In episode #3, we are joined by two guests, Brad Carr and Natalia Bailey from the Institute of International Finance (IIF) to learn about some of the most comprehensive research conducted in the adoption and governance of AI in the Finance industry, over the last 3 years.

With more than 450 members from 70 plus countries, the IIF's mission is to support the industry in the management of risks and to advocate for appropriate regulatory, financial, and economic policies. The IIF’s annual Machine Learning surveys since 2018 has provided invaluable insight into AI adoption, barriers and governance in the industry.

We also discuss the IIF’s Data Ethics Charter, and explore why banks have an opportunity, and perhaps a duty, to make trust a key part of their customer proposition.

About the speakers
Brad Carris Managing Director for Digital Finance at the IIF and has led the IIF’s work across a range of data and digital topics. Before joining the IIF in 2014, Brad spent over a decade in National Australia Bank.

Natalia Baileyis a policy advisor in the same team and has played multiple roles at the IIF over more than a decade. Natalia is also the driving force behind a lot of the IIF’s work around AI governance and data ethics.

In episode #3, we are joined by two guests, Brad Carr and Natalia Bailey from the <a href="https://www.iif.com/">Institute of International Finance</a> (IIF) to learn about some of the most comprehensive research conducted in the adoption and governance of AI in the Finance industry, over the last 3 years.
With more than 450 members from 70 plus countries, the IIF's mission is to support the industry in the management of risks and to advocate for appropriate regulatory, financial, and economic policies. The IIF&rsquo;s <a href="https://www.iif.com/Publications/ID/4198/Machine-Learning-Governance-Summary-Report">annual Machine Learning surveys</a> since 2018 has provided invaluable insight into AI adoption, barriers and governance in the industry.
We also discuss the <a href="https://www.iif.com/Publications/ID/4452/IIF-Data-Ethics-Charter">IIF&rsquo;s Data Ethics Charter</a>, and explore why banks have an opportunity, and perhaps a duty, to make trust a key part of their customer proposition.
About the speakers Brad Carr is Managing Director for Digital Finance at the IIF and has led the IIF&rsquo;s work across a range of data and digital topics. Before joining the IIF in 2014, Brad spent over a decade in National Australia Bank.
Natalia Bailey is a policy advisor in the same team and has played multiple roles at the IIF over more than a decade. Natalia is also the driving force behind a lot of the IIF&rsquo;s work around AI governance and data ethics.

Welcome to The Trustworthy AI Podcast from TruEra, the leading provider of AI quality diagnostic and monitoring software, hosted by Shameek Kundu, Head of Financial Services and Chief Strategy Officer. He'll speak to leading AI practitioners to demystify the concept of trustworthy AI, focusing initially on financial services. He'll uncover the real extent of AI adoption in the industry today, the importance of building trust, and practical ways of getting there. 

Welcome to The Trustworthy AI Podcast from TruEra, the leading provider of AI quality diagnostic and monitoring software, hosted by Shameek Kundu, Head of Financial Services and Chief Strategy Officer. He'll speak to leading AI practitioners to demystify the concept of trustworthy AI, focusing initially on financial services. He'll uncover the real extent of AI adoption in the industry today, the importance of building trust, and practical ways of getting there.&nbsp;

The Trustworthy AI Podcast

The Trustworthy AI Podcast interviews leading figures in machine learning and AI, discussing how to bring high-quality AI applications to real-world use, while navigating regulations, ethical standards, and business and community needs. The first season is hosted by Shameek Kundu, Chief Strategy Officer at TruEra, and is focused on financial services. 

 

The Trustworthy AI Podcast interviews leading figures in machine learning and AI, discussing how to bring high-quality AI applications to real-world use, while navigating regulations, ethical standards, and business and community needs. The first season is hosted by Shameek Kundu, Chief Strategy Officer at <a href="http://www.truera.com/">TruEra, </a>and is focused on financial services.&nbsp;
&nbsp;

Trustworthy AI

AI adoption in Financial Services with Brad Carr, Managing Director, Digital Finance & Natalia Bailey, Policy Advisor, Digital Finance at Institute of International Finance

In this episode, we talk to Anant Bhardwaj, who founded and leads Instabase, an AI application platform for unstructured data. Instabase has been helping Enterprise customers worldwide streamline their operational processes, by using AI and workflow automation to intelligently process documents. 

Anant talks about the evolution of the underlying language/ document processing techniques underpinning Instabase - from Program Synthesis to Deep Learning, and, more recently, Large Language Models (LLMs). He shares his nuanced view on LLMs: bullish on its broader promise, but cautious about its near term usability in Enterprise use cases due to issues around lack of predictability and security/ privacy concerns.

In this episode, we talk to Anant Bhardwaj, who founded and leads <a href="https://instabase.com/">Instabase</a>, an AI application platform for unstructured data. Instabase has been helping Enterprise customers worldwide streamline their operational processes, by using AI and workflow automation to intelligently process documents. 
Anant talks about the evolution of the underlying language/ document processing techniques underpinning Instabase - from Program Synthesis to Deep Learning, and, more recently, Large Language Models (LLMs). He shares his nuanced view on LLMs: bullish on its broader promise, but cautious about its near term usability in Enterprise use cases due to issues around lack of predictability and security/ privacy concerns.

