Multiple interconnected risk dimensions – credit, regulatory, market, liquidity and operational risks – are amplified by the increasing sophistication of clients and liquidity providers. The challenge is compounded by the speed and volume of market data in today’s fully electrified environment.
The problem, observes John Stead, director of sales enablement and marketing at smartTrade Technologies, is that many banks are still relying on vendors that offer only basic solutions when they need granular, responsive systems.
“This reality has driven many institutions toward specialised providers, which offer sophisticated solutions that can strike the optimal balance between risk and reward,” he says. “As I always tell clients, knowing, understanding and mitigating risks is absolutely key to any profitable business model. There are plenty of examples of banks running profitable operations only to throw away profits by failing to manage risk correctly.”
“There are plenty of examples of banks running profitable operations only to throw away profits by failing to manage risk correctly.”
John Stead
Matt Chichester, electronic trading at iSAM Securities agrees that FX risk management has become more complex in a number of ways.
“The race to the bottom in spreads has made things challenging for both LPs and retail brokers,” he says. “As brokers and LPs compete on tighter pricing, Tier 1 bank spreads have widened in some cases due to increased volatility and uncertainty, creating a pricing mismatch across the ecosystem.”
Risk management as a differentiator
While this has squeezed margins for many market participants – including brokers – it has created an environment where only LPs with deep internalisation capabilities, smart routing and robust risk infrastructure can thrive. In today’s environment, the ability to manage risk with precision, transparency and speed is becoming a true differentiator.
Eric Huttman, CEO of MillTech, notes that institutions can also create their own complexity. “The vast majority of our clients did not have an electronified FX setup before they came to us,” he says. “The physical trade is only one piece of their FX risk management life cycle and is entirely non-core. As a result, processes tend to be both decentralised and unconnected, with many firms executing over the phone or via email and regulatory reporting and confirmations having to be manually uploaded.”
Fortunately, this is beginning to change. What is also changing is the perception of data – the focus now needs to be on how data is stored and interpreted, because if you cannot do this well, it is just noise.
“For example, a client will have all the data on exposures in a different system but does not want to parse it themselves in order to create the actual trades that need to happen,” says Huttman. “They want a third party to be able to grab all the data sitting in different places on their system – in whatever format – compare it to hedges that are on and automatically determine if an adjustment trade needs to happen versus a threshold limit and then to execute on or not.”
“The advisory and consultancy space is an area where AI is also going to have a lot to say and although it is not a solution in and of itself, it is a key enabler”
Eric Huttman
According to Stead, the biggest efficiency breakthrough from electronification is the ability of banks to dramatically expand their currency and asset coverage without hiring armies of people to watch every transaction or position.
“Previously, more risk management literally meant more people and higher costs – now it should all be automated,” he says. “The transformation enables institutions to internalise broader ranges of currencies and assets while maintaining effective oversight through electronic systems.”
Proactive approach increasingly common
We are seeing banks move from reactive to proactive risk management through real-time monitoring and predictive analytics where the systems can anticipate market movements and adjust strategies accordingly, rather than just responding after events occur.
“This shift represents a fundamental change in operational efficiency, where electronic platforms provide continuous visibility into exposure profiles and enable automated hedging strategies based on predefined parameters,” adds Stead. “The institutions that have embraced this electronification are seeing dramatic improvements in both risk management effectiveness and operational efficiency. It is really a competitive necessity at this point.”
Chichester suggests that the efficiency gains from electronification are something of a double-edged sword.
“On the one hand, electronification has improved execution speed and market access, particularly for firms who have invested in real-time analytics and trade monitoring,” he says. “The ability to monitor exposures, client behaviour and flow characteristics dynamically – not just post-trade – is now fundamental to successful risk management.”
“The ability to monitor exposures, client behaviour and flow characteristics dynamically – not just post-trade – is now fundamental to successful risk management.”
Matt Chichester
However, it has also introduced new challenges. Trade signals and trader reactions to market events are quicker than ever, leading to higher volumes and frequency of trades. That increases pressure on brokers and LPs alike to have robust risk frameworks that can keep up with intraday volatility and react instantly.
