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Clients

Velocimetrics’ technology has been applied to multiple different use cases, enabling firms from various industry sectors to achieve complete operational oversight across their complex business processes

Velocimetrics’ technology is currently being used by buy and sell-side firms, trading venues and financial technology providers located across 6 continents to effectively detect potential sources of operational risk, performance issues, factors that could generate financial loss or negatively impact client satisfaction levels. Here is just a small sample of some of our client projects:

 

Australian Securities Exchange: Assuring consistently fast and reliable order matching

As the global exchange environment proves increasingly competitive, the consistent availability of ultra-fast order matching speeds and on-going reliability are integral to ensuring member satisfaction.

With Velocimetrics’ technology the Australian Securities Exchange (ASX) has been able to achieve the level of transparency necessary to fully understand the hop-by-hop performance of every equity order submitted to ASX Trade, one of the fastest integrated equities and derivative platforms in the world. In doing so, delivering real-time visibility of latency issues that could cause trading delays, providing greater operational oversight and increasing the exchange’s ability to proactively respond to issues and minimise potential member impact.

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City Index: Assuring equity price production system performance and market data quality

Committed to offering a market leading service, City Index wanted to be able to very quickly pinpoint and resolve any possible latency sources throughout their entire pricing flow.  They required a real-time solution that would identify delays in the data they received from exchanges, the processing of this data by their pricing engine and their price distribution infrastructure.

By deploying Velocimetrics’ technology, City Index is now able to independently monitor their equities price production process and the quality of market data being employed in real-time, with a near zero impact on their production systems and infrastructure. This development supports on-going efforts to effectively manage operational risk and ensure the continuous publication of fast, high quality pricing.

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City Index: Achieving even faster foreign exchange pricing

Following the successful implementation of Velocimetrics’ technology within their equity price production infrastructure, City Index turned its attention to FX. Producing tradable FX prices 24 hours a day, the ability to detect possible time delays in data received from liquidity providers, or latency impacting price production and distribution, proved essential in ensuring pricing accuracy and business success.

The solution employed now provides City Index with the ability to instantly detect the emergence of latency and issues occurring with the aggregation of data used to calculate prices. This enables the company to pinpoint possible time delays and tune their systems to ensure they can react even faster to changing market conditions.

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X2M: Resolving execution performance issues in a fast market

Consistently delivering optimised performance is integral to X2M’s shared service offering. Therefore, with multiple clients using the service at any one time, being able to rapidly identify, isolate and resolve developing issues that could negatively impact a client’s execution performance is a major priority for the firm.

By deploying TipOff, X2M is now able to more effectively solve problems in a fast market. X2M’s technical team uses TipOff to manage their network performance by facilitating improved bandwidth utilisation and capacity management, along with the ability to more efficiently identify where the cause of a fault lies within the end-to-end trade process. Their client services team uses the solution to more easily investigate issues reported by their clients.

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Improving trading system testing accuracy

Extreme market volatility caused an investment bank’s trading systems to react unexpectedly, resulting in multi-million dollar losses.  The bank needed to reproduce the scenario in their test environment to understand why and ensure it didn’t happen again.  However, they couldn’t access the data they were receiving at the time the incident happened to do so.

Keen to ensure they wouldn’t face this problem in the future, they employed Velocimetrics’ mdPlay service so they could continuously capture a copy of all of the feeds being consumed by their trading system and replay the segments of interest on-demand in their testing environment.

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Reducing foreign exchange trading losses by detecting latency hotspots

Concerned that latencies within their RFQ and RFSQ processes may be causing delayed quote publication and trading losses, this global investment bank wanted to be to able to effectively detect latency sources.

Velocimetrics’ technology enabled the client to examine each hop taken by loss making trades and understand their associated timings by providing the ability to quickly trace quotes right back to the pricing data ticks used to generate the quote. This approach enabled latency hotspots within their systems and across networks to be rapidly revealed.

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Reducing equity trading losses by detecting latency bottlenecks across complex trading environments

Keen to identify latency sources adversely impacting trading success, this global investment bank wanted the ability to quickly pinpoint where latency was occurring so they could then diagnose the root cause. To achieve this, our client wanted to be able to trace the path taken by loss making trades, all the way back to the original client order, even when the original order had been split up into multiple exchange and algorithmic orders, and no common trade ID was retained throughout the process.

Enabling complete trade reconstruction and the ability to measure both the hop-by-hop and end-to-end latency across these complex paths, Velocimetrics’ technology provided the performance metrics required to quickly identify latency hotspots.

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