Congrats to the BST Award Winners, as Data/Risk Rule the Day
The crop of entrants for this year's Buy-Side Technology Awards was excellent. I know that many were left disappointed after we received hundreds of entry forms, but please know that the judging panel took this job very seriously and it wasn't easy picking one winner for each of the categories.
[To view a full list of the winners, please click here.]
Let me just say, though, that common themes for innovation were in the realms of data management and risk management. There were dozens of entries describing the IT challenges around storing data, reporting that data, disseminating the data, having accurate data, and getting that data in a timely fashion. And most of these data projects were feeding some sort of risk-related function.
While there were awards for the Best Data Management Product (won by Markit) and Best Risk Management Initiative (won by LCH.Clearnet), many of these winners were developing solutions around data and risk.
This jives well with what was discussed at this year's Buy-Side Technology North American Summit a few weeks ago. Here are two key takeaways from that event:
Data Management: An Ever-Growing Importance/Challenge
Garbage in; garbage out. It's a saying that gets thrown around a lot in this space, but with the massive quantity of data that is being produced for analysis, bad data has a way of seeping into a firm's overall data architecture, producing unwanted results.
As one head of technology for a large and successful hedge fund told Tim: "You can build the best piece of hardware in the world, but without the data it's garbage."
Whether it's in setting up an effective enterprise data management (EDM) system, investing in new risk models and platforms, or building out an investment book of record (IBOR), the data that underpins that is crucial. And it's more than just having that data; you have to be able to effectively incorporate and analyze it.
Risk Management and the Buy Side
It's no secret that data drives risk management. Yury Dubrovsky, the chief risk officer of Lazard Asset Management, said during the event that the buy side is lagging behind the sell side when it comes to risk.
As Jake wrote: "Dubrovsky says he doesn't believe the sell side's effective embrace of risk has trickled down to the buy side." While buy-side firms have invested significantly in risk platforms and models, there is still a lack of human knowledge as to how best to use that information. This came on the back of a previous statement made by TowerGroup analyst Dushyant Shahrawat that portrayed a more optimistic expansion of risk capabilities on the buy side.
And responding to Misys senior risk advisor Bradley Ziff, who called for a "vast increase" in the types of risk analytics that buy-side firms make available to themselves, Dubrovsky stressed that simply having the analytics is not the end game.
"I agree that you need to have the best risk analytics possible, but if you don't know what to do with it, it doesn't matter," he said. "You can pay zero or $5 million-it's useless. If the culture of the company is not to absorb that information and do something with it, it's a waste. It requires a cultural shift within the firm."
Feel free to reach out via email (anthony.malakian@incisivemedia.com) or phone (646-490-3973) to discuss these topics, or ways to improve your awards submission for 2014.
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 Data Management
The Big Bang—a complex 40-year data journey yet to reach its destination
In this guest column, Finbourne’s Gus Sekhon reflects on the deregulation and privatization of the London Stock Exchange and what it meant for data.
Semantic density: old wine, or a new vintage?
Giving AI agents enough context to carry out enterprise tasks has become a priority for firms building them, but it’s expensive. It might not have to be.
Firms get AI access to LSEG data via DataBP admin layer
LSEG has expanded its agreement with DataBP to enable customers’ AI-based tools to request and evaluate data from the exchange and maintain more comprehensive usage records.
Rimes builds agents for exception management
The vendor aims to improve its data foundations to allow for greater agent autonomy.
The great migration: Firms work to integrate ISO 20022
Banks and asset managers are working to adopt the new messaging standard, but it’s easier said than done.
PostSig, CJC team up to run data management for London broker
In the first such deployment between the vendors, CJC will act as an outsourced data administrator using PostSig’s technology to manage the firm’s data.
Buy-side firms warn semantic layers not a quick fix for AI integration
Semantic layers promise to teach AI what a firm’s data means. Keeping that meaning current is the part that may get overlooked, tech heads warn.
Mind the stack: the foundation markets run on
Exchange data is an underappreciated component of the AI era, writes Jeff Kimsey.