In FX, margins are tight – so tight, in fact, that there isn’t any margin for error. Financial institutions can easily and quickly go from being slightly profitable to slightly unprofitable and therefore understanding the decisions which impact these margins is crucial.
The only way that firms can make truly informed decisions about how they interact with existing and prospective Liquidity Providers is by using data analytics. To date, decisions about which Liquidity Providers to onboard have too often been made purely based upon intuition and the strength of relationships. Which is ironic in an electronic industry such as FX which uses highly sophisticated technology and automation across practically all aspects of its trading operations.
Independent data is not only invaluable for informing the decision making process at the point of onboarding a Liquidity Provider but can also be used to provide vital insight on an ongoing basis. Against a backdrop of flash events and a constantly evolving geopolitical landscape, it is crucial that financial institutions regularly assess the performance of their Liquidity Providers and use the data to drive informed discussions with them. And this goes both ways. Liquidity Providers can also benefit from access to independent transactional data as they need to be able to justify their position with certain clients and demonstrate the value they bring and how an increased amount of flow from a particular client could be of benefit to both parties. With access to highly targeted information, Liquidity Providers may have a greater understanding about where they can adjust their pricing and how much additional flow they might win if they make certain changes. This is far more effective than the current more abstract conversations which often take place between both parties such as “you are too wide, if you tighten up by 0.1, you’ll win more volume.”
Data analytics is becoming more mainstream
Until relatively recently, rigorous data analysis has largely been confined to a limited number of highly qualified quantitative specialists within each financial institution but this is rapidly changing. The use of data is now becoming much more prevalent across a broader number of job functions within a firm – and that is exactly how it should be. If a sales person, for example, wants to argue for an improvement in liquidity provision for a client, they need to go armed with data in order to create a more compelling case. And as the use of data has become more mainstream across the firm, in order to be really useful, it also needs to be accessible.
You cannot present Liquidity Providers with complex information and expect it to form the basis of an informed discussion if the data itself is difficult to interpret. It isn’t sufficient to have sight of transactional data without being able to build a clear narrative from it – and for this, the data needs to be presented in a clear and comprehensive visual format.
FairXchange has conducted extensive research into effective data visualisation and it has been fascinating exploring how to make complex, multi-dimensional data as accessible as possible. As a result, our visualisations are designed specifically so that they most closely suit the human visual system. For us, it has been crucial to create a platform that can be used by a wide range of people within a financial institution, and not in a format that only one or two IT people and data scientists within the organisation can interpret.
The true cost of onboarding a new FX Liquidity Provider
When considering onboarding a new Liquidity Provider, the first thing to be clear about is that you shouldn’t exclusively be looking at spread or price quality. There are a lot of other areas to take into consideration, such as the costs of credit, financing and connectivity as well as the wider costs associated with the onboarding process. You need to be certain that the economic benefits of onboarding a new Liquidity Provider outweigh these economic costs.
There are also the direct costs of execution and price competitiveness to consider. Spread is important but doesn’t necessarily show the full picture – for example, there are many Liquidity Providers who don’t show aggressive spreads but show skews. Some Liquidity Providers are more opportunistic and only trade with you when it suits their own risk position. If you also get a lot of trade rejections, you will then need to go out to market more and this will increase your execution costs. Cost of rejects, market impact, spread and skew are all things that need to be fully understood when looking at selecting a new Liquidity Provider and assessing the true costs involved.
Selecting the best liquidity panel for your business
Diversity is key when selecting a liquidity panel -– you don’t want a lot of Liquidity Providers who all act in a similar way or are all skewed in the same direction. You need Liquidity Providers with a diverse approach to risk. One way to achieve this may be to consider a regional specialist bank or a specialist in certain currency pairs.
It is also important to consider the size of your panel. Many participants think that continuing to add Liquidity Providers is a good way to benefit from ever-better pricing through aggregation. However, this is a strategy fraught with risk as it increases the likelihood one of your counterparties will aggressively hedge your flow and create market impact, which potentially hurts everyone else in the panel. The long-term impact may be that you see your spreads actually widen as a result as the Liquidity Providers take action to avoid losses. You may also become less relevant to each of them given their reduced share of volume and therefore your pricing will get less attention. Given the rapid changes in the liquidity environment in today’s market, you don’t want to be stuck on a generic pricing configuration that hasn’t been looked at in nine months by the Liquidity Provider because your limited volume doesn’t justify the effort.
