AxiomSL: asset manager survey reveals data silos a major headache for COOs

The pandemic crisis brought with it an abundance of regulatory stress, deliberation, and change. A prime example was the tightening and then relaxing of EU shortselling disclosure rules and modifications to sensitive industries compliance requirements – a regulations roller-coaster ride for many firms. The difficulties they experienced in responding to these rapidly changing rules across multiple jurisdictions have prompted investment managers to reevaluate their global equity position monitoring capabilities.

To move forward, firms must look to emerging technologies including the cloud, high-performance computing, and AI/ML to automate their operations and increase efficiency. Thus, they are increasingly relying on the expertise of regtech and fintech firms to solve tough upstream data challenges and automate complex downstream reporting processes.

Data silos

Data silos are among the top issues keeping COOs up at night. Of the 20 investment group professionals interviewed for the survey, almost all indicated that data silos create real challenges in their firms. One said: “Data silos exist everywhere. I think even companies that say they are on top of it, are constantly having to review their plans and take a ‘big-picture’ view of their development.”

Looking at data-silo challenges through the lens of managing risk, regulatory data, and supervisory obligations immediately exposes the inherent need for data interconnections across an organization’s many functions. Firms that continue to expand in the US and abroad, for example, face a pressing need to comply with multiple jurisdictions’ rule complexities and nuances regarding foreign share ownership.

Typically, the myriad and frequently changing shareholding disclosure rules are siloed within the compliance function, the daily position data is spread across the firms’ complex fund management entity structure’s front offices – more silos, the essential reference and market data sets are both externally sourced and internally manufactured – yet more silos, etcetera.

Some firms indicated that the biggest problems were caused by external silos because data was being sourced, managed, and held in a variety of different systems. For instance, one COO remarked: “We use a few different data providers for different types of market data. That brings challenges, as there is not one unified reference point. Manging this and managing our data providers as third-party relationships is also difficult; consultants and trust is needed.”

Others pointed to internal silos and the differences between how varying departments use data as a cause for concern. For instance, one organization said that it faced problems because internal departments were not communicating well about how data was being sent out externally. The implications of these silos varied. Among them were inability to meet client demands for ad hoc reporting, lack of consistency throughout the organization, data security worries, operational risks, and regulatory reporting concerns.

One firm indicated that there was a strong need to set up a unified data platform while noting that the next steps were a combination of leveraging technology, cloud infrastructure, off-the-shelf products, and bespoke data services. Another common theme cited was blockchain, with some respondents arguing that this system can provide a structural way to access data.

Environmental, Social and Governance (ESG) data as a service and technical innovations such as machine learning were identified as critical areas of focus for the future, with several firms saying they needed to take advantage of data to support the growth of the firm. One firm said: “Data helps incorporate new artificial intelligence tools, creates a better platform for customer service, and improves data security, trading analytics, and compliance.”

Operating models

Most firms are complex (often laden with legacy systems across a network of recently merged entities) and must wrestle with potentially conflicting factors to arrive at an optimal Target Operating Model (TOM).

What is the right structure: home-grown, outsourced, or a mixture? A number of the respondents noted that there were numerous issues that needed to be reviewed in making the decision between outsourcing and building solutions in house.

Many are eager to embrace new technologies and establish a more efficient, agile way to manage regulatory requirements and streamline their TOM, as indicated in the following key insights:

  • Organizations should re-evaluate their current strategy for regulatory data-management and reporting and leverage what the market has to offer to achieve corporate objectives
  • Firms are relying more on external regtech and fintech providers of digital-based offerings, and recognizing the need for more automation
  • Artificial intelligence (AI), machine learning (ML), and robotics technologies are top of mind
  • Cloud-based solutions are becoming the norm

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