The Role of Asset Reference Data in Enhancing Treasury Operations

Today's macroeconomic conditions are rapidly evolving, banks are adapting, and the most advanced treasurers know how to take advantage of it. From high interest rates to global economic uncertainty, banks are compelled to increasingly explore new strategies in creative ways. Banks are looking for additional non-interest income streams, grappling with the growing complexity of financial instruments and regulatory requirements, and overwhelmed by both the need for and the amount of asset reference data.

This article explores how these macroeconomic factors are reshaping treasury operations, driving a shift from reactive to proactive and predictive strategies, and highlighting the critical role of asset reference data in navigating this complex environment.

Macro conditions drive treasurers to re-evaluate their strategy

Recent years have been marked by high interest rates, a topic of much industry discussion. This environment has already begun to transform the banking sector, with significant alterations in risk-weighted asset (RWA) calculations, a portion of lending authority now in the hands of non-traditional asset managers, and mounting market unpredictability. Currently, interest rates are in decline and the future trajectory is difficult to predict, given the uncertainty spurred by Trump’s victory, though rates have thus far appeared to continue to slowly fall. However, given the high demand for liquidity, deposits have yet to adjust, maintaining pressure on net interest income and keeping banks from becoming complacent. This unparalleled interest rate volatility demands scrupulous observation.

This past July, RSM noted that "in less than a year, the swing in the 10-year yield has moved more than 350 basis points in both directions, a volatility not seen since the 2008−09 financial crisis."¹

The processes which treasurers previously managed using static data and infrequent data updates are no longer sufficient. They require more frequent updates to their analyses, and are under increasing pressure to monitor more data, more thoroughly, and at an increased frequency.

Increase in non-interest income

Given the squeeze on net interest income, banks are leaning more heavily on non-interest income such as investment banking, refinancing, and asset management fees. 84% of participants in a 2024 KPMG M&A deal market study said they expected their deal volume to be greater in 2025 than in 2024.² Deloitte's outlook also referenced a recent US Bank earnings report which cited a re-invigorated M&A pipeline.³ This signals favorable conditions for investment banking fees, presenting increased corporate action activity which treasurers must monitor closely. Per Deloitte, "overall, noninterest income as a percentage of average assets is estimated to increase to nearly 1.5%, based on Deloitte estimates, the highest in the last five years."³

Instability in FX markets

Recent shifts in central bank monetary policies, paired with geopolitical and other considerations, have generated pronounced instability in FX markets. "Volumes on key [FX] trading venues soared to new records and hit multi-year highs as activity picked-up as much as 70% in the first seven business days of August".⁴ The 1970 Herstatt collapse, which indelibly linked Herstatt Bank with FX settlement risk, has imparted a valuable lesson. Treasurers are now more than ever tasked with the strategic management of the substantial liquidity risk engendered by these dynamics.

Agility in an evolving regulatory environment

Recent years have seen a profound shift in the regulatory environment for sell-side banks, marked by higher capital requirements, rigorous stress testing, and intensified scrutiny of risk management procedures. While the Trump administration may lead to a relaxation of capital requirements and a potential softening of the Basel III Endgame, banks must remain agile, given the ever-evolving nature of regulation. The key is to be prepared for change and to swiftly adjust to new regulatory demands.

Asset reference data emerges as an essential resource

Such macro conditions are compelling treasurers to reconsider their approach, transitioning from a reactive to a proactive stance, with asset reference data as the linchpin.

In recent years, the importance of asset data has risen significantly. Financial instruments have become more sophisticated, with derivatives and structured products becoming more prevalent. One such instrument is synthetic risk transfer (SRT), which has seen increased usage in recent years and requires large amounts of data to be transparent. Regulatory frameworks such as Basel III Endgame call for precise and timely data reporting across numerous asset classes and originating from multiple systems and locations.

The modern treasurer

The modern treasurer must navigate a landscape of increasing complexity, stemming from the greater use of technology in finance and the consequent upsurge in data volume and diversity. While technology offers new possibilities for data utilization, it also imposes heightened data management demands to maximize its potential. For example, AI applications require extensive, quality data sets for training. Recognizing their role as guardians of the definitive financial record, treasurers and their data operations teams must collect, cleanse, and distribute data throughout the organization.