There is great interest across the market in how more automated, data-driven approaches to hedging and currency management can deliver sophisticated, efficient and effective risk management.
Stead reckons the key word here is anticipation – if you can predict what is likely to happen, you can prepare and mitigate before events occur, which is infinitely more effective than reacting afterwards. “We are moving toward faster-than-real-time approaches where predictive capabilities enable proactive risk management,” he says. “Let me give you a practical example: you can anticipate credit issues for clients based on their current limits and typical trading volumes at specific times of the month, then proactively communicate with both the client and your credit team to arrange solutions before rejections occur.”
Similarly, market risk can be managed predictively. If you can anticipate that you are unlikely to receive offsetting flows for a large position in a particular currency and you know figures are due out soon, you can start closing the position before volatility spikes rather than scrambling afterward.
Looking into the future
“The data-driven approach leverages artificial intelligence to process vast amounts of information including historical patterns, market sentiment and economic indicators,” explains Stead. “The institutions using predictive analytics to understand client flow patterns based on historical data are gaining significant competitive advantages as they are essentially seeing around corners in ways that weren’t possible before.”
“By understanding client behaviour, flow quality and symbol performance at a granular level, LPs and brokers can hedge more selectively, reducing both market impact and cost,” says Chichester. “This enables smarter internalisation strategies – retaining exposure when the risk profile is favourable and offloading it promptly when it is not.”
When combined with predictive analytics, machine learning models and real-time monitoring, these approaches can dynamically adjust hedging strategies in response to shifting market conditions and liquidity profiles.
“This not only improves execution efficiency but also enhances resilience against volatility, supports better capital allocation and ultimately contributes to more stable and predictable trading outcomes,” he adds.
Stead observes that granular risk assessment should be considered table stakes, not a premium feature – the more granular the better to accurately capture outcomes for specific clients, currency pairs and times of day.
“But granularity alone isn’t enough,” he says. “You need comprehensive integration. Modern platforms must avoid the silo problem that has plagued the industry. Controls should be open to input from other bank systems to eliminate data duplication and provide truly comprehensive views.”
The best platforms now offer real-time position aggregation across multiple trading systems, advanced scenario analysis and sophisticated visualisation tools that enable immediate identification of risk concentrations. The holistic approach extends beyond traditional market risk to encompass credit exposures, liquidity constraints and operational dependencies.
Taking a broader view.
“What we are seeing with state-of-the-art solutions is the ability to understand currency risk in the context of broader trading activities and portfolio effects,” adds Stead. “The platforms that can incorporate correlations between currency movements and other asset classes provide much more comprehensive risk assessments than standalone FX systems.”
While the underlying technology has become incredibly sophisticated, the best platforms are actually easier to use than their predecessors. A well designed risk management platform should be intuitive enough to avoid introducing new operational risks from user confusion.
“The integration challenge has been largely solved through standardisation,” says Stead. “Any serious platform should provide open APIs in standard formats like FIX and REST, which makes integration straightforward rather than a custom development nightmare.”
The key principle is that systems should fit into existing workflows rather than forcing operational changes. However, Stead cautions against oversimplifying the implementation process.
“While basic operations should be intuitive, you still need expertise to configure advanced features like custom scenario modelling and sophisticated hedging strategies,” he suggests. “The most successful implementations combine user-friendly interfaces with proper expertise to leverage advanced capabilities. The goal is minimising disruption while maximising capability. If your risk management system is too complex for people to operate properly, the system itself becomes a risk.”
Modern risk management solutions, such as Radar, are designed to give dealing desks a continuous, real-time view of their exposure and client activity across all platforms and trading servers.
Rather than relying on static or end-of-day reports, these more advanced platforms continuously stream positions from MT4, MT5, cTrader, DXTrade, FIX APIs and proprietary systems into a unified live view, making it possible to assess net risk instantly across books, symbols and venues.
