Bringing more transparency and efficiency to the FX Liquidity Management process

July 2022 in Trading Operations

A growing number of third party, data driven vendors are having a big impact on the FX Liquidity Management process. Nicholas Pratt investigates.

FX liquidity management used to be seen as a purely administrative role that principally involved mapping streams to clients, for banks. Today it is a data-driven role that, when done well, can benefit both makers and takers, says Geoff Jones, director, FX spot venues at London Stock Exchange Group (LSEG).

Like other exchange groups, LSEG has built up its data –driven services, helped by the acquisition of Refinitiv in January 2021. Its FX business is also one of a number of third party liquidity managers that provides data-driven services to both liquidity takers and providers, with the aim of encouraging better trading relationships.

There are a number of drivers that have helped improve the quality of FX liquidity and accelerate the rise of the liquidity managers, says Jones. For example, as firms changed practices to meet requirement of the FX Global Code of Conduct, the liquidity management function, and the data used to support that role has helped to hold liquidity providers to account in creating more transparency, in reducing hold times and highlighting the differences in timing for accepted and rejected requests.

That said, where the principles behind the Code have been evolving over 10 years or more, the majority of market-makers were already aligned to the spirit of the rules by the time it took effect – there wasn’t a cliff edge change in behaviour. The big difference, says Jones, has been the development of technology and vendors that have brought more transparency to trading process.

Data-driven developments

Technology has also helped firms identify genuine liquidity in what remains a fragmented FX market, says Jones. “Liquidity is more diverse than ever before, so it is incumbent on clients and liquidity providers to understand these differences – why liquidity providers avoid certain flow for example.”

“Over the last five to ten years we’ve seen an increase in the level of detail in liquidity management reports,” says Jones. “It is so much more complex because of the volume of data. People are not only using more liquidity providers but the market data also changes faster.”

“Over the last five to ten years we’ve seen an increase in the level of detail in liquidity management reports. It is so much more complex because of the amount of data.”

Geoff Jones

The profile of liquidity providers has also moved beyond those early days when there was a difference between bank and non-bank liquidity. “It is no longer a fair statement to say banks are good or execute one way or non-banks are not and execute in others. Many non-banks are genuine liquidity providers,” says Jones.

“There was a period when a number of third parties were building platforms that enabled takers to bypass measures designed to protect liquidity providers and maintain good liquidity. So whilst the focus of the industry has been on liquidity provider behaviour, there is a responsibility on platforms and clients to ensure good market practice. Some of this technology was imported from other asset classes with centralised rather than over-the-counter trading. In OTC markets is not just about technology but also about relationships,” says Jones. “As a liquidity manager, we have the ability to see everything which means we can facilitate effective conversations between liquidity providers and takers. Good liquidity providers set out their expectations and good clients understand what is expected of them. Not all firms have access to the data to support these conversations but there are a lot of independent firms out there that can support smaller firms. Clients and liquidity providers are doing themselves a disservice by not using this data.”

“Markout data plays the biggest role, it gives you an idea of how both sides behave. Transaction cost analysis (TCA) and peer analysis is also powerful. The data and analytics help support conversations that should be taking place” says Jones.

“Liquidity management can be done without independent providers but the question is ‘what do I not know?’. That peer analysis cannot be done on a bilateral basis. That level of analysis really lends itself to providers like Refintiv supporting the FX liquidity management process. It can help the Liquidity Provider realise when they are an anomaly,” he says.

An important development on the technology side has been the use of artificial intelligence and machine learning to produce predictive analytics

Great responsibility

When it comes to the evolution of liquidity management, one of the biggest changes has been a much greater awareness by market participants of their responsibilities when they engage with their liquidity providers.

“Liquidity managers at tier 2 banks are cognisant that they are part of a wider ecosystem and that to get the best pricing from the best liquidity providers, you have to take more responsibility for your flow,” says John Stead, Global Head of Pre-Sales at smartTrade. “If you are just smashing the market, you will get wide spreads or just cut off.”

There are a number of drivers that have accelerated the evolution of liquidity management, says Stead. “Firstly, there is less ‘fat’ in the industry as a whole. Tier 1 banks are facing ever tighter margins and are looking more closely at liquidity and the trading patterns of their counterparties. Secondly, there is also more technology available to liquidity providers to identify bad behaviour from underlying price takers. For example, technology such as smartTrade’s AI Analytics allows banks to analyse clients’ trading patterns automatically and look for and notify the bank of any interesting correlations and patterns automatically.

The FX Global Code has also had an impact in encouraging more transparency and better behaviour. And finally, there is more awareness and sophistication in terms of the link between behaviour and the causes of liquidity issues.”

In essence, market participants care more about liquidity management than ever before and there are more tools available to help them do something about it.  

An important development on the technology side has been the use of artificial intelligence and machine learning to produce predictive analytics, says Stead. For liquidity providers, this is helping them to identify trading patterns amongst their clients, to anticipate future flow and segment their clients accordingly. “Segmentation has become more and more important as LPs seek to optimise their relationships with clients and to understand their underlying trading patterns. There will always be clients that are sharper than others, but now it is easier to spot them and LPs care more about it now. If you combine smartTrade AI Analytics and our AlgoBox module then you can automatically spot certain behaviour patterns and then automatically assign clients to appropriate pricing and hedging groups reflecting their impact and market behaviour.”

