Scotiabank Turns to Cloud GPUs for Risk Calculations
The Canadian bank has significantly improved the time it takes to run XVA calculations, and has big plans to further expand its XVA cloud GPU program.
At the end of 2016 into 2017, Scotiabank initiated a project that would allow it to use cloud GPUs to run its valuation adjustments (XVA) program. With the project gaining traction, the results have been impressive.
According to the bank, the runtime for risk calculations and derivatives pricing using cloud GPUs is 30 times faster, allowing brokers to deliver more accurate derivatives pricing in 20 seconds, which would previously have taken 10 minutes. It also allows for more nuanced risk
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: http://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 Data Management
Asset manager Saratoga uses AI to accelerate Ridgeline rollout
The OMS provider’s AI assistant helps clients summarize research, client interactions, report generation, as well as interact with the Ridgeline platform.
CDOs evolve from traffic cops to purveyors of rocket fuel
As firms start to recognize the inherent value of data, will CDOs—those who safeguard and control access to data—finally get the recognition they deserve?
It’s just semantics: The web standard that could replace the identifiers you love to hate
Data ontologists say that the IRI, a cousin of the humble URL, could put the various wars over identity resolution to bed—for good.
The art of communication: Data pros need better messaging
As the CDO of a tier-one bank puts it, when there’s an imbalance in communication between the data organization and the business (much less other technology heads) “that creates problems.”
Does TP Icap-AWS deal signal the next stage in financial cloud migration?
The IMD Wrap: Amazon’s deal with TP Icap could have been a simple renewal. Instead, it’s the stepping stone towards cloudifying other marketplace operators—and their clients.
T. Rowe Price’s Tasitsiomi on the pitfalls of data and the allures of AI
The asset manager’s head of AI and investments data science gets candid on the hype around generative AI and data transparency.
Waters Wavelength Ep. 298: GenAI in market data, and everything reference data
Reb is back on the podcast to discuss licensing sticking points for market and reference data.
Back to basics: Taxonomies, lineage still stifle data efforts
Voice of the CDO: While data professionals are increasingly showing their value when it comes to analytics and AI adoption, their main job is still—crucially—getting a strong data foundation in place. That starts with taxonomies and lineage.
