Artificial Intelligence and Machine Learning can allow companies to gain greater insights on existing data and explore new ways for that data to then be utilised. PETs can aid this process during development, implementation and monitoring.
- Synthetic data as a means by which to train AI/ML models- the pros, cons and achieving the best result in practice
- Utilising AI/ML in conjunction with PETs to help achieve a proactive rather than reactive data stance, giving organisations greater insight to the data they store and how it is used
- Strengthening the ability of enterprise to comply with various requirements from regulators, customers and internal stakeholders.
Gero Gunkel
Adri Purkayastha
Adri Purkayastha is currently Group Head of AI and Digital Risk Analytics at BNP Paribas S.A. In this role, his span of responsibility includes all Brands and Subsidiaries, across Domestic Markets, International Financial Services and Corporate & Institutional Banking. He focuses on developing, championing, and building an enterprise-wide understanding of AI/ML opportunities and risks, and overseeing end-to-end AI & Analytics governance and operating models. Additionally, he provides strategic and technical counsel on Data strategy and development of AI and Data Science solutions across the entire Group. Earlier in his career at Deloitte, he was the founder and product owner of AI-enabled SaaS solutions and AI & Data Science advisory lead focussed on Financial Services, worked in Forensic Data Analytics at EY and on Marketing Data Science in Pitney Bowes. He comes from a background that includes entrepreneurship, product management, and data science where we founded companies building AI-enabled products for EdTech, and P2P marketplaces.
