improve-model-quality

WEBINAR | JUNE 8TH 

Why isn't AI scaling in banks?

And what to do about it

After speaking with over 30 banks and regulators, former CDO at Standard Chartered Bank, Shameek Kundu, shares what he's learned. 

Over the last few years, significant investments have been made in creating and deploying models. Yet, for most banks adoption remains slow.

And as regulators in North America and Europe become more explicit in their expectations of responsible AI, AI projects risk even greater stagnation.

What can be done about it? 

Join us on Tuesday, June 8th as banking and AI veteran and former CDO at Standard Chartered Bank, Shameek Kundu, shares the current state of AI in banking and ways to increase trust and adoption of AI. 

During the 45-minute webinar, he will cover:

  • How deep and ‘real’ is AI adoption in banking?
  • What are the key barriers to adoption today?
  • Why is developing trust in AI so difficult?
  • What impact will new regulation have on the industry?
  • What can banks do to scale AI and make their investments count?

Tuesday, June 8th, at 8 AM PST, 11 AM ET, 4 PM GMT.

Can't make the live webinar?  No problem. Register anyway, and we will send you the recording. 

 


 

Join us for the webinar


Meet the Speaker

Shameek-Kundu

Shameek Kundu, Head of Financial Services and Chief Strategy Officer 

Shameek has spent his career in driving adoption of AI in the financial services industry.
 
Most recently, Shameek was Group Chief Data Officer at Standard Chartered Bank where he helped the bank explore and adopt AI in multiple areas (e.g., credit, financial crime compliance, customer analytics, surveillance), and shaped the bank’s internal approach to responsible AI.

About TruEra


TruEra provides AI Quality solutions that analyze machine learning, drive model quality improvements, and build trust. Powered by enterprise-class Artificial Intelligence (AI) Explainability technology based on six years of research at Carnegie Mellon University, TruEra’s suite of solutions provides much-needed model transparency and analytics that drive high model quality and overall acceptance, address unfair bias, and ensure governance and compliance.