When machine learning goes awry, here's how to do better next time
Executives from JP Morgan, Morgan Stanley, and BNY Mellon discuss the lessons learned through experimenting with machine learning at their firms.
At this year’s North American Financial Information Summit, held on May 17 in Manhattan, machine-learning engineers from JPMorgan, BNY Mellon, and Morgan Stanley discussed where they’ve seen machine-learning (ML) projects go wrong. While some of the lessons learned from failures may seem obvious, inexplicable, opaque ML implementations still plague the industry. Financial professionals want to use ML as a magic bullet, but without a thought-out process and a plan, the end results often
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@waterstechnology.com or view our subscription options here: https://subscriptions.waterstechnology.com/subscribe
You are currently unable to print this content. Please contact info@waterstechnology.com to find out more.
You are currently unable to copy this content. Please contact info@waterstechnology.com to find out more.
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@waterstechnology.com
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@waterstechnology.com
More on Emerging Technologies
‘AI for everyone, everywhere, with everything’
Waters Wrap: Anthony looks at some interesting projects involving machine learning, generative AI, and agentic AI from the last year.
Waters Wavelength Ep. 327: Standard Chartered’s Mo Rahim
He joins the podcast to discuss data and AI governance and guardrails for AI.
Paxos files to become SEC-registered clearing agency
The application comes after the blockchain infrastructure company completed a pilot in 2021 to test its settlement service.
Generative AI brings testing times for modelers
Flagstar’s lead model validator offers some tips for safely integrating LLMs into risk models.
Genesis CEO steps down, Wells Fargo deploys agents, DTCC sells Report Hub, and more
MarketAxess has enhanced its dealer-initiated protocols, EquiLend launches a market intelligence tool powered by AI, and the summer heat fuels fury over market data prices in this week’s news roundup.
PE money tips the ‘scale’ for growing vendors
The IMD Wrap: For many businesses, being able to take the next step toward success involves the ability to scale. Max looks at two recent fundraising deals that speak volumes about where the industry is headed.
Waters Wavelength Ep. 326: Connectifi’s Nick Kolba
He joins the podcast to discuss the model context protocol, LLMs and agentic AI.
Euroclear readies upgrade to settlement efficiency platform
Euroclear, Taskize, and Meritsoft are working together to deliver real-time insights and resolution capabilities to users settling with any of Euroclear’s CSDs.
