A large, privately held insurance and financial services organization managing approximately $120B in assets across multiple external asset managers.
The firm operates a multi-manager investment model with 13 mandates across 11 firms, spanning a diverse set of asset classes, including private credit, structured products, and other complex investments. As the organization expanded its manager network and investment strategies, it required a more scalable approach to data, analytics, and investment operations.
The client had made multiple attempts to establish an Investment Book of Record (IBOR), but each effort stalled before reaching a sustainable, enterprise-wide solution.
While an Accounting Book of Record was in place, it did not provide the transparency or flexibility required by the investment team. Portfolio data remained fragmented across managers, limiting the firm’s ability to analyze exposures, assess risk, and generate consistent reporting across the full portfolio.
As the organization expanded its investment strategy and operating model, these limitations became more pronounced.
The firm’s investment model had evolved to include 13 mandates across 11 asset managers, with significant variation in mandate structure, data delivery formats, and asset class exposure. In particular, private credit investments distributed across multiple managers introduced complexity in data consistency, cash flow modeling, and reporting, while structured products and other less standardized assets further complicated the creation of a unified portfolio view.
The client selected Bloomberg Enterprise (AIM, PORT, MARS) to support its IBOR initiative. However, early in the process it became clear that the challenge extended beyond system implementation. Data from multiple asset managers varied significantly in format, completeness, and structure, and many of the client’s investments did not align cleanly with standard ingestion and modeling approaches. For example, certain privately held assets could not be directly ingested and required the creation of custom shell instruments, with supporting cash flow data manually constructed to enable modeling and reporting.
In addition, ingestion workflows varied across platform components, requiring separate processes and data handling approaches depending on the system. As a result, establishing the IBOR required defining a consistent data model, building integration workflows, and aligning platform capabilities with the realities of the underlying data.
Grandview Analytics led the IBOR engagement end-to-end — shaping the data strategy, managing implementation complexity, and delivering a functional IBOR within the client’s chosen architecture.
During the initial 30-day roadmap phase, Grandview recommended a vendor-agnostic architecture in which the client would consolidate security master data, IBOR positions, and transactions upstream before feeding a single client-owned enterprise source into Bloomberg.
The client initially elected to proceed with a platform-led approach, opting to have Bloomberg aggregate the asset manager files directly. Grandview continued to support this approach while preserving the broader framework required to make the IBOR sustainable.
During the data preparation phase, Grandview worked across asset manager file specifications, FTP setup, portfolio segment structure, supplemental data workflows, and reconciliation design. This work established the foundation for a normalized investment data model across positions, transactions, and security master data.
Grandview worked with the client and its asset managers to:
Several data elements required significant translation to align with platform requirements. For example, delinquency status fields required strict formatting and validation, contributing to delays and reinforcing the need for stronger upstream data control.
During implementation, Grandview maintained alignment between the client’s long-term IBOR objectives and the realities of the selected platform architecture. Grandview coordinated the Bloomberg AIM, PORT, and MARS workstreams across multiple ingestion paths and system-specific requirements.
For complex and non-standard assets, Grandview engineered solutions to enable modeling and reporting. Certain privately held assets required the creation of custom shell instruments, with supporting cash flow data manually constructed to align with platform requirements.
Grandview also supported IBOR-to-ABOR reconciliation, validating the assembled investment data against existing accounting records. Throughout the implementation phase, Grandview actively managed vendor interactions, addressing gaps between expected and delivered functionality, coordinating resets in delivery approach, and maintaining alignment between the client’s requirements and platform capabilities.
As data came online, the limitations of the Bloomberg-aggregated approach became more visible. Transactions data was not available via API as originally intended, and positions and security information arrived in a disjointed manner.
By the end of the engagement, the client committed to Grandview’s original recommendation — a client-owned, upstream data model to be implemented on Snowflake. Grandview formalized this forward path in a closing recommendation outlining the client’s future-state investment data architecture.
Grandview established governance and coordination processes across stakeholders, helping the client manage vendor interactions and maintain alignment throughout the project.
In parallel, Grandview supported the build-out of the client’s Investment Operations function by defining workflows, documenting processes, and enabling the transition to a fully staffed internal team.
Grandview delivered a fully operational Investment Book of Record — consolidating positions, analytics, risk, and performance across a complex multi-manager portfolio onto a single platform. The full engagement, spanning roadmap, data preparation, and implementation, was completed within 12 months.
The resulting IBOR enables the investment team to:
The solution supports:
The engagement delivered immediate, measurable value — a working IBOR within 12 months — while establishing a clear and scalable path forward built on a client-owned investment data architecture.