UBS has increased its investment and development of leading FX technology builds notably over the past three years, especially since its recent acquisition of Credit Suisse, with a number of significant innovations having been brought to market this year.
The FX Trading platform at UBS supports the market-making businesses across spot, precious metals and palladium group metals, non-deliverable forwards, short-term interest rate (STIR) instruments and options, in addition to a leading offering in algos and smart-order router functionality.
Another notable area was significantly enhancing the data and analytics capabilities on UBS Neo, within its FX trading operations. This included new analytics tools and publications for FX spot, including the launch of a monthly FX Liquidity Monitor publication, an internal FX flowtool for sales, and an interactive e-FX quant analytics dashboard. The launch of STIR analytics on the platform breaks down prices of STIR instruments into its fundamental components, while advanced analytics were rolled out on multi-currency options products.
The bank also extended its algorithmic trading capabilities, incorporating pre-trade transaction cost analysis (TCA) to enhance execution outcomes. Post-trade TCA reports, which are benchmarked against UBS and third-party providers, are now available for both principal and agency FX products. These enhancements ensure that clients benefit from a more transparent and data-driven trading process.
In options, UBS has shifted from traditional pricing methods to a more service-oriented model. The enhancements include advanced pre-execution tools such as pricing grids, term structure analysis and entry-point analytics. With 90% of client pricing requests now automated, costs have been lowered and scalability improved, allowing UBS to focus resources on more complex client needs. Additionally, custom channels for risk management and pricing have led to a more efficient and competitive environment.
Further innovations were seen in UBS’s application of artificial intelligence and machine learning to its request-for-quote (RFQ) platforms. This technology provides real-time pricing improvements and has led to significant increases in trading volume across digital channels. The bank's adaptive pricing logic, which incorporates decision-tree and non-parametric survival analysis, has been particularly effective, contributing to a 30% year-on-year revenue growth, as reported in 2024.
To enhance client autonomy, UBS introduced post-trade functionality for FX cash, enabling clients to amend, roll, allocate, or average trades without involving sales teams. This self-service model increases operational efficiency and allows clients greater control over their trading activities.
Ciara Quinlan, head of principal e-trading, says: “Investment in advanced trading, pricing and platform innovation has enabled the seamless integration of Credit Suisse client flows.
“Despite the complexity of system integration and client migration, we delivered a smooth transition without disruption, demonstrating the strength and resilience of our FX platform and positioning us for rapid future growth.”