“Agile, dynamic, and real-time” are key front-office data requirements. But they can be difficult to reconcile with the industrialized data management and quality certification processes governing the middle and back offices.
Ultimately, the challenge the industry is trying to address is that of putting a portfolio manager in a position, before their market opens, to have all the required information lined up—accurate, timely, and complete—so that they can run the workflows and make investment decisions on behalf of their clients.
A front-office user needs good positions data, but that is not all that matters. Equally important are the nature and context of that position. For example, if a portfolio manager is looking at cash, is it “trade date” cash, “settlement” cash, “good” cash, or is it “still being reconciled” cash? Similarly for reference data—be it traditional market information such as prices, indices, and benchmarks, or more novel sources like environmental, social and governance (ESG), investor behaviors, or sentiment indicators—portfolio managers need to know the source, whether it has been applied correctly, and if it is complete. It’s not good enough if only 80% of the portfolio has been enriched with the right reference data sets and 20% of the positions have serious gaps, meaning some analytics aren’t quite complete and probably cannot be calculated.
The cash positions, the reference data and the analytics all need to line up. You wouldn’t typically understand that so well if you were just looking at it through the lens of a custodian, or even a middle office. You have to be in the portfolio manager’s chair, looking at the full suite of analytics at a security and portfolio level, and understanding how those positions are made.
Having a close understanding of the investment decision-making process also helps when managing time constraints. One of the things we hear all the time is, “I’d like my data to be more timely. I want real-time everything—real-time positions, real-time cash.” Adequately managing these challenges requires an in-depth understanding of the investment process itself.
The key questions are: how “real time” do you really need this data to be, and what context do you want around it? Is the current workflow the only way to drive the outcome, or can that workflow be configured differently? Answering these questions requires the perspective of understanding what the portfolio manager is trying to do, or what the algorithm is trying to do with that data. Often, upon closer investigation, what managers really need is to have an update before 10am, or every couple of hours, rather than in real time.
The Asia-Pacific region faces a somewhat unique set of time zone-related challenges that need to be understood and managed. If the core business processes of a data vendor or service provider are geared around North America, then that is going to leave a lot of people in Asia-Pacific markets a little underserved. Also, if you have global portfolios with data needs across different regions, you have to get into the details of what really matters when there are multiple definitions for market open and end-of-day. Being able to control that data flow at the portfolio level is key as we move away from the once-a-day batch delivery model from five or 10 years ago.
These days, the time between data arriving, being normalized and being applied has been reduced from 12 or 24 hours to minutes or seconds.
A global, 24/7 “follow the sun” operating model has always been our strength. It is critical for any global investment teams and portfolio manager. We are extending the concept into data servicing to support global, multi-region start-of-day requirements by applying standard and custom operational control checks to remediate data on our clients’ behalf. Our client service team monitors and reports on agreed SLAs and KPIs, providing transparency via client dashboards.
I’m excited about State Street partnering with major technology providers who have developed great capabilities, such as Microsoft’s Azure cloud infrastructure, to continue solving some of these hard problems.
The trend toward outsourcing of data management is shifting more into the mainstream. Data-as-a-service is attracting both asset managers and asset owners alike, where the need for timely, accurate and complete data is becoming increasingly important. They are looking for a data custodian who can hold onto the data, steward it, organize it, deliver it in a number of ways, provide connectivity through APIs, and be the golden source copy.
Marko Milek is a managing director and APAC Head of Data and Analytics at State Street in Singapore. He is responsible for managing and developing State Street’s data, analytics, research and advisory functions in the region.
Further reading
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
An inside look: How AI powered innovation in the capital markets in 2024
From generative AI and machine learning to more classical forms of AI, banks, asset managers, exchanges, and vendors looked to large language models, co-pilots, and other tools to drive analytics.
As US options market continued its inexorable climb, ‘plumbing’ issues persisted
Capacity concerns have lingered in the options market, but progress was made in 2024.
Data costs rose in 2024, but so did mitigation tools and strategies
Under pressure to rein in data spend at a time when prices and data usage are increasing, data managers are using a combination of established tactics and new tools to battle rising costs.
In 2025, keep reference data weird
The SEC, ESMA, CFTC and other acronyms provided the drama in reference data this year, including in crypto.
Asset manager Saratoga uses AI to accelerate Ridgeline rollout
The tech 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.”