Whether the issue is quality, quantity or availability, data management is a persistent problem in the asset servicing industry
Effective data management is an issue plaguing the asset servicing business. With the quantity of data available constantly on the rise, reporting requirements evolving and increasing at pace and legacy systems still holding back a significant portion of the industry, “everybody I speak with has a problem in this area,” says Steven Strange, head of product for asset management at ION Markets.
The range of data management headaches is constantly increasing, says Richard Anton, chief operations officer at CIBC Mellon. Standardisation, inaccuracies, expectations around the modelling of unique securities, performance result analysis and more all add to firms’ workload.
Alongside increased data quantities comes greater security concerns. “There’s a delicate balance between making data accessible and keeping it secure,” he explains. “Our clients are seeking the ability to access, analyse and connect data to drive informed decisions” — but they must also ensure that only those with authorisation can retrieve that information.
“Navigating today’s continuum is no easy feat,” Anton continues. He suggests that the industry is “recognising a tipping point” and leaning towards advanced technological solutions and collaborative frameworks to improve the resiliency, efficiency, accuracy and timeliness of data for all market participants.
While data quantity has often been a challenge in the past, broader availability now is both a blessing and a curse. According to ION’s Strange, the issue lies in “how you put the data into different applications, and how you check the quality”.
Ensuring data quality and integrity is vital, but when a variety of sources are being drawn on, the process of doing so can be complex. Relevant reports need to be identified and run, and manual work remains a key part of the process. Even if aspects can be automated, these procedures “still generate a report that someone has to deal with”, Strange comments.
With the industry currently facing “a huge range of disparate and disconnected data sources, both public and private. [CIBC Mellon] recognises the importance of enabling a more robust and diverse data supply chain as clients build for the future”, Anton reports. The company aims to enhance the data security space, with selective sharing and more efficient integration high on the priority list. This is something that customers are demanding; there’s “a need to create new products and services tailored to client opportunities and strategic direction”, he confirms.
“Drawing insights from unstructured and disparate data is the most fundamental challenge facing the investment industry, particularly in the private market space,” shares Davit Harutyunyan, director of product for data at Allvue Systems.
He goes on to say that companies are producing valuable data themselves, and in large quantities, but cannot extract meaningful insights from it due to inappropriate, inconsistent formats and multiple data silos.
These silos operate in “different dimensions”, adds Will Thomey, co-head of business development at Acadia. These ‘dimensions’ may be based on process, around pre- or post-trade; market or transaction type; line of business, or any number of constraints, such as technological capabilities. As such, there is no authoritative source of data and firms “are often comparing their version of data to their counterparty or client”, he concludes.
Reporting on the rise
On top of this, as in all areas of the industry, evolving regulation plays a role in the data management world. “From ESG to investor fee reporting, regulatory bodies around the world are implementing new rules that force investment managers to draw out new data and metrics that many have not had to report on before,” says Allvue’s Harutyunyan. These added obligations require faster and more accurate data management and require firms to make considerable changes to their operations.
In the US, “many private equity managers are grappling with the impact of the SEC’s new reporting rules approved during summer 2023 for private fund managers”, he continues. These rules, with a compliance date set for 2025, have left forms “scrambling” to track, collect and report relevant data each quarter. “Those who are already committed to a holistic, firmwide data strategy will have a far easier time solving this challenge.” As this situation replicates across jurisdictions, it provides further motivation for firms to take action now.
ION’s Strange states that “regulators need to consider the amount of data behind reporting when they’re coming up with these extensive rules.” Larger firms have far more resources at their disposal and are able to allocate sufficient time and money to meeting requirements, but smaller firms are “often either going to make mistakes or become non-competitive in their own business,” he explains, regulatory reporting becoming such an overwhelming part of their operations that they’re unable to do anything else.
Acadia’s Thomey is sure that financial firms are well aware of the importance of good data management; after all, any shortfalls are likely to incur penalties such as fines and enforcement actions. As such, the use and control of data, data lineage and data accuracy accountability are key priorities, although these operations can accrue considerable costs.
ESG reporting, an increasingly prevalent element of firms’ regulatory responsibilities, is a particularly challenging area. Data is difficult to source, not only due to inconsistent definitions and varied methods of measurement, which make it hard to compare results from different companies, but because firms can be hesitant about disclosing their practices in this space. Without improvements in transparency around ESG disclosures, along with a concerted effort to harmonise reporting methodologies, this problem is unlikely to go away. This also demands a commitment from companies to share their data in good faith.
Searching for solutions
When firms are gathering information from such a range of providers, it’s essential to have data committees and audit teams in place, says CIBC Mellon’s Anton. These crucial roles help to guide companies’ data strategies, ensure consistent quality and verify data integrity, providing oversight across both internal and external data sources. Allvue’s Harutyunyan reinforces the point that collaboration is key when it comes to making industry-wide change. As firms work to develop a comprehensive data strategy, “it is imperative to partner with the vendors and service providers that can bring the expertise and products to resolve complex issues”. Implementing such a strategy tends to be a multi-year project, and companies must be confident in those they’re relying on to ensure consistent and valuable progress is made.
