Portfolio Monitoring & Reporting In A World Of Messy Data

Across the Alternative Asset Management landscape (private capital and hedge funds), portfolio monitoring and reporting to clients/LPs is becoming increasingly important…and increasingly complex.

The need for alpha is driving allocation to alternative assets classes and new geographies where you seldom have the luxury of reliable data standards and consistency, often worst on the private side.

Portfolio managers are using an increasing amount of alternative data (weather, car registrations, housing prices, consumer sentiment, etc) as they chase returns.  At the same time clients/LPs are throwing their weight around, requiring progressively granular reporting to support more sophisticated factor strategies and reporting on new dimensions – think ESG. 

You probably find yourself squeezed between an accelerating amount of data sources, formats, and systems on one side and ever more complex internal and external requirements on the other.   

The result?  Increasing ad hoc reporting work, error-prone manual processes, and poor data governance.  Do you actually know what data is used where? Have you got consistent, scalable processes?   

Internal: Portfolio Monitoring is becoming more demanding

Nothing beats performance.  You have decided to play, now you’ve got to keep track of the scores of individual investments, each fund/vehicle, and your firm overall.  Investors are increasingly gravitating to safer bets – successful, established players. The result is AUM growth, but also likely expansion into new asset classes or geographies.

More data, faster.  Investors are accelerating the use of alternative data.  On the private side, PE houses are building sophisticated models and taking data dumps from portfolio companies.  Investors in direct lending are monitoring alternative data on top of debt covenants and interest rates. If you are in renewable assets, you are looking to monitor wind or solar energy performance through operating companies.

Have you got a flexible, scalable process for ingesting data? While the value is in the actual analysis, you do need the data in a consumable format.

External: Client/LP Reporting is becoming more demanding

Demands are driven by a number of strong forces: increasing regulations, more challenging mandates and products (SMA, SOFs, etc), new investor classes, and the ESG agenda to name a few. 

The strongest driver? Larger, more vocal Clients/LPs who are reluctant to write cheques without more transparency and better reporting.  In a recent survey* of 196 limited partners (LPs), just under 50% noted the need for better reporting analytics and nearly 30% would like to see a move to standardised reporting templates.

As Alts move beyond the preserve of sophisticated institutions and family offices, the governance and regulatory oversight will continue at pace.  And ESG reporting is moving from nice-to-have to must-have and currently influencing fundraising battles, in particular in Europe.  

Another driver that will increasingly come to the fore, from larger clients/LPs, is reporting that enables investors to understand overlapping factor risk.  The challenge here is individual clients/LP will define their concentration targets e.g. industry or geography, rate exposure, etc. differently, so that asset managers end up with a barrage of similar but not identical reporting requirements.  While block chain and more real-time reporting will at some point become reality, in the next few years granularity of reporting and client/LP specific requests are likely to be your biggest headache.   

Have you got a roadmap for more granular, more frequent reporting across your firm without having to employ a sweatshop of data analysts?   What tools are you planning to use that scale and can be governed?  (Excel is great but not for this job)

It is not ‘to be or not to be’, it is a question of ‘breadth and depth’ 

It will become existential.  As a growing and innovative asset manager you face two fundamental monitoring and reporting challenges. First, how to deal with the increasing breadth of asset classes and fund structures?  Second, how to deal with the increasing depth of potentially relevant data – some real-time – for each investment?

Clearly ‘technology’ is the answer (after you are clear on your operating model).  But how do you industrialise something where complexity is exponential?  With new asset classes, geographies and fund structures, the number of point systems and data sources are accelerating and by going deeper you face another set of systems and data sources.

The only (economically viable) answer is to scale & ROI on your tech:  Intelligent Glue

Irrespective of your ‘unique’ operating model, success is not found buying one large system that does everything for you (it doesn’t exist) nor in trying to build your own super system. 

Instead, you must:

  1. Leverage point solutions (thereby using other people’s money and burned fingers)
  2. Only build internally from scratch where there is a truly unique use case (careful when listening to your software engineers)
  • Use intelligent glue to connect and enhance your systems, data and processes
  1. Migrate in small steps to globally recognised data management solutions (yes, they are in the cloud)

It’s about delivering value quicker by our maxim of ‘don’t rip out, connect & enhance’.

* By SS&C Intralinks, in partnership with Private Equity Wire, October 2020


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Tech & Data: Why Is Everything Taking So Damn Long?

In my discussions with senior leaders of Alternative Asset Management firms, I often hear the same refrain: “why is it taking so damn long?” or “when am I actually going to see return on my tech or data investment?”

Want a solution? Then check out these 6 Rules.