First things first Market Data management, which is also the first step in your process, you’ll be continuously looking for providers to catch more and more data. Because of the variety of asset classes, markets, regulations, and so on, you will hardly find a single data provider that will cover all your needs. So you will be continuously analyzing new providers (data coverage, methodology, compliance with your needs…) and then selecting them and of course negotiating contracts.
The risks here is to miss some data that might be relevant or trending for your business. Of course if the negotiation part is not meet properly you can easily see how it will impact your costs.
Then Data sourcing and transformation. Therefore, once you selected your providers and start receiving the actual data, you need to be able to map them together…
Data Quality control is probably one of the biggest challenges you will be facing here. We can say that the extra-financial topic is fairly new and have a moving target. Our experience in Amundi showed us the huge difficulties to deal with the quality of what we receive from the providers, and it is not because you are plugged to a big well-known provider that everything will go smoothly and you won’t be facing any issue. And it is better to tackle it at the very beginning of your process, otherwise it will cost you much more effort to handle it at the end.
The risks here are spending time and money trying to anticipate what might go wrong and end up with holes that will impact your business.
Next pain point is focused on the ESG data coverage and methodology. And by coverage I mean matching the provider data to your own issuer/asset referential. You need to keep in mind that all the providers will not use the same identifier, some will attach the data to an issuer, other they will attach it to one of its assets, some will use ISIN, some will use SEDOL and so on. Also the provider won’t give you a list of all the assets you’re investing into. They might give you a data attached to the equity but you are investing into a bond for this company. Managing how data will be transferred from the main company to a subsidiary, from an asset to another one, from a company to another in the same sector and same size for example… all this is part of the Methodology to disseminate the data and increase the coverage.
So low coverage will affects will make the data unusable, especially when you need to aggregate it on a portfolio level.
4th pain point is Data Governance. It goes without saying a bad governance will lead to big issues in the workflow. Who is in charge of pointing out the changes in the regulation, will he be the same person in charge of selecting the provider to fill the gaps, is there a well-defined process to deal with data quality, who will be calling the provider to ask him for explanations… Data Governance is in the heart of the business and needs to be well defined.
Last but not least the Technology to be implemented to cope with all these challenges. Of course it needs to be scalable to handle the continuously growing volume of data, flexible enough to deal with its volatility, industrialized enough to keep the process efficient and to minimize the operational risk. It is also very important to not forget about innovation to ensure a future-proof tool capable of anticipating the trends on the market.
Of course not all these pain points are relevant for all the asset managers. Amundi is a big asset manager with a lot of ambition regarding ESG, is clearly facing all this issues, but depending on their size and ESG policy, some topic might not apply. For example, some asset managers might not need an in-house ESG methodology, they are more likely relying on a third party. Or they might be a very specialized company and might focus on working with one data provider.
*Amundi Leading Technologies & Operations