CIBC Mellon’s Anton comments that “there is an indispensable link between innovation and data”. Perhaps the most visible innovation of recent years has been the acceleration of AI capabilities, and just as the rest of the industry — and the world — those in the data management space are considering how the technology could benefit their operations.
In a chicken-and-egg situation, “without following data quality best practices throughout an entire firm, teams will be unable to take full advantage of the benefits that AI brings”, says Allvue’s Harutyunyan. On the other hand, AI could be instrumental in allowing firms to wrangle the quantity of data now available to them. As the two continue to progress, there’s a lot of potential for mutually beneficial interactions and use cases. One such example lies in the investment compliance space. Currently, firms inform clients of how they should invest — and what guidelines they must operate within — in the form of a document saturated with legal jargon. Converting that into actionable insights is a manual-intensive, expensive process, and one that AI could accelerate. “It can’t do it all, but it can start to figure out that language so you can read it faster,” ION’s Strange explains, allowing users to determine what data they need at pace.
Industry experts are quick to warn that AI isn’t a fix-all solution. While Harutyunyan confirms that it’s now “making a material impact on managers’ fund operations and workflow efficiency”, a lack of trust in the technology remains. While document summarisation is a space that many firms are looking towards when considering new AI use cases, ION’s Strange comments that “there’s a lot of nervousness” that such a system may not perform as good a job as its human counterpart. It can be a helpful tool, but some manual intervention remains necessary, for now.
T+1
The forthcoming shift in the US, Canada and Mexico to a T+1 cycle for equities settlement will substantially reshape how firms manage static data and settlement information.
The capital markets space has already made an “urgent call” for intelligent data automation ahead of the shift, according to a report from Coalition Greenwich and Xceptor. As data demands become more complex, the speed at which operations must be completed increases and the margin for error grows ever narrower, manual processes are becoming unable to keep up.
T+1 is amplifying existing data quality issues in the industry, ION’s Strange observes, “putting the spotlight” on any mistakes resulting from bad data. “If companies haven’t got a plan in place — which I would hope most people do by now — these problems are going to accelerate very quickly.”
According to the report, as of November 2023 nearly a third of financial institutions were using manual processes to cleanse data more than 50 per cent of the time.
Half of all respondents reported using proprietary, labour-intensive services for these processes. In an accelerated settlement environment, these time-consuming methods are no longer fit for purpose.
“It’s going to be stressful,” says ION’s Strange, considering the implications of the shortened cycle. The window to rectify missing data issues will be far smaller, and the industry “is going to have to leverage what technology is out there to check that the data is okay”. Beyond the technology, employees are going to be expected to work after trading hours to fix any problems that come up, he predicts.
“The main problem, for fixed income and equities markets, is their overall size,” Acadia’s Thomey adds. Issues with data quality can have cascading effects, with issues such as delayed data, reconciliation issues and operational complexities increasing settlement fail rates and, subsequently, funding and fail costs.
To prevent catastrophes, secure communication between counterparties and custodians must be maintained, says CIBC Mellon’s Anton. He also emphasises the importance of consuming real-time data to enable exception management and corrections procedures to be completed as quickly as possible.
Although the upcoming change will be hugely impactful on markets globally, it’s not without precedent. Some areas of the industry are already operating on a trade day settlement basis, and other jurisdictions have settled into T+1 environments. The main focus in this case is therefore not to support a novel process, says Acadia’s Thomey, but rather to eliminate operational friction.
“There are beneficial processes and technologies that can be adopted to make the shift to T+1 for fixed income and equities markets” — which will be most directly impacted by the change — “less burdensome for market participants,” he reassures. These solutions usually reconcile disparate data or automate settlement processes, reducing manual processing requirements.
As T+1 go-live dates rapidly approach, firms who have not yet constructed, implemented and familiarised themselves with a robust data strategy will be at an overwhelming disadvantage. Once again, an accelerated settlement cycle has provided an impetus for the industry to make significant changes to its operations; continuing as usual is no longer a viable option.
What’s to come
ION’s Strange warns that data management issues are “only getting worse”, due to both the volume of data available and the subsequent problem — and cost — of storing it. “People found this difficult 10 years ago, and they find it way more difficult now unless they have mature data transformation plans in place.”
“As a service provider, we know that simply delivering data will no longer cut it,” affirms CIBC Mellon’s Anton. “The challenge lies in surfacing data quickly to capitalise on opportunities and address market volatility.”
With the financial services landscape constantly evolving, whether by external factors or regulatory changes, firms must work to keep up with the demand. It may seem like a never-ending race, but slowing down isn’t an option if businesses want to remain competitive. Challenges may persist, but so must the industry.
