DATA ANALYTICS IN RETAIL BANKING AND INSURANCE SUMMIT
17-18 JUNE 2021
VIRTUAL EVENT
Summary
The finance and insurance sectors by nature have been intensively data-driven industries, managing large quantities of customer data and with areas such as capital market trading having used data analytics for some time. After analysing the requirements and the technologies currently available it is clear that there are still research challenges to develop the technologies to their full potential in order to provide competitive and effective solutions. These challenges appear at all levels of data chain and involve a wide set of different technologies, which would make necessary a prioritization of the investments in R&D, such as real-time aspects, better data quality techniques, scalability of data management and processing, and better sentiment classification methods.
The Data Analytics in Retail Banking and Insurance Summit by Uniglobal will cover a range of topics that make this summit appealing to Retail Banking and Insurance companies, as well as other industry players from all over the world. It will bring on board a solid network of professionals and senior level experts who will share their experiences and views on the current sector challenges and opportunities, as well as expectations and predictions about future trends in Data Analytics. During multiple sessions the participants will discuss developments of Data Analytics, current challenges in the industry, rising importance of digital transformation and many other important topics.
DAY 1 – 17 JUNE 2021
DAY 2 – 18 JUNE 2021
Speakers
Sponsors
WHO SHOULD ATTEND?
- Insurance Companies
- Retail Banking
- Digital Banking
- Digital Transformation
- Consumer Banking
- Capital Markets
- Private Banking
- Wealth Management
WHO SHOULD ATTEND?
Chief Officers, Managing Directors & Heads of:
- Data Management / Data Analytics
- Data Protection & Data Privacy
- Data Integration
- Data Engineering
- Data Architecture
- Data Quality
- Data Science
- Data Infrastructure
- AI & ML
- Robotic Process Automation
- IT / Technology
- Innovation
- Digital Transformation / Digital
- Research & Development
- Customer Experience / Customer Data