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Operational resilience: The future?

Matt Eddy
Matt Eddy
Head of Real-Time Delivery & Integration at Refinitiv

The evolution of data-as-a-service and analytics-as-a-service opens possibilities for fresh approaches to working with market data and pricing analytics which can boost operational resilience and agility for trading teams. Matt Eddy, Head of Enterprise Integration Proposition at Refinitiv, discusses three key steps for those considering moving to the cloud to boost operational resilience, and embrace new opportunities.

  1. Having operational resilience can also mean being agile enough to embrace fresh opportunities as they arise in changing markets and operational environments.
  2. Three key steps can help trading teams consider where data-as-a-service and analytics-as-a-service would provide the most benefit.
  3. Looking into the future, cloud-based approaches to market data and analytics could provide trading teams with unprecedented levels of intelligence.

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The COVID-19 pandemic has shown that operational resilience is about far more than just compliance.

For trading teams, operational resilience is about having the agility to respond and recover from extraordinary conditions, and then being able to engage the new opportunities that may emerge from those changing circumstances.

A new Refinitiv white paper, Why operational resilience is now essential for the trading business, explores ways in which trading teams at financial services firms are beginning to consider operational resilience as being important for their business, as well as a potential future compliance requirement.

Creating operational resilience for front-office teams

The first two blogs in this series, explored how operational resilience is impacting trading teams, and regulatory trends around operational resilience. This blog, the final one in the series, discusses three key steps for creating operational resilience around market data and pricing analytics for front-office teams.

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How can trading teams be efficient and agile?

The challenging market conditions during the first half of 2020 demonstrated how important it is for financial markets trading desks to have good access to the data and analytics they need to do their jobs well.

Teams had to navigate dramatic market moves while working from home or from a business continuity site. Not only did trading teams have to execute client orders, they also had to make sure risks were being properly managed, and compliance requirements were met.

Yet some teams were able to move beyond these requirements and truly embrace the opportunities that these volatile markets provided. To be both efficient and agile in the face of challenges and opportunities, trading teams might want to take the following three key steps:

1. Take stock

Pause and consider the trading team’s current market data infrastructure, as well as the compliance and pricing analytics it uses.

How could efficiency be enhanced? Were there opportunities that the team had to let go because of challenges around market data or analytics? Or what kinds of opportunities would the team like to be in a position to engage with in the future?


2. Consider the cloud

Attitudes towards the cloud within the financial services industry have changed dramatically in the wake of the COVID-19 pandemic.

A survey conducted by Celent showed that 48 percent of respondents said they were definitely or likely to increase their use of the cloud relative to their pre-COVID-19 strategy.

A first step when considering the cloud is to look at the current costs the firm incurs for its market data and analytics in areas such as:

  • Data center costs (power, space, cooling)
  • Networks
  • Software and operating system licenses
  • Human resources to monitor and manage
  • Weekend change management

It’s important to have a complete estimate of costs to be able to create use-cases that reflect the total savings from efficiencies.

Next, examine potential use-cases for the cloud with stakeholders, including the front office teams, compliance, IT, data governance, etc. Also, explore how data-as-a-service might align with the organization’s overall vision for digital transformation.

It’s possible that shifting to working with real-time and historical tick data in the cloud would fit in with the firm’s overall digital transformation goals.

3. Rethinking analytics

To improve operational resilience and enhance agility, more and more trading teams are considering analytics-as-a-service solutions as well.

To better understand how this approach might fit within the front office, first assess those current compliance or pricing analytics the firm uses that are non-competitive in nature. That is, which analytics are non-proprietary and are widely used by firms, or are a form of analysis mandated by regulators.

Second, look at whether the data used in these analytics processes is either currently hosted in the cloud, or whether it could be.

Third, work with a partner that can remove those inefficiencies to deliver analytics in the cloud for key use-cases. To build momentum, it can be a good idea to start with use-cases where the biggest efficiency savings can be achieved quickest.

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What is the future of operational resilience?

For trading teams, it’s clear that both data-as-a-service and analytics-as-a-service can make significant contributions towards creating operational resilience and enabling agility. Exciting possibilities are emerging.

For example, running analytics in the cloud can reduce run times dramatically, from 18 hours to just a few seconds. It’s quickly becoming the industry norm for risk analysis to be done at scale in near real-time. Organizations could be able to see where their own position is, as well as that position relative to the entire firm.

Also, going forward, there may be a much greater emphasis on working with data sets that are already consistent, or being able to normalize data sets quickly.

Trading teams need data quality to be high, and they need to be able to achieve that quality rapidly to keep up with their ability to perform analytics. So, the current focus on data governance, data quality, data integration and data lineage will increase in intensity.

All of these trends will create more operational resilience for trading teams, financial services firms, and the financial system as a whole.

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