What are we doing to stamp out AI bias in financial services?

Financial services and fintech businesses can gain significant competitive advantage if they take action to deal with, and remove, unfair bias in their data now, ahead of potentially tougher regulations being introduced which could force companies to act in future.

That’s the view of Nicolai Baldin, founder and CEO Synthesized, who was speaking on the ‘Open Finance’ podcast, produced by leading financial technology provider, Finastra. He was joined on the podcast by Adam Lieberman, Head of Artificial Intelligence and Machine Learning at Finastra.

Listen to the full podcast here and read the full article here.

Agenda:

• Why is AI bias a problem for fintech and other organizations? 
• What problems can data bias create? 
• Why is it essential to address bias now and what are the risks for the organizations that don't tackle it?
• How do Finastra and Synthesized work towards solutions to data bias?
• What are the implications for society if we don't solve these problems collectively?
• How will the field of data and AI bias evolve in the future? 
  

“Failure by society to deal with data bias would mean a vicious cycle of bias in artificial intelligence.“We need to seek an understanding of bias and prioritise it, otherwise we are just going to replicate it. Machine learning in a nutshell is about using historical data, drawing patterns and insights and making predictions. 

“If we don’t define what bias is, and then look for it in our data to make sure it’s as bias- free as it can be, then we are just going to be learning to replicate this bias that lives in our datasets. It’s a cycle of bias that can be prevented.”
Adam Lieberman, Head of Artificial Intelligence and Machine Learning at Finastra