Adopting AI, ML, and automation in the banking industry with Agus Sudjianto, EVP, Head of Corporate Model Risk at Wells Fargo

2 years ago Posted By : User Ref No: WURUR97187 0
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  • TypeWebinar
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  • Location Online Event
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  • Date 03-03-2022
Adopting AI, ML, and automation in the banking industry with Agus Sudjianto, EVP, Head of Corporate Model Risk at Wells Fargo, Online Event
Webinar Title
Adopting AI, ML, and automation in the banking industry with Agus Sudjianto, EVP, Head of Corporate Model Risk at Wells Fargo
Event Type
Webinar
Webinar Date
03-03-2022
Location
Online Event
Organization Name / Organize By
Cogniltytica
Presented By
Agus Sudjianto, Executive Vice President, Head of Corporate Model Risk at Wells Fargo
Organizing/Related Departments
Enterprise Data & AI
Organization Type
Company
WebinarCategory
Both (Technical & Non Technical)
WebinarLevel
All (State/Province/Region, National & International)
Related Industries

Engineering

Computer Science

Information Technology

Computer/Technology

Internet/Ecommerce

Location
Online Event

The March 2022 Enterprise Data & AI featured guest speaker is Agus Sudjianto, Executive Vice President, Head of Corporate Model Risk at Wells Fargo and his presentation "Adopting AI, ML, and automation in the banking industry" Thursday, March 3, 2022 from 11:30 AM  - 1 PM ET!

The banking industry has rapidly adopted Machine Learning for various applications for predictive analytics and process automation. The adoption of AI/ML is very natural because of the nature of the business that is both data and process intensive. While the benefits of AI/ML are very compelling, they are also bringing new risks beyond the traditional financial risk. With their model risk management practice that has been maturing in the last 10 years, banks are ahead of other industries in managing the risk of AI/ML. One of the key aspects to manage the risk is model explainability. 

While the adoption of so called ExplainableAI, which is typically ‘black box’ machine learning models accompanied by post-hoc explainability tools, is becoming more common for low risk applications, the concern remains for high risk areas such as credit underwriting; thus large banks are typically more cautious in adopting the methodology. There are many recent developments on inherently interpretable, self-explanatory machine learning models without the problem of post-hoc explainers. The focus of my talk will cover applications of AI/ML, their risk management as well as the approach for designing inherently interpretable machine learning for high-risk applications.

 

Be sure to stick around for Q&A at the end! Register and attend for free on the Cognilytica event website: https://events.cognilytica.com/CLNTkxMnwxOA

Agenda:

  • 11:30 - 12:30pm: Featured Presentation
  • 12:30 - 1:00pm: Your Q&A and interaction
Registration Fees
Free
Registration Ways
Website
Address/Venue
Online Virtual Event  N/A 
Contact