Webinars 

• Fintech business models built for uncertain times
• Preparing identity verification and fraud prevention strategy as agencies disburse stimulus and disaster recovery funds
• Educating consumers and preparing internally for COVID-19 scams
• Aligning fraud, growth, and innovation strategies 

In this webinar, Socure Privacy & Compliance Officer Annie Bai, Socure Product Director Gene Radin, and Socure VP of Marketing Rivka Little explore the demand CCPA places on identity verification and how leveraging advanced analytics and data science methods along with digital document verification can enable a safe road to CCPA compliance. 

In this webinar we’ll discuss:

• What is the process of CCPA’s verified customer requests (VCR) – or is there one?
• What are the consumer and business risks in complying with CCPA’s verified customer requests?
• How AI-based digital identity verification enables safe CCPA compliance
• Aligning fraud, growth, and innovation strategies

Feature Engineering is what separates good machine learning outcomes from great machine learning outcomes.  Part art and part science, feature engineering combines domain expertise with data science acumen to transform raw data into the variables that drive machine learning models.

In this second webinar in our six-part series, Socure’s VP Data Science, Pablo Abreu, discusses the methods used in feature engineering to go from raw data (discussed here Data Exploration - Improving the Foundation) to highly predictive features. More specifically, Pablo will share the approach Socure takes to build proprietary predictors to boost machine learning model performance.

In this webinar, Pablo will share:

• General concepts and approaches to feature engineering
• Typical challenges encountered with feature engineering
• Several best practice approaches to consider to maximize success
• Considerations for manual vs. automated approaches to feature engineering

In this first of six webinars, Pablo starts at the beginning and discusses different methods for data exploration. As the goal of data science is to extract knowledge and insights from data, it makes sense that we start with data and explain the process used for the initial analysis of data.

In this on-demand webinar, Pablo shares:

• General concepts and approaches to data exploration
• Typical challenges encountered with data exploration
• Several best practice approaches to consider to maximize success