What is interesting in this market is that decisions about which Liquidity Provider to select are often made on anecdotal evidence and the reputation of a particular Liquidity Provider. There is a lot of trust involved – and just because a Liquidity Provider is right for one particular firm, it doesn’t mean that it’s ideal for another. Armed with impartial, independent data, financial institutions can make more informed decisions during the selection process and beyond.
With the tools now available, financial institutions even have the luxury of a ‘try before you buy’ experience. They can look at areas such as:
- If I were to onboard this LP, how would it benefit my business?
- How competitive are they?
- How will it meaningfully change our cost of execution?
- Do we have enough volume to make this sustainable for us?
Again, a key consideration when adding a new Liquidity Provider to the panel is to think about the dilution of flow to existing Liquidity Providers. It is important to ask yourself: “will we jeopardise the relationships we already have by doing this and, if so, does it look like this will be worth it?”
Providing evidence in an evolving landscape
As already highlighted, ongoing analysis of a Liquidity Provider’s performance is critical. The data is particularly useful in providing evidence about how liquidity changed through major market dislocations. Take the COVID-19 pandemic, for example. It was interesting to see the speed with which Liquidity Providers adjusted their pricing, how much by, how quickly they came back in and whether there were any structural changes in liquidity provision before and after the start of the pandemic in March 2020. Whilst many Liquidity Providers talked about being as competitive as possible during this time, the data provides the hard facts. Being able to point to tangible evidence of strong performance and commitment to relationships during testing times makes for a compelling value proposition.
Reaping the benefits
One of the principal benefits of this sort of data analysis is that by understanding the relative changes in execution costs as a dollar number it makes decisions about Liquidity Providers far less subjective. This has been game changing in our industry and truly benefits all parties. The ultimate purpose of having sight of the transactional data in an easy to interpret format is to help both parties speak a common language. It isn’t about creating a situation in which one party wins and the other loses – in which one party wins and the other loses; FX trading is emphatically not a zero-sum game. It is about having fair, meaningful discussions in which both parties win by creating sustainable long-term relationships.
We are getting to the stage where more institutions are using data analytics to understand the current state of their business and their relationships with their Liquidity Providers. In 2021 and beyond we will start to see the measurement process evolve into something deeper and more iterative. In the same way that the top Liquidity Providers have now automated much of the calibration of the liquidity their customers receive, we see customers starting to automate many more parts of the liquidity management process.
It is important to point out, especially when looking to the future, that we do not believe this inevitably leads to completely automated decision making. It is our firm belief that technology exists to augment, rather than replace, human decision making. Data should assist the decision making process across all stages but people undoubtedly need to be involved at every stage, both now and in the future. There are nuances around all relationships that cannot be interpreted from the data alone.
It does, however, mean that the nature of people’s roles is changing as data becomes more accessible to a wider audience. We see this as a positive; it makes jobs more interesting, reducing or removing many mundane tasks and enhancing the decision making process. Increased use of data in decision making is, in our view, one of the most significant recent developments in the FX industry, providing major opportunities for both the buy and the sell-side.
FairXchange’s Pricing Stack Analysis
Data shows impact of liquidity decisions on a financial institution’s P&L
FairXchange’s Pricing Stack Analysis feature within its Horizon product enables financial institutions worldwide to make more informed, data driven decisions about how they interact with existing and prospective Liquidity Providers. By providing a complete view of a financial institution’s pricing stack, FairXchange’s Pricing Stack Analysis provides unparalleled insight into the dynamics of their liquidity and enables banks, brokers and hedge funds to understand the financial impact of their Liquidity Provider selection compared to other choices they could make. Pricing Stack Analysis uses FairXchange’s sophisticated proprietary technology to start addressing specific insightful yet previously unanswerable questions such as:
FairXchange is completely independent and has no affiliation with any Liquidity Providers or trading venues.