Cloud computing has been around for many years, but the capital markets and the post trade space in particular have been relatively slow to adopt it. In a DerivSource Q&A, Celent, senior analyst Arin Ray and Torstone CEO Brian Collings, discuss the fast growing adoption of cloud, software-as-a-service (SaaS) solutions and managed services in the back office and how they have the enabled big data and AI solutions needed to meet complex reporting needs.
Q: The cloud/SaaS trend has been around for a while and the market is quite mature, but the back office has been notoriously slow to automate – how pervasive are SaaS solutions, APIs and cloud technology in the back office today?
Arin Ray, senior analyst, Celent: Cloud is a relatively late entrant to the capital markets, not just in post-trade. However, in the last 18-24 months we have seen a radical shift in attitude among banks who are opening-up to the cloud, if not already implementing their cloud strategies. While post-trade processing has generally been a laggard when it comes to adoption of new technology, we now see growing interest and adoption of cloud technology in this space.
Cloud can be a nebulous term and take different forms – such as cloud-based infrastructure, platform, software and application. It can also come in different flavours such as private, public, hybrid, and managed cloud. Amidst this diversity of options for adoption, we observe the following trends:
- In the early days financial institutions, especially large ones, favoured the private cloud. But improving performance and security aspects of the public cloud are now making many opt for a hybrid or managed environment. Similarly, initial focus was on cloud-based infrastructure; there is now growing levels of comfort in using cloud-based applications and software including in post-trade.
- Many banks, especially beyond the largest institutions, expect their solution providers to deliver the benefits of cloud because they think expert providers are better positioned to address cloud’s requirements, such as security and location. Consequently, we see almost all post-trade solution providers, big and small, offering cloud-based solutions, and reporting growing user base. The combined user base of SaaS based post-trade solutions of a few leading providers is already well into high double digits and growing rapidly.
- With the FinTech revolution, we also see many cloud native solutions emerging in the post-trade space (e.g., in reconciliation and collateral management). Such providers also report a growing user base including some of the largest banks and market infrastructure providers.
- APIs – as understood in the current usage of the phrase (though APIs have been around for years internally) – are still not mainstream in the post-trade world at this point, but general adoption trends of the cloud from other segments point toward their wider adoption going forward.
Level of automation depends on various factors because of the complexities involved in the back office. In equities, the levels of straight through processing is the highest (over 70% to 90% depending on the institution). In other asset classes such as FX, fixed income, or non-exchange traded derivatives it is lower (50% or less). Many banks are currently undertaking electronification and digitalisation initiatives – such as electronic platform implementation, upgradation, rationalisation – in the front office in these asset classes, and post-trade automation and modernisation would be the next item on the agenda for most of them.
Q: What proportion of the firms you surveyed are now opting for managed services solutions for post-trade processing (do you have any data to prove this is increasing or is it more anecdotal?), and do they outsource the whole back office or just components? What is driving this move towards more managed services?
Ray: The need for managed services resonates in almost all our conversations with financial institutions. Additionally, the providers of post-trade solutions report significant user base and high growth rate of their managed service solutions, and there are discussions underway for creating new solutions in this category. Post-trade is a vast and diverse arena, and well over 50 financial institutions are already using managed services for at least some part of their post-trade operations, and the number of functions being outsourced in this category is registering double digit growth (10-30%) in recent years.
A general trend among financial institutions is to start with a select few functions or components for outsourcing under managed service, and then expand the functional scope. However, quite a few financial institutions have already outsourced their whole back office under managed service arrangements, typically for a few strategically important asset classes.
Cost is the biggest driver of change; especially since most financial institutions are looking to move away from managing anything in-house that is considered non-competitive, they are preferring expert third party providers to take care of end-to-end processes under manager service engagement. Economies of scale and expertise are also important considerations because expert third party providers can easily develop and maintain solutions following latest standards and practices while adhering to regular changes in regulatory environments and market conditions. Furthermore, by serving a range of institutions they can drive down unit cost through common pooling of resources and expertise.
Q: What are the easy wins when it comes to automating back office processes? Have most firms done these already?
Brian Collings, CEO, Torstone: There has been surprisingly little automation in the back office space, so there is much to improve. The problem with a lot of the legacy technology still in place is the lack of flexibility. So the first step is moving to a modern cloud-based system, which immediately gives better search and aggregation features that provide more transparency and quality data.
Much of the complexity of recent regulatory and compliance requirements comes not from the reporting itself but from the flexibility to consolidate and aggregate the correct transactional data and ensure complete coverage of the business.
Q: What are some areas that are ripe for automation/could be more automated than they currently are? What stands in the way?
Collings: Any workflow that has some basic logic to define an operational process can be easily automated with a modern system like Torstone Inferno. Rules-based processing can take most of the mundane and manual procedures away, leaving more time for exceptions to be handled correctly, which then lowers the risk of costly mistakes by focusing effort on the important issues.
Historically, short term annual budget cycles have played a large part in the decision not to change post-trade systems and take a more holistic view. Another hurdle has been the focus on regulatory changes, which has been time consuming for most organisations. However, in the rush to meet the deadlines to be compliant, firms have come to realise that the cost of changing existing legacy platforms has been significantly more than expected. Today, firms are reviewing their post-trade platforms and looking for more automation and flexibility to cope with ongoing change.
Q: What processes are harder to automate and why?
Collings: Exceptions ‘to the rule’ are the hardest to automate, even for a modern platform. But exceptions are harder because not all of the information is available to make an automated decision. That’s where a combination of Big Data and AI techniques play their part. If an AI engine is provided with quality data, the exceptions themselves have patterns that AI techniques can extract to determine the correct decision and learn to automatically process the next exception.
Q: How are the newer technologies (e.g. advanced analytics and robotics solutions) going to help? How pervasive are they at this point and what is the best use case?
Collings: It is the low cost of cloud-based data storage and relatively cheap cloud processing power that have made Big Data and AI techniques a reality today, and these two key technologies will have a huge impact on the post-trade industry.
As an example, using a cloud-based big data framework, Torstone helped bring the latest Regulatory and Legal Ledger reporting to the Japanese market, providing our clients with scalable, flexible solutions covering transaction volume, data location, and cross-asset class coverage.
From an AI perspective, Torstone Inferno is an open platform. The data quality in our system is extremely high because it is the customer’s official ‘books and records’, and therefore it is completely reconciled. Using AI technology in conjunction with rich, high-quality data creates a powerful combination in terms of improving operating efficiency and post-trade analytics for analysing transactional data.
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