As of March 2021 the new Sustainable Finance Disclosure Regulation [SFDR] came into effect. This regulation is developed to drive sustainable investment. The SFDR will have big impact on asset managers, banks and fund brokers. In the upcoming weeks we will publish a blog series focusing on the SFDR, the obligations, the timelines, the definitions and the Adverse Sustainable Impacts Statement to help you get your head around the subject. And to ensure you are well prepared for the new regulation.In this blog post we will focus on common market data challenges we usually solve for our customers and discuss why these are even more challenging for SFDR. We also give some practical advice on how to overcome these challenges.

By Marc Bracher and Colin Prins

This blog post was first published on January 7, 2021 and updated on May 6, 2021.

Common SFDR market data challenges

Financial Market Participants have to overcome multiple challenges before they can call themselves SFDR compliant. Most of these challenges will sound similar to the regular market data changes you have to overcome every day. But keep in mind that SFDR requires something extra.

1.      SFDR requires data from multiple sources and multiple vendors

The ESAs published their final report on the draft Regulatory Technical Standards [RTS] in February 2021. It’s expected that the draft RTS presented there will be adopted to be the final RTS. Based on the RTS we assume that SFDR requires data from multiple sources and multiple vendors. Adding a lot of complexity to the game.

Short after the publication of the consultation paper in April 2020 we have sent out a request for information (RFI) to the main suspects. We asked market data vendors about their data coverage on attributes, (calculated) metrics and instrument universe. Not all of them provided the necessary information, but none of them is likely to provide 100% of the required data. Based on the outcomes of this RFI we expect you will at least need to contract two and more likely three different providers. In addition, it’s expected, you’ll have to source data from fund accounting and portfolio management systems and combine these data with data provided from external sources in order to calculate the metrics and comply with SFDR.

Next to the contracting part, the number of data sources also affects the IT capacity needed. You will have to write and maintain multiple feed handlers to take the necessary data into your system, requiring extra efforts of your IT team.   It is also good to keep in mind that most of the obligations under SFDR will require you to disclose information in multiple languages.

Another technical challenge is to address the changes data providers make to their API’s, files and feeds. Maintenance capacity will be required to keep up with regular and incidental changes. Especially taking into account the necessity for multiple data vendors under SFDR, this aspect should be considered carefully.

2.      Data feeds are often incomplete

After closing the contract and taking in the data there is often a new challenge popping up. When mapping the fields in the database there is always something missing or the live data is different from the data in the sample file.

If this occurs you will have to find another source offering the missing data and to write a new feed handler to take in the data. Because you can’t predict what data will be missing from the feed this will for sure add some more pressure to the already strict SFDR timelines.

3.      SFDR requires a lot of non-financial data

Not only you have to make smart decisions on what providers to contract, you will also have to focus on the types of data required. To complete your Adverse Sustainability Impacts Statement, you might have to look further than the offerings of your current market data provider(s). SFDR contains many indicators that require non-financial, more specifically ESG data.

For example to calculate the Carbon Footprint Indicator you will need market capitalization data, holding data and carbon footprint data for that holding.

Not every market data vendor will be able to offer those specific ESG fields when the SFDR becomes effective.

4.      Non-financial data is not widely available for small caps

When we mention that not every market data vendor will be able to offer all the required ESG data, it is good to add that probably ESG data will be widely available for ‘Blue Chip’ companies. For small caps this is less likely. Partially this is caused by the fact that the Non Financial Reporting Directive [NFRD], which requires large corporates to report on non-financial matters like ESG, doesn’t apply to most small caps. This means that UCITS management companies offering a fund with holdings in small caps will have to put way more effort in gathering the data.

5.      SFDR requires you to give insights in your data collection process

A lot of attention in the SFDR goes out to the Adverse Sustainability Impacts Statement. But there are other points that require your attention as well. For example the requirement that demands insight in your data collections process. That means you will have to report on the measurements you have taken to ensure the best possible coverage. Not only you will have to be able to provide information about the sources for your SFDR reporting, you will have to ensure that data from multiple sources is equal and comparable. For example when you switch vendors to do a calculation you will have to explain differences in field names and descriptions.

How to overcome the SFDR market data challenges

Luckily it is not all bad news. There are ways to overcome these challenges. It all starts with your data model. SFDR will test the flexibility of this model. The more flexible, the better you will be able to add or switch market data providers and to handle multiple types of data.

Characteristics of the ideal SFDR data model:

Zooming in on the ideal SFDR data model we see a few main characteristics. At the core of our believes is the single database that stores data from every provider separately. This helps you to get large amounts of data from multiple sources in quickly. It also helps to easily recognize what data is missing and to fill in the gaps with data from other vendors already in the database.

The ideal SFDR data model allows you to store the original data as well as the outcomes of calculations. The database contains the original fields that are used to do the calculation, so you can always track the original source. The outcomes are listed as coming from a separate vendor or source (this could be you).

Last but not least you should pay attention to the requirement about the insights in the data collection process. A good data model explains where the data is coming from, how it is processed and shows what actions you have taken to ensure the best possible coverage.  

The BIQH data model

If you want to learn more about the ideal SFDR data model or want to see it in action, we would like to invite you to contact us. The BIQH data model is a great example of a flexible model that supports many FMP’s to manage their market data.

We’re always open for a chat and we love discussions, especially when it comes to financial market data. Let us know your challenges, questions and uncertainties relating to the SFDR regulation!

If you have any questions about our SFDR solutions or fund data flows, please contact:

Ferdie Daanen | Director of Business Development | BIQHFerdie Daanen
+31 (0)6 1455 8103

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