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AI in wealth management and asset management:
creating a successful business-technology partnership around high-value use cases

Making AI transparent:
Using explainable AI when clients and regulators need to understand what algorithms are doing

Operationalising AI models:
Using MLOps to run AI at scale when models multiply

ESG and AI:
Gaining an accurate picture of ESG data across the confusing ESG rating landscape

Duration 45 min

  • 30 min (presentation)
  • 15 min (Q&A)


As AI adoption is strongly increasing across wealth management and asset management, business and technology leaders are facing new challenges, across their maturity levels.

While many banks are still stuck in the ‘POC purgatory’, some are moving ahead and require to operationalise the use cases they have successfully adopted, to let them perform in their broader technology environment.
Specific topics are also strongly emerging based on pressure from regulators and stakeholders. Transparency becomes a must, which poses some constraints for data scientists to use specific algorithm classes, and requires a systematic approach to make AI explainable. ESG is also gaining prominence in the industry, with a new European regulation on reporting, to cut across the inconsistency of data sources. AI can help bring clarity in this confusing landscape.

Cognizant has supported multiple ‘tier 1’ banks in the build-up of their AI strategy from governance build-up, use cases pipeline setup to the operationalisation of models, resulting in 50+ models supporting major banking decisions running in production.

We would like to share our experience in making this journey successful for our clients.
Mykola Hayvanovych, Ph.D., Cognizant Global Head of AI for Banking and Financial Services will lead this session, hosted by Brigitte Roy, Head of Banking and Financial Services Switzerland, and Luc Gerardin, Head of Cognizant Digital Business for Banking and Financial Services in Switzerland.

To secure your spot for this session, please RSVP