The availability of comprehensive data empowers treasurers to enhance decision-making, achieve collaboration with other bank divisions, and helps to ensure a clear view of all risks within the institution. To this end, they must acquire, compile, and access data from diverse sources. In the present climate of cost-consciousness, the imperative is to achieve these goals in a cost-efficient manner. Treasurers must, therefore, master the art of leveraging technology to optimize their return on investment, and to scale operations without a concomitant rise in manual workload or labor needs.

Today’s most impactful reference data

In the era of advanced technology and big data, one might wonder if there can ever be too much information running through our brains. The answer in almost all cases, surprisingly, is no. The significance of data completeness cannot be overstated. Incomplete data leads to decisions made with blind spots, regulatory scrutiny and fines, and the training of unreliable AI models.

To ensure that the most important bases are covered, the following types of asset reference data have gained importance under current conditions.

• Capital transparency: treasurers require comprehensive access to the sources and uses of capital. Aggregating source data of inventory and collateral enables the bank to understand optimal uses of capital and what has been deployed for funding. This increases liquidity availability, optimizes funding, and ensures regulatory compliance.
• Economic asset reference data: includes data such as interest rates, inflation, and consumer pricing indices, which is necessary to monitor interest rate volatility, allowing the bank to reposition strategies as desired. Inflation tracking is also essential. This time-series data is critical, requiring storage with both effective date and knowledge date time horizons to enable the linkage of changing analysis outputs to their economic drivers.
• Valuation and pricing data: used in many downstream processes, and intraday updates are important to track rapid market changes. Many downstream processes that rely on pricing data are batch-oriented. To maintain data accuracy, valuations should be obtained and vetted regularly before publishing downstream. The central treasury function manages a wide array of asset classes, each with its own set of market data providers and valuation policies, so regular cleansing is paramount to resolving discrepancies between vendors. During periods of market turbulence, it is crucial to continuously assess the impact on both the RWA and capital adequacy calculations. Therefore, the system responsible for pricing validation and exception management should support multiple vendor feeds, side-by-side comparisons, and a robust exception workflow.
• Corporate actions: influenced by the increase in M&A activity, corporate actions now need to be processed at scale. Given the surge in activity, firms must ensure that all M&A activity is captured in the security master. This increases in importance as banks rely more heavily on investment banking fees, where research and investment banking teams can use analysis of this data to identify potential business opportunities.
• Credit ratings and risk metrics: to accurately assess risk, financial institutions must also closely monitor credit ratings and other risk metrics of their borrowers. This includes traditional lending activities and any partnerships or investments with private credit firms. Banks must have access to this data to make informed decisions and mitigate potential risks. Research and investment banking teams can also use this data to identify potential business opportunities.
• Changing regulatory reporting requirements: this seems to always include new identifiers, such as security identifiers (ISIN, CUSIP, and SEDOL) and counterparty identifiers (BIC and LEI). Additionally, as regulations continue to evolve, having access to up-to-date identifiers drives compliance and prevents penalties.

How asset data streamlines treasury and financial resource management

The key to achieving comprehensive capital and liquidity stress testing across various market scenarios is a foundation of robust and reliable asset reference data. Forward-thinking treasurers are conducting stress tests per the Basel Committee’s guidelines as well as with their own scenarios, underpinned by meticulous economic analyses. Access to many asset reference data from diverse sources equips treasurers with a holistic perspective of their financial standing, enabling them to adapt effectively to new market conditions.

Integrated data & risk management

The data fabric established by the data mesh architecture serves as the authoritative source for asset-related data across the bank, promoting uniformity and precision throughout the numerous systems in a typical infrastructure. By centralizing data management and controlling domain-specific data distribution, this framework upholds data quality, enabling teams to utilize trustworthy, consistent information. This in turn encourages collaboration and nurtures a data-driven culture with empowered employees and innovative operating models.

A shared understanding of data is also the foundation for integrated risk management. A 360-degree view of risk enhances decision-making processes by facilitating access to precise and dependable asset data for treasurers and financial resource managers. Such analyses and decisions are best conducted through a collaborative approach involving treasury, financial resource management, risk management, and compliance teams. Interconnectedness is an inherent feature of the financial markets; therefore, it follows that a holistic approach to risk is essential for an accurate evaluation.

