Data analytics and ML in the Cloud

English
October 1, 2020
from 10:00 AM to 11:00 AM CEST

WEBINAR OVERVIEW

Despite proof and evidence of the benefits of cloud migration, scepticism remains about its security, slowing the process of digital transformation in safety-critical contexts such as banking and digital payments.

Inspired by our customer experience, we will show how we introduced data analysis and machine learning on cloud to the largest Italian paytech, bringing quantity and quality of data and leveraging Artificial intelligence-based technologies having a major impact on banks’ capabilities in areas like fraud, risk management, marketing and service delivery, all in a security compliant way.

WHY ATTEND?

This BONUS webinar in our series covering all aspects of Cloud adoption in Financial Services focuses on building a Data Analytics Cloud Platform and offers insights into:

  • How to build a Cloud Data Platform
  • Remain compliant to normative and GDPR
  • Enable a new approach to the Data Analytics and Machine Learning

This will be another engaging online event with insightful presentations followed by a Q&A panel discussion with our guest speakers.

Agenda

10.00-10.10 CEST (09.00-09.10 BST): Strategic Infrastructure Considerations for the C-Suite and Board Members in Financial Services Marco Magagnini, Partner, Data Reply

10.10-10.20 CEST (09.10-09.20 BST): Nexi Cloud Data and AI Journey
Stefano Gatti, Head of Data & Analytics, Nexi

10.20-11.00 CEST (09.20-10.00 BST): Panel Discussion and Q&A (facilitated by Freddy Gielen, Executive Partner, Reply)
Giuseppe Porcelli, Principal EMEA Machine Learning Specialist Solutions Architect, AWS
Stefano Gatti, Head of Data & Analytics, Nexi
Marco Magagnini, Partner, Data Reply
Luca Montinari, Senior Manager, Data Reply

Speakers

Giuseppe Porcelli
Principal EMEA Machine Learning Specialist Solutions Architect
AWS
STEFANO GATTI
Head of Data & Analytics
Nexi
Freddy Gielen
Executive Partner
Reply
Marco Magagnini
Partner
Data Reply
Luca Montinari
Senior Manager
Data Reply

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