An investment Fata Warehouse (IDW) aims to bring disparate together into one place. It’s different from a pure data warehouse in that it focuses only on investment data management.
Types of data going into the warehouse include:
Data sources include Portfolio Management Software, Investment Accounting Software, Trade Order Management Systems, market data vendors, Execution Management Systems, etc.
The IDW is a central hub for collecting, combining, and organising data. It takes input in all different shapes and sizes and makes it easy to analyse. Before putting it all together, the data is checked and cleaned to ensure accuracy and reliability.
A general-purpose data warehouse, like Snowflake, will sit downstream from the IDW. Such a system might include more internal and external datapoints. Internal data can be information about client investments, and external data can be macroeconomic events, just to name a few examples.
When combined with a business intelligence tool, you can start to analyse investor deposits/redemptions correlation with performance and macro events as just a few examples.
Investment Data Warehouses and IBOR Systems both help organise information, but they have fundamental differences. Both represent fundamentally different investment management data warehouse models.
An IDW house is primarily concerned with consolidating information. It provides a central place for reliable, stored information that won't change until someone actively changes it. As such, there are usually good capabilities to get pre-validated information into the IDW and out of it. Client reporting systems are typical consumers of information from a data warehouse.
Usually, an Investment Data Warehouse won’t have visualisation and business intelligence functionality, but sometimes this will be the case.
The warehouse will absorb data on many different formats and will export it in just as many formats. Hence, the data model internal to the data warehouse must be flexible.
Some systems (like Limina's Investment Data Management System) structures the data before storing it. Other systems might store the raw data and attempt to structure it when you want to extract it.
An IBOR, on the other hand, is concerned with creating portfolio views for any use case. This can be position and cash, including preliminary deposits and open orders in the market. Or it can be settled cash for custody reconciliation.
On the face of it, it might seem like these are vastly different things. However, the IBOR needs a lot of data to do its job. It needs security mastering, prices and trades in real-time for example. From there, a proper generation 3 live-extract IBOR will calculate accurate cash and position views in real-time. Therefore, such an IBOR can sometimes negate the need for a separate Investment Data Warehouse solution.
An IBOR’s benefit is that it can simultaneously empower investment decisions. Some IBORs have Order Management capabilities, in these cases, this is referred to as enterprise Investment Management Software. Below you can see some system landscape examples and what capabilities an IBOR might come bundled with:
One interesting thing to note is that neither the IBOR nor the warehouse needs to understand the difference between asset classes. They can model any asset class in a similar, standardised way. This, of course, isn’t the case for investment compliance software or trade order management software. So, if your IBOR is bundled with such a system, it will know the intricacies of various instrument types.
The most common use cases of an Investment Data Warehouse for asset managers and fund managers are:
One of the main reasons why investment managers use an Investment Data Warehouse is to simplify and speed up their reporting. Instead of wasting time and dealing with multiple systems, they can store everything in one place. One place for all the data makes extracting and analysing information more straightforward so you can generate reports quickly and accurately.
Historically, best-of-breed systems were commonplace in the investment management industry. A best-of-breed setup is illustrated further up in this article. You might have had three solutions just in the front office, then at least the same in the middle office. To connect these systems and to gather data from them for downstream reporting, something is needed to “glue” it together. A purpose built Investment Data Warehouse for Asset Managers can fulfil that purpose. The caveat is that a broader solution, like a front-to-back system, would negate the need to integrate so many systems in the first place.
A business intelligence (BI) tool like Power BI can be great for analysing large amounts of information. It can help you answer questions about your investors, portfolio performance and macroeconomics to identify trends and spot opportunities for business development. The data warehouse can power such BI tools.
In conclusion, if you’re considering an IDW, we’d urge you to consider the use cases above and review the system landscape illustration in detail. Is it really a standalone warehouse you need? Or would an Investment Management Solution with an IBOR better serve your needs?
As former investment managers, we struggled to find transparent and unbiased information about different systems. The challenge is even more complex since there is no fully standardised vocabulary in the buy-side industry for various solutions.
At Limina, we’ve created guides to explain the various acronyms used in the financial buy-side industry. In this guide, part of that collection, we focus on data warehouses for asset managers.
In the name of transparency, Limina can serve as an investment data warehouse. This guide, however, isn’t meant as a pitch for our solution. If you’re interested in exploring us more as a potential partner, we’ve created two public articles about what firms Limina is most suited for and when Limina might not be the right choice.