Importance of alternative asset reference data

Advanced technologies, such as SWIFT's updated format ISO 20022, often necessitate supplementary asset reference data. For instance, in streamlining payments and settlements, SWIFT ISO 20022 messages require additional asset reference data. Without this data, banks will be stuck using SWIFT ISO 15022 and a less streamlined settlement process. Other financial processes, such as reconciliation, can be bolstered by the inclusion of additional asset reference data. More sophisticated reconciliations are characterized by higher levels of automation, enabling tasks like matching line items based on security attributes beyond the available identifiers. As industry convergence continues and more market participants enter private markets, security identifiers become less reliable, and the importance of other reference data grows.

Centralizing the source of truth

To address these requirements, banks must implement a scalable, centralized security master across all asset classes. The system should feature a comprehensive capital-markets aware data model, reducing the time needed for initial implementation. Scalability is crucial for accommodating the vast data requirements of large banks. Additionally, the flexibility of the data model, which should allow for a multitude of user-defined fields, is necessary for adapting to evolving business needs, regulatory updates, and the integration of new technologies.

Technology as a strategic enabler for effective asset reference data management

Banks often source data from multiple vendors, receiving it in various formats. The challenge lies in integrating, ingesting, and storing this data in a manner that is not only accessible but also seamlessly blends with other datasets. This is where modern technology steps in, offering automated solutions to streamline these processes. Automating the collection and validation of asset reference data significantly reduces manual effort and minimizes errors. By implementing programmatic data governance frameworks, banks can establish robust data quality standards, ensuring the integrity of their asset reference data. Furthermore, the more data used to train AI tools, the better they become at assisting with data management tasks, creating a virtuous cycle of improved data quality and enhanced operational efficiency.

The increased availability of asset reference data unlocks opportunities to leverage advanced technologies. Modern technology also offers the flexibility and resilience that are crucial in today's volatile financial environment. Establishing a data mesh architecture allows banks to swap out specialty systems and adapt to changing needs without compromising data integrity.

Centralized storage solutions, coupled with a data mesh architecture, maintain data integrity and ensure that all teams across the front, middle, and back offices have access to a centralized security master. This approach maximizes the ROI of technology investments by democratizing data access and enabling more informed decision-making. As HSBC noted, boards now expect treasurers to “demonstrate that they have a firm grip on the resilience of their systems, processes, and counterparties/partners.”⁵ By adopting these technological advancements, banks can meet these expectations and navigate the complexities of the financial landscape with greater agility and confidence.

The future of asset reference data

As the financial landscape continues to evolve, asset reference data is set to play an increasingly critical role. The future will see a rise in the complexity of financial regulations and the volume of financial transactions, making high-quality asset reference data indispensable.

One of the key drivers of this trend is the growing adoption of Ai and data science in financial services. These technologies rely heavily on accurate and comprehensive data to make informed decisions and predictions. As AI and ML become more integrated into treasury and financial resource management, the demand for high-quality asset reference data will surge. This data will be essential for training algorithms, enhancing predictive models, and automating processes, ultimately leading to more efficient and effective financial operations.

The evolution of technology will also unlock new opportunities for leveraging asset reference data. Emerging technologies such as blockchain, cloud computing, and advanced analytics will offer innovative ways to collect, store, and analyze asset reference data. These advancements will enable treasurers to gain deeper insights into their financial positions, identify trends, and make data-driven decisions that enhance financial performance.

Centralized, automated, and real-time data is possible

Core to this future is the ability to store and manage asset reference data in a centralized security master. A centralized approach ensures data consistency, reduces redundancy, and enhances data integrity. Treasurers who adopt this strategy will be better equipped to streamline their operations, improve risk management, and optimize their financial resources. By having a single source of truth, treasurers can eliminate data silos, reduce manual errors, and enhance collaboration across different departments.

Moreover, the future of asset reference data will be characterized by increased automation and real-time data processing. Automated systems will not only reduce the manual effort required to manage asset reference data but also ensure that the data is up-to-date and accurate. Real-time data processing will enable treasurers to respond quickly to market changes, regulatory requirements, and other external factors, thereby improving their agility and competitiveness.

The future of asset reference data is poised for significant growth and transformation. As financial regulations become more complex, AI and ML gain prominence, and technology continues to advance, the importance of high-quality asset reference data will only increase. Treasurers who invest in centralized, automated, and real-time data management solutions will be well-positioned to navigate the challenges and capitalize on the opportunities that lie ahead.