The question is the level of automation that firms are willing to use, says Stead. For example, to what extent can automation truly support the trading and sales team to add more value, automation for automation’s sake is not an efficient goal. There is also more regulatory scrutiny on the use of artificial intelligence and an onus on firms to explain how algorithms have made certain decisions – a development that is still in its infancy.

“Relationships really do matter. They should be based on trust because you want liquidity partners not providers. But the technology allows for trust with verification.”

John Stead

But has the use of more advanced technology and third-party liquidity managers actually changed the behaviour of either liquidity providers and liquidity takers? According to Stead, there have been changes on both sides of the liquidity process. “When it comes to liquidity takers and the assembly of a panel of liquidity providers, it was previously thought that the more liquidity providers, the better. Now people realise that less can be more and are moving beyond that stance,” says Stead.

“The pandemic and the resultant market volatility of the last two years have also played a role in this change. It is during times of crisis that you find out who your real friends are. And those LPs that continued to price during the height of the market volatility, have been retained and now form the bedrock of firms’ LP panels. Then you may have another group of LPs that will get switched in and out based on performance,” says Stead.

However, as important as technology is, there is still a relationship element to good liquidity management. Stead says that a greater focus on liquidity management should encourage more conversation between liquidity providers and takers. “Talk to your clients about how they should behave. There is an education issue there. Make sure that your clients are not sweeping you and that you are using the proper risk controls in terms of flow, credit checks, transaction size and other factors.”

Technology definitely informs, but pricing and trading decisions are often based on a wider context – such as the other business that may be done between liquidity providers and takers. “Relationships really do matter and this is still the case,” says Stead. “Those relationships should be based on trust because you want liquidity partners not providers. The LiquidityFX Solution including AlgoBox and AI Analytics provided by smartTrade allows for trust with verification.”

In this space it is during times of crisis that you find out who your real friends are

Data-driven process

There has been a fundamental shift in liquidity management. It is now more of a data-driven process, says Guy Hopkins, founder and CEO of FairXchange. “Previously, the big liquidity providers would go to their clients and present them with all this information in terms of what’s working well and what is not. But each liquidity provider would have their own format and this would give clients no way to compare the data between liquidity providers and to respond to the information. It is now a far more systematic and robust process,” says Hopkins.

“For liquidity takers, it is not always as simple as picking the top five by market share. We want to take out the guesswork on what it is still a speculative exercise.”

Guy Hopkins

This is not to say that challenges do not remain. One of these is the increased use of FX aggregation. Some FX trading firms are using up to three or four aggregators, all with their own data format, which makes it difficult for firms to see the bigger picture when it comes to data analysis, says Hopkins. Consequently there is a premium on services and providers that can consolidate this data, such as the rising number of third party providers of liquidity management software that include FairXchange.

There are some similarities with the growth of TCA and the use of independent providers. However, while independence is helpful for liquidity management, the main-focus is the ability to capture and consolidate the data, says Hopkins. “TCA and best execution are more regulatory-driven processes, whereas liquidity management is more commercially-driven. Firms now realise the value of that market-wide data and why it is so important. For example, the firms doing the liquidity management are not always the originators of the trade, so they have to be aware of why trades are not working,” he states.

Liquidity fragmentation remains an issue, says Hopkins. “FX is not a complex asset class – it should not be hard for counterparties to agree on a set of data to use as the basis for their dialogue. But people do need to think about liquidity recycling. With new liquidity providers that you’re onboarding, you have to assess whether that liquidity is genuine. There is also the leakage of skews – when liquidity providers send out their indications of interest, they do not want to see the market using that information against them back in the lit market. It is a big challenge,” says Hopkins.

In the past, liquidity management was primarily based on spread and market share but there are now many more nuances factored in, such as the cost of rejection, so that trading firms get a better idea of the total value that a liquidity provider brings, says Hopkins. “The knack is to produce information that liquidity takers actually need.”

It is also about providing information that is actionable, such as making changes to the panel of liquidity providers, something that may require new trading and credit agreements plus lots of testing. “There is a lot of operational expense borne by the business when it comes to changing the panel of liquidity providers,” says Hopkins. “So it is important to know the economic cost of that change and the potential upside for both liquidity takers and providers.”

It is about making the selection of liquidity providers a data-driven exercise, says Hopkins. “For liquidity takers, it is not always as simple as picking the top five by market share. We want to take out the guesswork on what it is still a speculative exercise. So we promote the modelling of this process in advance using broader data. And for liquidity providers, it helps them to get a better idea of their customer service and makes for a far more constructive relationship.”

Ultimately, FX is still about relationship-driven trading, says Hopkins. And while liquidity management may be more data-driven, it is about using that data for practical changes. This means that the data is not just used by teams of quantitative analysts for number crunching but also by sales teams for client pitches, for example.

“In the old days, a sales person would go to the liquidity team and say tighten our pricing to make us more competitive,” says Hopkins. “That has changed now and sales people are going back to their clients and have the data to support the discussion about how they make the most appropriate changes to the relationship.”