THE CLOUD HAS MORE THAN A SILVER LINING FOR THE FINANCE SECTOR.

In the finance sector, attitudes to cloud computing have evolved from sniffy ‘nimby’ism to outright advocacy. However, Appsbroker director Alex Wolcough argues that a simple ‘lift and shift’ approach to moving applications off-premise overlooks the many opportunities provided by the machine learning capabilities now native to leading cloud platforms.

Tipping point for the financial sector

Many industries have already realised the benefits of the cloud and have embraced the agility and cost benefits that on-demand compute and storage can bring. Previous concerns such as security, data protection and on-premise/cloud integration have been addressed to such an extent that retail, manufacturing, health and other industries are actively adopting the cloud – it now seems to be the finance sector’s turn to jump on board.

In the past, cloud technologies have met with strong resistance from the industry. For example, in-firm security and compliance departments – and even regulators – have thrown up objections to putting client or transactional data into external data stores. However, as with other industries, attitudes have softened as each of these concerns has been addressed. Government bodies and regulators have also started to provide helpful direction such as the FCA’s Finalised Guidance 16/5 (published in 2016) and the more recent EBA guidance concerning the use of cloud service providers by financial institutions, which was published in December of last year. Indeed, even GDPR provides clear guidance to EU firms on their ability to move data between countries, which gives lie to the myth that firms in a member state need to keep data within country.

Building cloud solutions

Many top-tier firms have already engaged dedicated teams to drive adoption of the cloud. However, the goals of these pioneers have not been to simply ‘lift and shift’ on-premise applications to the cloud. Why? Firstly, lift and shift does precisely that – it lifts and shifts all the complexity and cost currently residing in the data centre into the cloud. Secondly, they have sought to take advantage of the analytical tools and capabilities that often sit alongside cloud-based and on-demand compute and storage technologies.

This fresh approach has allowed investment firms and fintech providers to more efficiently build and deliver next-generation financial applications with both lower operational overheads and a lower overall cost base.

Turning MiFID II compliance into an advantage

A great example of how this powerful combination of capabilities has delivered real value has arisen from the implementation of MiFID II and MiFIR in the EU. With so much regulatory focus on the front office, many firms needed to build or buy capabilities that would capture client/sales desk interactions and ensure the correct implementation of MiFID II/MiFIR rules (e.g. Transparency, Record Keeping, Derivatives Trading Mandate, Transaction Reporting, Best Execution Reporting).

Building this capability on a cloud platform has allowed some banks not only to automate the application of the regulation but also to reap collateral benefits: applying the data analytics and visualisation tools available on the cloud platform to the data harvested for record keeping and regulatory reporting is now providing insights into client behaviour and profitability. For the first time, firms can get a detailed picture of client performance across both their electronic and voice businesses – much of this in near real-time.

Deeper analytics on demand

The depth of analytical capabilities offered by these platforms makes them attractive to quantitative analysts who seek deeper insights into both client and market behaviour. The elastic compute capability combined with huge storage capabilities means that petabytes of data can be analysed in relatively short periods of time with the additional benefit that banks only pay for what they use rather than investing in “tin” that can sit dormant. The familiar tools of the trade, such as “Python” or “R”, have been cloud enabled but it will be interesting to see how these will integrate with the machine learning capabilities now coming on stream on the major cloud platforms.

Risk analytics

It’s not just the front office that can benefit. The delay in the implementation of FRTB – the new rules on capital adequacy – and the softening attitude to cloud computing means that IT teams can now reconsider their approach to the infrastructure required to support the vast number of calculations needed for risk and capital adequacy modelling. By storing transaction events in the cloud and then applying modelling using the cloud’s elastic compute capabilities, firms can start to modernise and optimise their IT real-estate based on the immediate need at any moment in time rather than having to anticipate and plan for infrastructure months in advance.

Not ‘either/or’ but ‘and/and’

Of course, most financial sector firms will have a multitude of legacy applications they won’t want to re-architect. These platforms will sit alongside the new and will still require external inputs, such as market data and instrument reference data, as well as access to private client data. Many market data vendors are catering to this need through the provision of direct data feeds into the cloud, ensuring the same access to data that on-premise applications get today and providing the vital “air” that financial applications need.

Conclusion

It often takes several iterations of an innovation before it reaches its full potential. The evolution of the Arpanet – an obscure business recovery network for American research universities – into the Internet around which much of our lives now revolve is a great example of this. We are just beginning to see how a new wave of cloud technologies can empower technologists to deliver to the ever increasing demands of lines of business. However, the early adopters in the finance sector are already enjoying the benefits that the cloud brings in the form of both savings on the bottom line and contribution to the top line.

©BestExecution 2018

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