As investment firms expand, they often encounter performance attribution reporting gaps. With growth in portfolios to manage, strategies to execute, and data to analyze, reporting can quickly become a considerable pain point. Accuracy, transparency, and consistency all come under pressure with scale.
However, organizations do have options for how to resolve investment performance attribution. Modern technology connects data sources, reduces manual reporting requirements, and standardizes attribution. Find out how it works and why it matters in this article.
Key Takeaways
- A growing firm can face many challenges with performance attribution reporting, often due to data completeness, freshness, and accuracy challenges.
- Gaps in performance attribution reporting impact the ability of investment managers to make the best data-driven decisions.
- Organizations that adopt modern data investment management platforms can close the gaps and ensure consistency and accuracy in reporting.
Why Performance Attribution Reporting Becomes More Complex as Firms Grow
Growth is not a bad problem to have for any business. It does create some complexities. In investment management, an increased client roster and the ability to probe more data sources do impact portfolio attribution analysis.
Why is this? There are several causes, including:
- Expanding asset classes
- A greater volume of data from multiple sources
- The need to develop customized benchmarks for clients
- Disparate technology platforms
- More rigid compliance standards
All these things contribute to performance attribution analysis gaps. Without solutions for these challenges, firms could incur more risk and not be able to communicate completely why portfolios performed well or poorly. If investment managers cannot be clear about the investment decisions that drove gains or losses, it can erode trust and derail client relationships.
Disconnected Data Sources Create Incomplete Attribution Reports
Data-driven decision-making has become the norm in investment management. The insights gleaned are the product of multiple data sources. When organizations struggle with integration, aggregation, inconsistencies, and missing information, they can’t be confident in attribution results.
Data often lives in silos, making it difficult to combine and evaluate as a whole. This impacts visibility when it comes to attribution reporting. Legacy technology is often the reason for disparate data sources. They lack the architecture to integrate easily with APIs (application programming interfaces). This leaves organizations with no clear path forward for data integration.
To overcome this challenge, firms are adopting investment management software built around an Integrated Master Data Model (IMDM) that centralizes investment data across front-, middle-, and back-office workflows. With investment data centralized and normalized, firms can more efficiently analyze portfolio information, generate reports, and support data-driven decision-making.
When companies have a single source of truth for data, this ensures that all users have access to the same information.
Manual Reporting Processes Increase the Risk of Errors and Delays
Manual processes are a leading cause of performance attribution reporting gaps. When investment managers have to manipulate spreadsheets, it’s time-intensive and subject to human errors. Even if these are shared documents, it’s not the same as having software that drives and automates workflows.
Additionally, manual reconciliations are risky and require lots of labor. They slow down the ability to produce timely attribution reports, which will only become worse with growth.
Firms can eliminate these issues by implementing technology that covers the entire process. One key capability is workflow automation. Automating repetitive data and reporting processes can reduce manual intervention, improve efficiency, and lower the risk of human error. When systems can automate repetitive tasks, the risk of human error decreases while efficiency increases.
Limited Data Standardization Impacts Attribution Accuracy
Not all data has the same format. As a result, organizations have difficulties with consolidation and analysis. Ideally, data definitions, formats, and calculations should be consistent.
Investment data often originates from multiple systems, providers, and formats, creating challenges around consistency, reconciliation, and validation. Without standardized data definitions and a centralized framework for managing that information, discrepancies can flow through to downstream analytics and reporting.
While data standardization has long been a burden, new investment management platforms can centralize this into one bucket for analysis. When organizations have this level of control and capabilities, they can trust attribution accuracy.
Growing Firms Struggle to Scale Attribution Reporting Across Portfolios
With growth comes the need to scale activities, which means technology is critical. What does scalability actually mean in this context?
It’s the ability to operate reliably when clients and data increase without interruption. Firms need to be able to apply new strategies and add new funds and investment vehicles to their operations.
Scaling also hits bottlenecks when organizations:
- Use fragmented legacy tech stacks.
- Manage complex multi-asset classes
- Require increasingly granular transparency and auditability that can be difficult to support efficiently across fragmented legacy environments
Scaling, however, doesn’t have to be so complicated. Cloud-native portfolio accounting software provides greater operational scalability, allowing technology infrastructure to adapt as firms, portfolios, and data volumes grow. Legacy systems get replaced, providing more robust functionality in terms of managing many types of assets and supporting audit-readiness.
With a strong technology layer providing scalability, firms don’t need to worry about downtime, latency, or slow data analysis. These capabilities boost performance attribution analysis consistency.
How Better Investment Data Management Helps Close Reporting Gaps
A common theme of all these challenges is data management. It’s one of the most valuable assets a company has, but only 7% of firms fully monitor data systems once they go live.
Data management is an ongoing task, especially in times of growth. It’s not just a concept but a strategy. Firms that prioritize data management can actually earn a competitive advantage in terms of business intelligence.
Organizations must also be able to audit and correct issues in order to close reporting gaps. A technology platform built on an MDM supports this endeavor.
The results of pivoting to this type of data management yield many benefits, including:
- Improving data consistency
- Reducing manual work
- Enhancing the reliability of attribution reporting
Choosing an Investment Data Platform to Support Scalable Attribution Reporting
As firms modernize their tech stack, selecting the right investment data platform greatly influences attribution reporting reliability. Some key criteria to seek out while assessing options include:
- Cloud-native SaaS platforms
- Solutions that incorporate AI and machine learning for data analysis
- The ability to consolidate data silos and restructure it
- Solutions that use an MDM
- Advanced performance measurement and attribution reporting features
- Easy integration options
Based on these crucial components, firms find that INDATA meets and exceeds their needs. Organizations using INDATA can improve the reliability of their performance attribution reports. INDATA built its suite of solutions to help investment firms manage complex data workflows. Contact INDATA to learn more.
FAQs
What information is included in a performance attribution report?
A performance attribution report includes the specific sources of a portfolio’s returns relative to a benchmark (e.g, S&P 500). It typically provides a breakdown of active management results into key components, including asset allocation, interaction effects to determine if excess returns are the product of smart choices or market luck, and security selection.
Who uses performance attribution reports within an investment firm?
Those who use performance attribution reports within an investment firm include multiple teams across many use cases, such as investment decision-making, meeting compliance requirements, and client communications. The list of roles consists of portfolio managers, analysts, risk and compliance teams, client relations, and leadership.
How often should investment firms review performance attribution reports?
At a minimum, investment firms should review performance attribution reports on a monthly basis. By evaluating these monthly, firms can have more visibility into internal evaluations. In times of high growth or expansion, the interval may need to be shorter, as organizations monitor the expansion of clients, data, and assets.
What is the difference between performance attribution and performance measurement?
The primary difference between performance attribution and performance measurement is what they quantify. Performance attribution reveals the investment decisions that led to returns (e.g., asset allocation or stock choices) that either beat or lagged the benchmark. Performance measurement is the total financial return or loss of a portfolio over a defined timeframe.
