An ongoing challenge for many financial markets organisations is how to increase efficiency and maximise cost savings across the business. Many firms are reviewing operations to identify market data cost reduction opportunities, as data costs typically account for a very large part of budgets.
At Xenomorph, we have been working with clients to determine what features are required to systematically reduce data costs, and through this process we have identified quite a few different elements needed.
Any market data cost reduction strategy has to be measurable – you need to be able to estimate the amount of money you are going to save – but you also need to understand the effects on all the exports that are happening, and then the implications for the consuming systems downstream. You need to make sure that every change you perform is carried out within a robust data management system, to ensure it is fully audited and centrally managed. In addition, this system has to be as transparent and configurable as possible, because the more changes you have to make to the downstream systems, then typically the greater the costs that you will incur.
Assuming that you have a data management system with the above features – how would you go about rationalising your data usage? In our experience you should identify a series of strategies and work through the list, starting with the easiest first.
To begin with you would look at a single process, a single account, and see if you can spot any duplication going on with that account. If you can, reconfigure the imports and then spoof the downstream system to eliminate those duplications. Spoofing places a data management layer between the vendor and the downstream system that intercepts and manages the requests without causing any disruption to the receiving application.
We often find that systems (front office systems, trade and position platforms etc.) are hard-wired to a data vendor, and to change that or add other data vendors would take considerable effort and budget. It is much better if you can spoof that system into thinking that it is still talking to the vendor, when actually your data management application is sitting in the middle. The data management layer intercepts and analyses the request from the calling system. If it has the data then it simply returns that dataset to that calling process; if it only has a partial dataset then it can send a partial request on to the vendor and when the data is returned you stitch the two datasets together and then send that on to the calling system.
Market data cost reduction – high level architecture
Once this process has been repeated across every single account that you have, you can then look across accounts to see if there is any duplication going on across the organisation. If there is, and it is of significant cost, then you want to do the same – reconfigure and spoof the systems.
Another issue we find is that when a new instrument is onboarded, different systems have different IDs and we see the same instrument being onboarded under different guises on one or more systems. Obviously, if you have a duplicated instrument it can cause issues with reconciliation, so it is important to put matching and checking in place when you onboard to make sure that you are not reproducing the same instrument.
You should also look at the fields you are buying – different vendors have wide range of pricing policies and so sometimes you can purchase the same field at a very different price from another vendor. Ideally you should be able to source data from a range of vendors, and then compare and substitute between them where possible.
Another interesting strategy when managing data costs is to produce an internal invoice for data consumed by downstream departments – thus highlighting the cost of the data that they are using. When different departments become responsible for the market data budget they may well question whether or not they really need all of the data that they are consuming.
Once you have followed all of these processes it is highly likely that you will have identified data that is being downloaded but not used – you might purchase the data and no one is reading it, or no one is exporting it. If that is the case then you can start to question if you really need that data at all.
If you are looking to formulate and execute a market data cost reduction strategy then please get in touch and one of our team will be able to discuss ways to help you gain greater control of your market data budget.