“Enhanced alerting capabilities also allow users to take action before sharp clients drain their P&L – risk teams are able to act in the moment, rather than after losses are realised,” explains Chichester. “This consolidated insight empowers faster, more informed hedging decisions, allows brokers to dynamically adjust their risk posture as conditions change and integrates risk oversight seamlessly into daily workflows.”
Knowing the customer better
Coupled with powerful historical analytics, scenario testing and visualisation tools, these solutions also enable deeper investigation into client behaviour and risk trends over time. By bringing all key data, predictive insights and execution capabilities into one environment, Chichester observes that they allow risk teams to operate with maximum speed, precision and competitiveness, turning risk management from a defensive function into a strategic advantage.
Of course, these solutions require a careful balance between sophistication and usability. “They often require additional training or skills,” acknowledges Chichester. “However, many of today’s platforms have been adapted with this in mind, making them increasingly modular and intuitive in order to be as user friendly as possible.”
Having already achieved ultra-low latency, measuring processes in single digit micros, Stead reckons the next competitive frontier is faster-than-real-time capabilities through prediction and anticipation. “The only way to be faster than real-time is to anticipate what has a high probability of occurring and prepare your strategies before events happen,” he explains. “We are seeing clients use predictive analytics to understand when flows will occur based on historical data and this is just the beginning.” Artificial intelligence is driving much of this innovation, though it requires careful implementation. AI brings tremendous opportunities for enhanced decision-making, automated responses and pattern recognition, but vendors must also consider the new risks that the technology introduces.
Model risk becomes more significant and there is potential for AI systems to amplify market volatility through correlated responses.
Stead suggests the future landscape will likely include quantum computing applications, digital twins for market simulation and autonomous risk management systems.
When asked to assess the factors FX trading firms should take into account when selecting an FX risk management solutions provider, Chichester states that beyond the obvious considerations of performance, reliability and support, there are a number of key questions firms should ask before committing to a provider.
“First, do they build their own technology? Second, do they understand both the broker and the LP perspective? Third, is the pricing model transparent? Fourth, do they offer real-time insight, or simply end-of-day reporting? Fifth, is the platform able to scale with your firm? Ultimately, it’s about finding a partner whose risk philosophy aligns with your business model and allows your firm to grow both competitively and with future developments in technology.”
Systems must be robust
Ultra-low latency and high data processing capability are absolutely non-negotiable when it comes to vendor selection as any system must excel not just in normal conditions but especially during volatile periods around market events, says Stead.
“This is where you separate the serious providers from the rest,” he adds. “The evaluation must be comprehensive because risk itself is multifactorial. Forward-thinking capability is equally crucial. Evaluate what the vendor is doing to address future risks and opportunities, particularly around AI.”
The technical requirements extend beyond basic functionality. Clients need platforms that can integrate seamlessly with existing systems, provide intuitive interfaces that minimise operational risk and demonstrate proven performance under stress conditions.
Stead also warns against ignoring the human element. “Evaluate the vendor’s support quality, financial stability and commitment to ongoing innovation,” he says. “This is a strategic decision that will impact your operations for years, so invest the time in thorough due diligence – including reference checks and pilot implementations where possible.
While Huttman reckons there is no excuse for any firm not to have a comprehensive view of its exposures, the user friendliness of these systems varies.
“Most people do not understand the concept of a cost of hedging,” he says. “A lot of what we do is to try and remove the vagaries on what the existing costs are in their setup from an execution perspective.”
When looking for a risk management system, firms need to define what their problems are. Important questions to ask when using a new platform or provider include ‘where is the money?’ and ‘where is the risk?’. As Huttman observes, there are many examples of providers where the client is forced to take balance sheet risk against them.
According to Huttman, the big focus for platform providers now is next-generation decision-making enhancement. “The advisory and consultancy space is an area where AI is also going to have a lot to say and although it is not a solution in and of itself, it is a key enabler”, he concludes. “However, it will allow firms to automate different rules and preferences into a configurable system, which will deliver a customised automated solution.”