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      PriceOn from TraderTools: turning FX services into profit centres

      Published: just now

      yaacov heidingfsfeld tradertools

      In an industry where aggregation technology is rapidly becoming commoditised, TraderTools, under the leadership of President and Co-Founder Yaacov Heidingsfeld, is charting a different course. With their innovative PriceOn solution, TraderTools is not just keeping pace with the evolving FX technology ecosystem — they're reshaping it.

       

       

      Yaacov Heidingsfeld 200x200

      Yaacov Heidingsfeld, President & Co-Founder, TraderTools

       

       

      The Commoditisation Challenge

      "FX technology in a big picture is a race to zero in terms of the commoditisation of the availability of the aggregation technology," Heidingsfeld explains. This trend has led to a situation where replacing existing systems is a heavy lift with little reward. "Even if you saved a couple of hundred thousand dollars a year on your license with your technology provider, your internal resources, nobody's come back to work really in the last four years," he notes, highlighting the current challenges in the post-pandemic work environment.

       

       

       

      The Birth of Price-On

      Recognising the need to differentiate in an increasingly homogeneous market, TraderTools began a collaboration with industry veteran Drew Niv in 2019. “The idea was really how to differentiate ourselves, because we saw the writing on the wall in terms of the context of the commoditisation of technology”. The goal was clear: to enable banks and brokers to better manage their own liquidity, but in a more comprehensive sense than ever before.

       

      Heidingsfeld credits some of their success to fortunate timing: "It's better sometimes to be lucky than smart," he quips, referencing a saying from his co-founder. “So we identified a problem we started creating a solution, but we got very lucky in the implementation of that solution”. The rise of large language models (LLMs) proved to be a game-changer for their approach.

       

      "A lot of things just came together. The first one is the growth and acceptance of Large Language Models. The difference between using a trainable large-language model and backtesting is the difference between the first De Chevaux [or 2CV] car and a Lamborghini," Heidingsfeld asserts. While traditional backtesting can only observe past events, LLMs can learn from historical data and forecast future behaviour, providing a significant edge in market analysis and prediction.

       

       

      Price-On: A Modular Approach

      PriceOn is TraderTools' answer to the market's need for differentiation. Importantly, it's designed as an incremental piece of technology. "You do not need to replace what you currently have," Heidingsfeld emphasises. This approach leverages TraderTools' 27 years of experience in the industry, allowing them to interface with a wide range of existing technologies.

       

      After two and a half years of marketing PriceOn as a complete solution, TraderTools realized that many customers struggled to implement the entire system at once. In response, they broke PriceOn down into three modules:

       

      1. Market Recon

      2. Market Sentry

      3. Market Maker

       

      These modules can be licensed in a pyramid fashion, allowing customers to start with Market Recon and add additional functionality as needed. Heidingsfeld notes, "We are currently pricing it such that there's no financial incentive for you not to use Sentry if you're going to use Maker," encouraging customers to adopt the full suite of tools.

       

       

      Real-World Impact: The LBBW Case Study

      To illustrate the power of Price-On, Heidingsfeld points to their successful implementation with LBBW, a German regional bank. Before implementing Price-On, LBBW didn't view FX as a profit center but rather as a necessary service for their corporate customers.

       

      "What three years of production has taught us is they are currently aggressing the market only 30% of the time. The balance of the time is internalisation and passive order flow," Heidingsfeld reveals. This shift has transformed LBBW's FX operations from a cost center to a profit generator. "Where business had been costing them probably a pip on a regular basis, they're earning anywhere between 50 and $70 a million on their flow," he adds.

       

      The benefits extend beyond just profitability. LBBW has doubled the size of their FX business without adding personnel, thanks to the intelligent pricing enabled by Price-On. "They've doubled the size of their business and they've doubled the size of their business without adding any personnel on the desk. So they become more profitable, they're winning more business and they didn't have to grow their infrastructure. It's all automated," Heidingsfeld explains.

