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Why do Traders Need a Managed Service Partner?



Jeff Mezger, Vice President of Product Management, Financial Markets, TNS


Does your financial institution have the understanding, resources, talent and bandwidth to execute an effective data center strategy in-house? If not, it needs to, as behind every transaction is a labyrinth of algorithms and networking infrastructure technology that converge in one location: the data center.

For most, the answer will be ‘no’. There will not be the resource or skill in-house to keep ahead of the maze of technical and logistical options to execute the fastest and most profitable trades. Trading success requires accessing extremely powerful servers, with the best data lines and connections close to where the trade is physically taking place. Processing close to the source of the input data provides the lowest possible latency between input and response – and speed matters. Milliseconds can mean the loss or gain of millions of dollars.


Latency Matters

Low latency is vital for algorithmic trading. Many factors affect latency, especially hardware location and network connections. Trade execution speed is critical in maximizing profit and loss, and a competitive advantage comes from having the best communication links to hardware in the best location.

TNS’ ultra-low latency Layer 1 technology for exchange direct access inside the data center was the first architecture of its kind to be offered and deployed globally and remains the most advanced solution in the market. It eradicates the need for multiple switches by using a simple, single-hop architecture to deliver direct exchange connectivity in as little as 5 to 85 nanoseconds – impressive when you consider that the human eye takes 400 nanoseconds to blink!

So, acknowledging that speed and colocation are vital for executing a trading strategy, what can firms do to underpin trading success? Many will outsource operations to a specialist managed hosting, colocation and connectivity service provider.


In-house vs. DIY

A recent independent report Colocation of Financial Markets Trading Infrastructure’, identifies the pros and cons of in-house management (a “DIY” approach) versus a managed service model. The report found that managed service providers offer beneficial value-added services for capital markets clients. Advantages include cost savings, trade efficiency, and simplified access to data and network infrastructure support, enabling trading firms to focus on their core business competencies. Industry analyst firm, Celent, which authored the report, interviewed trading firms and data and trading technology providers and found that the key decision criteria when deciding to engage a managed service provider included:

  • Consultation and expert advice on the ideal configuration of hardware, network connectivity, location, data feeds and network bandwidth.
  • Agility and flexibility to take advantage of ever-changing investment opportunities by rapidly and easily deploying trading strategies in new markets.
  • Access to high-end network services, leveraging high-speed solutions, including ultra-low latency, in-data center Layer 1 connectivity to link to trading venues, new customers and other service providers.
  • Operational efficiency and future proofing, with access to the latest technology, and highly experienced staff in all global jurisdictions who help to navigate cultural, linguistic, and regulatory obstacles.



Managed Service Providers offering remote data center space and connectivity are on a quest to deliver a uniform global experience to ensure trading in, for example, Singapore or Tokyo is the same as trading in London or New York. They are also constantly investing in technology and new locations. For TNS, this means responding to customer requests to deliver a service in any location, most recently announcing a managed hosting and colocation offering in Madrid.

On rare occasions, perhaps instigated by political or economic events, firms may need to move from their existing data center location, as seen recently when key exchange, Euronext, relocated its primary data center and related colocation services from Basildon in the UK to the Aruba Global data center IT3 in Bergamo Italy. Such a physical move is a big undertaking and firms need differentiated support and solutions to ensure that they can seamlessly move and trade continuously, regardless of their size, requirements and the exchange location.

So far, TNS has moved nearly 20 existing and new customers to Bergamo, providing traders with uninterrupted, seamless trading. Our customers have been able to focus on their core business while we have managed the global supply chain issues to ensure a smooth migration. With suppliers quoting lead times of a year for some equipment, our buying power compared to smaller firms or those attempting to DIY a move, has proved invaluable in ensuring a smooth transition.



