Entities are the structures through which private markets firms raise, deploy and return capital. They carry the governance, filings, approvals and tax positions attached to each investment. They are also a key reference point for most other operational data sets.
As firms scale into more strategies, more jurisdictions and more complex deal structures, the volume of entities grows and the data underneath them changes more frequently. That places pressure on an area of the operating model that has not always been built for that level of scale.
This article sets out why entity management is becoming more important for GPs, what the target state looks like, and what is required to reach it.
Deal structures are driving the complexity
The growth in entity volume is a consequence of how deals are structured to generate returns.
Firms are managing more entities, more relationships between those entities, and more jurisdictions, each with its own regulatory requirements. A single GP may run several strategies, each producing different vehicles and different life-cycle events, meaning frequent change in the underlying data.
Private equity illustrates the point. An investment has to be structured to be made, held and eventually exited, and that structuring evolves at each stage. When a deal completes, a holding structure is established to acquire and hold the asset, often spanning several jurisdictions. Further vehicles are then added over the holding period as the investment develops, for example to support additional acquisitions, third-party co-investment, or management incentive arrangements. Each change affects ownership and equity, and entities are one of the main records through which those changes are viewed. Keeping entity data accurate is therefore what allows those changes to be tracked reliably.
A similar layering is happening at the fund level. On the capital-raising side, firms are broadening how and from whom they raise: evergreen and semi-liquid vehicles for wealth channels, separately managed accounts for larger investors, and parallel or feeder vehicles for different investor groups and jurisdictions. Alongside this, continuation funds and GP-led secondaries have become established routes to hold assets for longer or provide liquidity. Each of these adds entities and relationships at the top of the structure, so the complexity sits not only in how capital is deployed, but in how it is raised and managed.
Where entity data sits in the operating model
Across the investment life-cycle, operations are held together by a small number of core data types: accounting and general ledger data, portfolio monitoring, valuations, capital activity, ownership, and entity data.
Alongside transaction and instrument data, entity data is the structural layer the others rest on. It provides the legal structure that ownership, value and capital flows attach to, and it ties the other data sets together.
The role this layer plays becomes clearer when the structure is viewed in two directions, because each direction relies on entity data for different reasons.
Fund-up covers how investor capital is raised and pooled. The entities here are the funds, the GP, the management companies and the feeder and parallel vehicles. This is the layer where fees, expenses, carry and allocations are calculated, and where investor commitments and positions are recorded – all of which attach to these vehicles.
Fund-down covers how that capital is deployed. In a private equity context for instance, the entities here are the holding companies established for each investment and the portfolio companies themselves. This is the layer where ownership, control and economic interests are held, with shareholdings, appointments and jurisdictions recorded against each entity in the structure.
Both directions rely on the same entity data layer, and this is where it sits in the operating model: as the common layer connecting how capital is raised with how it is deployed. It is also a layer that evolves. Entities are formed and dissolved, ownership changes and structures are reorganized, so the record has to keep pace with the rate of change in the business.
Common pain points
These challenges are consistent across the market, and tend to appear in some form as firms grow.
- Fragmented data
Entity data typically sits across multiple teams and systems, with no single view that is complete and current. Structures change through the life-cycle of a fund, and manually maintained records can fall out of date between updates, making it difficult to confirm whether a given record reflects the current positions.
- Data held outside the firm
For many firms, a large share of entity data is created and maintained externally, by fund administrators, law firms and other providers. Each provider keeps an accurate record of the part they service, but more often than not, no single party holds the full picture. Assembling this means drawing on several sources, and the formats and update cycles will differ from one provider to the next.
- Administrative burden
Every entity carries ongoing administrative work, from formation through to filings, statutory record keeping and director and officer requirements. When the underlying data is fragmented, each task takes longer, because information has to be found and checked before it can actually be used.
Each of these challenges becomes more difficult to manage as the number of entities grows, and structures change more frequently.
The target state
One maintained record
- Entity data is held in a centralized way, covering each entity’s legal details, ownership, appointments and documents, and the rest of the operating model treats that record as its reference point
Clearly defined ownership
- Ownership of the record is defined, not assumed. The firm owns the complete record, and everyone who maintains entity data, whether that is internal teams, administrators or counsel, has a clearly defined role in keeping it current, enabled by an operating model built on sound technology and data principles
Connected to different processes
- Across the fund and deal life-cycle, both economic and governance processes interact with entity data, from capital movements, through to regulatory filings. For those workflows to run reliably, they need to draw on an accurate, live set of entity information
How can Alpha help
- Operating model design: We support firms in designing and delivering entity management operating models that scale with business complexity, defining the target state
- Technology evaluation: We evaluate the entity management technology landscape against the firm’s requirements, including an assessment of integration capability
- Integration design: We support firms in designing data flows between the platforms in a firm’s technology stack, identifying where the overlaps sit
Assess your entity management operating model against the target state above. If you’re seeing gaps, please reach out at [email protected]
