Improving Operational Models Through Data and Innovation

A survey BNY conducted earlier this year to gauge perspectives and expectations on various aspects of operational transformation provides notable insights from leading investors in the region, including global asset owners and managers:

• 79% of survey respondents said they are planning or in the process of enhancing their investment operating model.
• Operational efficiency is the top priority for financial institutions, with 50% of respondents focused on improving operations to support performance and growth.
• Investment data management is recognized as a major hurdle by 58% of clients surveyed, underscoring the critical role of data validated in a timely manner for ensuring smooth and resilient operations.
• The three biggest obstacles to achieving operational transformation are high costs (22%), disruption of stable operations (21%) and complexity (19%).
• AI is expected to have the most significant impact on portfolio management and cash flow forecasting, according to more than half those surveyed.

These trends present both challenges and opportunities for firms in APAC and signal a need to reimagine investment operating models and align operations with the expectations of local investors to drive long-term growth. "Asset owners and managers are rethinking their end-to-end investment operating models to boost efficiency, scale and resilience. This shift is being driven by rapid advances in technology, a thirst for data and rising allocations to private markets,” says Salmaan Nayeer, Head of Commercial Product, Middle Office Solutions, APAC, BNY

Unlocking the data-centric operating model
 

Global asset owners and managers in APAC continue to grapple with the increasing complexity and volume of data. Pre-trade research emerged as the most challenging front-office task, with data management, reporting and security master management also cited as among the most demanding data processes.

Adopting a data-centric approach helps clients to better harness data so they can uncover actionable insights aligned with investment strategies, make more informed investment decisions — and generate alpha.

Open architecture and an agnostic model offer a flexible solution for enabling the seamless integration of data with existing providers and robust middle-office processes. This reduces the friction between front and back offices while making it possible to adapt to any technology platform. Critically, the model should focus on validating the data upfront in the investment operations value chain and ensuring the production of a true Investment Book of Record (IBOR).

To further mitigate operational risk, firms are increasingly outsourcing data management. This approach shifts responsibility for complex processes to trusted partners who can validate data upfront in the front- to middle-office environment. By integrating data across product lines, the data-centric model helps to streamline decision-making and deliver a comprehensive view of critical information across the investment lifecycle.
 

Bridging the gap: Reliable data for private and complex assets

As investor appetite for private and complex asset classes continues to grow amid the hunt for diversified options for enhancing returns, asset owners and managers must adapt to managing both traditional and private assets effectively. A total portfolio view across assets is key to achieving a consolidated investment perspective and making more informed, strategic asset allocation decisions — and doing so faster.

Outsourcing middle-office functions may help to achieve these aims by automating data aggregation and introducing real-time visibility across all asset classes. In particular, this can be done with trade processing, reconciliations and collateral management, which respondents consider to be the most suitable post-trade investment operations tasks for outsourcing, given the commoditized nature of these activities. These activities can then facilitate the maintenance of the IBOR by an experienced service provider with a globally consistent platform.

This approach also allows for increased focus on strategic priorities as operational processes are streamlined. With increasing regulatory demands and the management of complex assets requiring precision and agility, this is particularly valuable in today’s financial environment

AI integration: From vision to execution

The prevalence and increasing sophistication of AI and other cutting-edge technologies provide asset owners and managers with new — and increasingly compelling — options to enhance investment performance.

AI is shifting from a conceptual promise to a practical application across investment operations. According to the survey, 58% of respondents already see AI being applied in both portfolio management and cashflow forecasting, with additional interest in areas like know your customer (KYC) and compliance monitoring. These developments suggest AI is becoming a core component of current operational strategy rather than an option to consider in the future.

In response, firms are re-evaluating their investment operating models, with many embracing operational transformation to streamline workflows and enhance scalability. This reflects a broader trend toward integrating advanced technologies into daily business operations, with data-led approaches increasingly shaping how firms operate and grow.

Rather than serving as a standalone tool, however, AI is becoming part of a broader effort to modernize investment models. As adoption grows, the focus is shifting from experimentation to execution, and innovation is no longer optional, but rather a core driver of sustained impact and measurable outcomes.
 

Transforming models for long-term success

Transitioning to new data-led operating models, while not an easy undertaking, can yield long-term strategic benefits by streamlining processes, reducing risk and helping firms to sharpen their focus on core capabilities.

Costs, the potential for disruption and the complexity of implementation are the key factors that need to be considered. Many firms have experienced setbacks because they underestimate the difficulty of integrating new systems, aligning stakeholders or maintaining operational continuity throughout a transformation. However, ignoring the need may pose even greater risk.

Ultimately, firms that embrace the transformation process by centralizing operations and integrating data and functions will be better positioned to meet evolving client demands and unlock greater transparency, scalability and resilience across the investment lifecycle.

Middle-office solutions: Our scalable, end-to-end solutions help clients improve operational efficiency by simplifying trade support, data integration and reconciliation processes. [Learn more]

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