Firms need to future-proof their trading infrastructure by working with a provider that has experience in managing access to vast amounts of raw market data, can support multicast requirements and is able to offer scalable solutions to accommodate the demands of ever-expanding bandwidth. As traders diversify their portfolios, their market data needs can place excessive network capacity pressures on their infrastructure, sometimes running into tens of gigabits. Seek a provider that can easily accommodate these requirements and handle data bursts during high activity periods, such as those seen on many recent occasions due to market volatility caused by political and economic events.










Operations need a makeover. AI and Machine Learning can help.



Ashmita Gupta, SVP and Head of Business Intelligence and Analytics at Linedat


Data is the lifeblood of asset management. Its accuracy is paramount to effective decision-making, and ultimately, preserving the bottom line. Trade settlement is a data-intensive and repetitive process and is an example where the quality of the information to hand is make or break. This is because as assets under management increase, so too does the complexity and the probability of errors. But where the volumes of information might exceed that of what a human mind can process, the computing power of AI and ML can be employed to control quality and clean missing, out-of-date and incorrect data.

Not only does this boost efficiency by increasing the accuracy of trade settlements, but it is vital in protecting profits in a regulatory environment that is moving towards greater punitive measures for trade failures.


Forward-looking compliance

In compliance, real-time fraud and anomaly detection by AI and ML can reduce the all-too-common false positives that arise from reviewing rule-based alerts. When genuine faults do occur, they also cost time and money, as well as increase wider risks and inflict reputational damage.

Ashmita Gupta

Research by LexisNexis revealed that every $1 of fraud loss costs U.S. financial services firms $4. Firms cannot afford this. Neither can they afford the delays and uncertainty associated with undergoing a solely manual review process. To combat this, AI and ML solutions that combine internal data and external data can create a comprehensive view of a company’s front, middle and back-office operations. This can – much more quickly – diagnose why failures occurred and analyse historical patterns to predict when future faults may occur.  And of course – prevention is easier and cheaper than working backwards when a trade fails.


A virtuous cycle of business improvement

As more data is accumulated and analysed, the predictive capacities of this technology increase. This continuous development empowers human decision-makers to formulate proactive response strategies, creating a virtuous cycle. Risk managers benefit from an improved understanding of where to allocate resources and firms are empowered to make smarter staffing and planning decisions. Preventing future faults from occurring ultimately benefits the business by reducing operational costs and enabling compliance professionals to spend time on higher-value tasks.

A recent report by Clifford Chance and EY points to the value for document intelligence, where AI can read and analyse masses of unstructured data in Key Investor Information Documents, investment management and legal agreements, and then present actionable insights at scale. As well as facilitating personnel across the board to deliver a greater speed of client service and enhanced customer experience, improved processes can help retain and acquire top talent instead of having them focus their time on manual, repetitive tasks.

In addition to improving through use, AI and ML models benefit from being able to sit on top of existing infrastructure, making it easy to integrate into existing systems. Focusing on simply upgrading legacy manual systems is not enough as this still risks data unavailability. In the time that systems are down, companies lose out on crucial opportunities for insight and commercial growth and are unlikely to keep up as the settlement cycle moves to T+1. Additionally, the interoperability of AI and ML with the cloud means that it is a more future-proofed approach for business continuity, where firms can scale as they need to.


Control and confidence

The asset management industry faces numerous economic and geopolitical headwinds, the resolution of which is largely out of their control. Luckily for them, in the realm of operations, there is a clear route for firms to gain a competitive advantage from the increased data availability, accuracy and efficiency that comes with AI and ML capabilities. More than simple process improvements in the back office – implementing these technologies can go towards mitigating regulatory breaches, curtailing financial and reputational costs. Asset managers can have greater confidence in how they ought to set up their operations to best serve their clients both now and in the future.


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Shoring up defences to take advantage of the cloud




By Dave Waterson, CEO, SentryBay


The banking industry is embracing all the benefits that the cloud offers and slowly but surely moving its infrastructure over. The motivations for migrating include greater control of costs, access to reliable, constantly updated and optimised technology and an ability to build competitive advantage.

