two case studies: defect detection as well as fraud detection models from start to finish and their chances of implementation. We’ll discuss what works and what may be holding you back from a successful implementation. The need for several solution strategies and packaging them in one delivery will also be explored.

Victor Lo
Victor Lo

AI and Data Science Center of Excellence Leader, Workplace Investing


Keynote Details

How to Find a Tailor-Fit “Unicorn” Data Scientist for Financial Services
With data scientists coming with all kinds of backgrounds and experience, how do you know which type you really need to meet your business needs? How many types of data scientist are out there? And where can you find them? What kinds of analytics can they provide for the financial services industry? Drawing from over 25 years of experience in the field with over two decades of management, Victor Lo will introduce a framework for the classification of data scientists and propose a mapping scheme between these talents and various types of projects.

Keynote Details

How to Find a Tailor-Fit “Unicorn” Data Scientist for Financial Services
With data scientists coming with all kinds of backgrounds and experience, how do you know which type you really need to meet your business needs? How many types of data scientist are out there? And where can you find them? What kinds of analytics can they provide for the financial services industry? Drawing from over 25 years of experience in the field with over two decades of management, Victor Lo will introduce a framework for the classification of data scientists and propose a mapping scheme between these talents and various types of projects.

Jen Gennai
Jen Gennai

Head of Responsible Innovation, Global Affairs


Keynote Details

Putting Ethical Principles into Practice When Deploying Machine Learning
As principles purporting to guide the ethical development of Artificial Intelligence proliferate, there are questions on what they actually mean in practice. How are they interpreted? How are they applied? How can engineers and product managers be expected to grapple with questions that have puzzled philosophers since the dawn of civilization, like how to create more equitable and fair outcomes for everyone, and how to understand the impact on society of tools and technologies that haven’t even been created yet. To help us understand how Google is wrestling with these questions and more, Jen Gennai, Head of Responsible Innovation at Google, will run through past, present and future learnings and challenges related to the creation and adoption of Google’s AI Principles.

Keynote Details

Putting Ethical Principles into Practice When Deploying Machine Learning
As principles purporting to guide the ethical development of Artificial Intelligence proliferate, there are questions on what they actually mean in practice. How are they interpreted? How are they applied? How can engineers and product managers be expected to grapple with questions that have puzzled philosophers since the dawn of civilization, like how to create more equitable and fair outcomes for everyone, and how to understand the impact on society of tools and technologies that haven’t even been created yet. To help us understand how Google is wrestling with these questions and more, Jen Gennai, Head of Responsible Innovation at Google, will run through past, present and future learnings and challenges related to the creation and adoption of Google’s AI Principles.

Gil Arditi
Gil Arditi

Product Lead, Machine Learning


Keynote Details

From Self-Driving to Fraud Detection – How Lyft Streamlines Machine Learning Deployment
In this keynote address, Gil Arditi will cover the areas of machine learning development at Lyft, talk about friction points in the model lifecycle – from prototyping and feature engineering to production deployment – and show how Lyft streamlined this process internally. He will also cover a step-by-step example of a model that was recently developed and taken to production.

Keynote Details

From Self-Driving to Fraud Detection – How Lyft Streamlines Machine Learning Deployment
In this keynote address, Gil Arditi will cover the areas of machine learning development at Lyft, talk about friction points in the model lifecycle – from prototyping and feature engineering to production deployment – and show how Lyft streamlined this process internally. He will also cover a step-by-step example of a model that was recently developed and taken to production.

PAW Financial is part of Machine Learning Week Las Vegas — the facts:

Days

Days

Conferences

Tracks

Workshops

Speakers

Speakers

Sessions

Sessions

Attendees

LAST YEAR – COMPANIES ON THE 2019 AGENDA

Witness how practitioners at these leading enterprises apply machine learning:

Enova
ESIS
Experian
Gallagher Bassett
Goldman Sachs
Hitachi
Institute of Consumer Money Management
Microsoft
Manulife
Pacific Life
Paychex
PricewaterhouseCoopers
Safety National Casualty Corporation
Stanford University
Wells Fargo

Previous attendees describe what they found most valuable at PAW:

Testimonials

James McCaffrey- Senior Scientist Engineer, Microsoft

The bottom line: the event was really good — I give it an overall grade of an A- which is (tied for) the best grade I’ve ever given to any conference.

Indu Sriram - Digital Marketing Analytics Manager, Staples

I'm happy we have a conference like Predictive Analytics World - where practitioners like myself can meet other professionals and learn all the latest and greatest. It's a go-to resource and I often attend - hats off to this conference's producers!

Allison Gonzalez - Decision Science Analyst, USAA

Just do it! Everybody is doing it! I attended PAW San Francisco 2016 and I come back with many new contacts, new friends, and more knowledgeable.

Kenton - Economist, Nike

The emphasis on practical application of analytics to real world business problems and decision making is just right at this conference!

Jason King - Principal Scientist, Procter and Gamble

A 360 degree event - great for anyone who wants to know where data analytics is at and where it's going.

Cross-register for one or all of the other Machine Learning Week conferences:

PAW Business
PAW Healthcare
PAW Executive Breakfast
Deep Learning World

This PAW Financial event is held alongside the more broadly-scoped event, PAW Business. While financial services-specific topics are covered at PAW Financial, some financial services companies present at PAW Business on topics such as marketing applications and analytics strategy. Available cross-registration options provide you the opportunity to attend sessions at both events. Click here for details about PAW Business.

See also the co-located conference Deep Learning World for additional sessions from Capital One, John Hancock, Northwestern Mutual, PayPal, and others. Cross-registration options are available to attend both events.

Impressions from PAW Financial

Come to Predictive Analytics World and access the best keynotes, sessions, workshops, vendor exposition, expert panel, networking coffee breaks, reception, networking lunches, brand-name enterprise leaders, and industry heavyweights in the business.

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