The Evolution of LLM Use at Scale with Anant Bhardwaj, Founder & CEO at Instabase

In episode #10, we are joined by two guests, Andy McMahon and Greig Cowan from the NatWest Group, to learn about the group’s Machine Learning Operations (MLOps) journey.

Andy and Greig talk about the four pillars of that journey - People, Process, Data and Technology - and about the efforts to embed ML model quality by design into those pillars. They explain how the group’s standardised data lab methodology, supported by a modern toolset, has enabled the group to scale its data science capability rapidly. 

About the speakers

Andy McMahon heads MLOps at NatWest Group, while Greig Cowan heads Data Science and Engineering for Data Innovation at the Group. Both have extensive experience of taking analytics solutions from ideation to production. 

Andy’s experience spans model building, software development and technical management. His particular area of interest is the challenge of deploying machine learning based software products at scale. He is also the author of a book on ML engineering.

Greig has over 15 years of experience at the leading edge of scientific research, including with the Large Hadron Collider, where he developed physical models to statistically extract fundamental parameters from large datasets. He now focuses on data science innovation within the financial services industry.

In episode #10, we are joined by two guests, Andy McMahon and Greig Cowan from the NatWest Group, to learn about the group’s Machine Learning Operations (MLOps) journey. Andy and Greig talk about the four pillars of that journey - People, Process, Data and Technology - and about the efforts to embed ML model quality by design into those pillars. They explain how the group’s standardised data lab methodology, supported by a modern toolset, has enabled the group to scale its data science capability rapidly. About the speakers Andy McMahon heads MLOps at NatWest Group, while Greig Cowan heads Data Science and Engineering for Data Innovation at the Group. Both have extensive experience of taking analytics solutions from ideation to production.  Andy’s experience spans model building, software development and technical management. His particular area of interest is the challenge of deploying machine learning based software products at scale. He is also the author of a book on ML engineering. Greig has over 15 years of experience at the leading edge of scientific research, including with the Large Hadron Collider, where he developed physical models to statistically extract fundamental parameters from large datasets. He now focuses on data science innovation within the financial services industry.

Embedding Model Quality Into Your MLOps Journey, with Andy McMahon and Greig Cowan of NatWest Group

In episode #9, TruEra co-founder Anupam Datta is joined by his guest, Agus Sudjianto, Executive Vice President and Head of Corporate Model Risk at Wells Fargo. Agus talks about the importance of ensuring model robustness, going beyond explainability and fairness, as a prerequisite for greater adoption of AI. We also learn a little bit of the history of Model Risk Management in the context of the U.S. banking industry and the important role it plays to increase trust in AI. Finally, Agus shares his thoughts on the AI opportunities that excite him the most and advice for young data scientists who are thinking of joining the banking industry. 

About the speaker

Agus Sudjianto is Executive Vice President and Head of Corporate Model Risk at Wells Fargo. Prior to joining Wells Fargo, he led analytics modeling teams at Lloyd’s Bank in the UK and at Bank of America. 

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Links:

Trustworthy AI Podcast

Shameek Kundu LinkedIn

Anupam Datta LinkedIn

Anupam Datta Twitter

Agus Sudjianto LinkedIn

TruEra

TruEra Twitter

Allen Newell-Wikipedia

In episode #9, TruEra co-founder Anupam Datta is joined by his guest, Agus Sudjianto, Executive Vice President and Head of Corporate Model Risk at Wells Fargo. Agus talks about the importance of ensuring model robustness, going beyond explainability and fairness, as a prerequisite for greater adoption of AI. We also learn a little bit of the history of Model Risk Management in the context of the U.S. banking industry and the important role it plays to increase trust in AI. Finally, Agus shares his thoughts on the AI opportunities that excite him the most and advice for young data scientists who are thinking of joining the banking industry. 
About the speaker
Agus Sudjianto is Executive Vice President and Head of Corporate Model Risk at Wells Fargo. Prior to joining Wells Fargo, he led analytics modeling teams at Lloyd’s Bank in the UK and at Bank of America. 
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Links:
<a href="https://marketing.truera.com/trustworthy-ai-podcast">Trustworthy AI Podcast</a> 
<a href="https://sg.linkedin.com/in/shameekkundu">Shameek Kundu LinkedIn</a>
<a href="https://www.linkedin.com/in/anupamdatta">Anupam Datta LinkedIn</a>
<a href="https://twitter.com/datta_cs">Anupam Datta Twitter</a>
<a href="https://www.linkedin.com/in/agus-sudjianto-76519619">Agus Sudjianto LinkedIn</a>
<a href="https://truera.com/">TruEra</a>
<a href="https://twitter.com/truera_ai?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor">TruEra Twitter</a>
<a href="https://en.wikipedia.org/wiki/Allen_Newell">Allen Newell-Wikipedia</a>

AI adoption in Financial Services with Brad Carr, Managing Director, Digital Finance & Natalia Bailey, Policy Advisor, Digital Finance at Institute of International Finance

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