Alongside this, however, is the risk of exposure to cyberattacks.

The dynamic environment of the cloud removes organisations from total control of their network operations. In many cases, the cloud service provider takes responsibility for, at least, some of the systems and policies which ordinarily would be monitored by the company. Shifting data from secure on-premises networks into the cloud opens opportunities for cyber attackers and makes it easier for data to be leaked, which is why according to IBM nearly half of all data breaches happen in the cloud.

There is also the issue of compliance. A cloud environment typically enables large scale user access, but meeting with regulations such as GDPR, PCI DSS and HIPAA necessitates strict access control. If banks and financial services companies cannot demonstrate full adherence with regulations they are at risk, not just of a data breach, but of hefty fines for non-compliance.

The key to a successful cloud migration is strategic planning. Having a clear picture of the vulnerabilities that may occur as a result of moving data, applications and platforms into the cloud allows banking organisations to put defence mechanisms in position.

Securing endpoints

Perhaps the most obvious place to start is with the devices that will be used to access cloud-based systems. Laptops, corporate PCs, home PCs and smartphones are vulnerable. It takes just one keylogging attempt on an unmanaged laptop that is logging remotely into an online bank account to put that employee at risk of personal theft. It can equally take one malicious screen capture incident to grab the log-in details for the bank’s network and allow a bad actor access to the data of thousands of customers’ bank accounts. These are just two examples of common malware that frequently attack systems that are unprotected.

The rapid shift to remote working followed by hybrid models that allow employees to work in offices or from home have provided greater flexibility for workforces. For banks and financial services organisations however, this has created a huge headache when it comes to managing security. IT teams whose job previously was to monitor and log activity within a secure controlled location, are now expected to monitor the same activity, but across app virtualisation services such as Azure Virtual Desktop and SaaS applications like w365 with no direct visibility of the devices that are being used.

So, for a cloud migration to be successful and risk free, banks must recognise these vulnerabilities and start from that perspective.

Never trust, always verify

In a cloud environment even more than on-premises, the traditional approach to security which presumes that cyber attackers are always on the untrusted side of the network, and trusted users are always on the trusted side, should be put aside in favour of adopting a zero trust approach. This is a model that trusts nobody and assumes that all devices are untrustworthy. It means that access to the system is denied completely until the employee and their device have been verified.

The risk of an attack is now so great, and the belief in zero trust so strong, that the Spiceworks Ziff Davis 2022 State of IT report, carried out among over 1000 technology buyers in North America and Europe, found that 65 percent of companies in Europe were implementing, or planning to implement zero trust security solutions within two years.

The importance of wrapping data & applications

With zero trust in place, banks should turn their attention to building a layered approach to cybersecurity. Internet security, anti-virus software and securing the wireless network with virtual private networking (VPNs) still have an important role to play, but what is needed now as the threat landscape becomes more complex, is dedicated solutions that containerise data and applications securely, so they are wrapped against the threat of cyberattacks particularly from keyloggers, screen capture malware and other forms of cyberattack.

This type of security solution, which protects data entry on all devices, but particularly those that are used to remotely access cloud-based apps is essential to a layered approach and works without needing to identify the malware. It is also scalable, allowing banks and financial services companies to approach security as a continuous process. This is particularly important when it comes to compliance and is fully in line with regulations such as PCI DSS which requires continual reassessment and remediation of problems when personal and payment data is being handled.

Cyber threats have evolved to take advantage of weaknesses in the cloud, and the solutions that organisations use to tackle this pervasive problem also need to evolve. Delivering a mechanism that prevents an attack and which is easy for employees to deploy, wherever they happen to be working, and on whatever device, is a significant way of meeting the challenge.

The message, therefore, for the financial industry as it manages its migration to the cloud is to ensure a layered, integrated suite of security is in place as part of a zero trust approach. This will mitigate attacks and shore up defensive walls enabling them to fully maximise all the advantages that the cloud can bring.

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