       

       

      Adapting to Different Market Participants

      PriceOn's flexibility allows it to cater to different types of market participants. For retail brokers, the system offers sophisticated customer segmentation based on knowledge level and what Heidingsfeld terms as "luck" level.

       

      "We've created essentially groupings of customers based on knowledge level and luck," Heidingsfeld explains. "In a standard recon view of the market for a retail broker, you have six categories... all the way to knowledge level three and luck level three. And we give you a picture and we say, these guys, you should never be internalising, these guys you should always be internalising."

       

      This granular approach allows brokers to optimise their risk management and pricing strategies for different customer segments.

       

       

      The Technology Behind Price-On

      At the heart of PriceOn is its use of machine learning and large language models. Unlike traditional backtesting methods, PriceOn uses a learning model that reviews historical data to forecast future market behavior. This approach allows for more dynamic and adaptive risk management strategies.

       

      "It's not using a backtesting model. It's using a learning model, right? Where you're reviewing history to learn from it and try and forecast what the future is," Heidingsfeld emphasizes.

       

      The system can ingest and learn from historical data, with Heidingsfeld recommending a minimum of three months of data for optimal performance. "I would not suggest learning from less than three months of data, but the more you give me, the better I learn," he notes.

       

      2024 10 07 20 35 18

       

      Implementation and Training

      For institutions looking to implement Price-On, Heidingsfeld estimates a typical setup time of about a month. This includes analysis work, rule setup, and infrastructure configuration. The system is designed to be user-friendly, with Heidingsfeld stating, "We've made this pretty idiot proof. Lots of training videos. We'll spend time with you. We'll hold your hand."

       

      However, he also stresses the importance of commitment from the client's side. "In the ATFX relationship, we trained the risk people. I'd say it took two to three weeks to train them and they're committed. They really want to learn," he says. On the flip side, he mentions that they've had to end relationships with customers who expected a "magic potion" that required no effort on their part.

       

       

      Market Positioning

      TraderTools' approach with PriceOn sets them apart in a crowded market. While competitors offering FX aggregation are moving towards selling analytics packages, Heidingsfeld sees this as insufficient differentiation. "They're feeding you the decays and that's going to be the differentiator. And now they're all doing it anyway," he notes.

       

      Instead, TraderTools positions PriceOn as a complementary tool that can enhance existing systems. This strategy allows institutions to improve their operations without the need for a complete system overhaul. PriceOn sits on top of any existing system."If you're a customer [of one of the FX aggregation providers], this is just another reason why you can justify not changing your kit, which you really don't want to do anyway," Heidingsfeld explains.

       

       

      Looking Ahead

      As the FX technology landscape continues to evolve, TraderTools' PriceOn solution stands out as a forward-thinking approach to liquidity management and risk assessment. By leveraging advanced machine learning techniques and offering a modular, adaptable system, TraderTools is helping its clients navigate the complexities of modern FX markets.

       

      With success stories like LBBW and a growing client base, TraderTools is well-positioned to continue its innovation in the FX technology space. As Heidingsfeld puts it, "We've moved to use other tools that are available in the market." This adaptability and willingness to evolve suggest that TraderTools and PriceOn will remain at the forefront of FX technology for years to come.

       

      In an industry where differentiation is increasingly difficult, TraderTools' PriceOn offers a compelling solution for banks, brokers, and other financial institutions looking to optimise their FX operations. By focusing on intelligent liquidity management and leveraging cutting-edge technology, TraderTools is not just keeping pace with the market—it's helping to shape its future.

       

      To learn more about TraderTools and to follow the company on LiquidityFinder, click the links below.

      This content may have been written by a third party. LiquidityFinder makes no representation or warranty and assumes no liability as to the accuracy or completeness of the information provided, nor any loss arising from any investment based on a recommendation, forecast or other information supplies by any third-party. This content is information only, and does not constitute financial, investment or other advice on which you can rely.
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