Data: From Big Chaotic to Smart Profitable

FICC businesses have been hit by multiple headwinds in recent years: tighter margins, lower volumes, rising costs, restrictions on proprietary trading, new CCP clearing requirements, as well as regulation more generally. In an environment as challenging as this, it is easy to overlook the importance of the data that underpins the entire business. As a result, while data is collected and stored, it is typically done on an ad hoc inconsistent basis, which results in multiple data stores using different formats. The collective result is a huge volume of data that is so incoherent that it is of minimal practical use for supporting effective decision making and action. This is true not only of the data itself, but also the metadata associated with its original capture.

Immediate pressure to remedy this comes from various regulatory data requirements (such as the BCBS 239 standard within Basel IV) as well as cost/profitability concerns, but a further motivation is the inexorable growth of electronic trading. The lower frictional costs of electronic trading stimulate new trading activity. Furthermore, the electronic share of existing activity continues to increase, even in markets such as fixed income that have a long term affinity with voice. This transition applies even to relatively opaque corners of fixed income such as corporate bonds. For instance, electronic corporate bond trading in the US jumped from 19% to 26% of activity between Q1 and Q3 of 20181. Meanwhile in Europe the EU estimates that 25% of all corporate bond trading in 2017 was electronic2.

This is effectively a self propagating situation: more existing bond trading activity is becoming electronic, which in turn stimulates new trading activity that is also electronic, so ever more electronic bond trading data needs to be captured.

Therefore, making the smart data transition immediately makes far more sense than delaying and continuing to amass ever-increasing quantities of unstructured and low-usability data.


The first step is to normalize and aggregate all existing internal (and if desired also external) data sources across all channels into a single consistent and consolidated state, which can also be updated in real time. Then supplement this with analytics that give the cleaned data the business intelligence to make it smart.

Armed with smart data, analysis and reporting can also become smart over any time scale from seconds to years. A critical gain here is that analysis and reporting become dynamic, actionable and potentially profitable – not just pretty pictures to be printed off and discarded later.

This is especially true if the smart data solution used is sufficiently flexible to allow the incorporation of proprietary analytics alongside its own built-in analytics, as this delivers multiple additional benefits:

In-house quants will have immediate access to a single homogenous granular data store, which will significantly boost their productivity, as they will no longer have to spend ~80% of their time on collecting, cleaning and organising data3.

Combining proprietary and built-in analytics will enable FICC businesses to make the very best possible use of their data to derive more profitable business intelligence.

Users will have instant desktop access to precisely the quantitative expertise they need to maximize their individual productivity.

All this can be delivered in real time; the value of analysis will no longer be eroded by latency.


Servicing buyside relationships profitably and efficiently in an environment where data is proliferating and margins are tight requires best in class data curation and analytics. Recent analysis by Boston Consulting Group4 found that this was typically not the case so that: …data fragmentation and siloed management practices leave sales teams with a limited view of the client. Furthermore: In the absence of high-quality, easily accessible data, sales teams are required to spend valuable time searching for risk, industry, benchmarking, and other information they need.

By contrast, smart data enables far more efficient navigation to deliver quick identification of the most promising opportunities to enlarge client relationships and profitability. Building a detailed profile of a clients current activity becomes a matter of seconds, making identification of possible additional synergies and sales almost trivial.

One example of how this enhanced client knowledge can be used to gain an important edge is in the automated generation of customized and targeted insights. If all a clients data is immediately available in a readily-accessible format, it becomes possible to assemble intelligent narrative that will be of interest and value to that specific client. However, if the solution that smartens the data also includes tools to create content without requiring human intervention – such as through the use of natural language generation (NLG) tools – then the entire process becomes not only highly automated but also exceptionally valuable in boosting client relationships and profitability. When compared with distributing generic research or manually writing custom material, a massive increase in productivity becomes possible.

A few leading FICC businesses are already taking this approach in order to enhance the client experience and to boost client retention and revenue. Other examples include providing clients with customised tools that assist them in searching for corporate bonds across multiple sources. An important value-add here is that clients smart data profiles can be leveraged to customise search tools to their specific needs. Therefore, the default search sources provided will only be those relevant to individual clients, thereby making their workflows more productive.


Capabilities like this are obviously valuable for the conventional client servicing model, but new opportunities are arising in FICC that could further boost their importance. Research by Opimas suggest that cost pressures could see ~20% of large (defined as AUM >USD50bn) asset managers outsourcing part of their trading desk activity by 20225. For smaller asset managers, the figures are even more striking: for managers with USD10bn under management Opimas estimates that ~10% will outsource their trading desk completely, while a further ~30% will outsource some of their activities. \\

A FICC business armed with smart data and analytics will have a major competitive edge when trying to capture this business, as it will be able to demonstrate its ability to tailor its outsourcing services to a highly granular and client-specific level.

Furthermore, the inherent flexibility of a FICC business that has implemented smart data and analytics means that it is able to offer exceptional service to buyside clients of all size. So smaller clients that were previously difficult to service cost-effectively are now fully accessible. For some FICC businesses this might open up a completely new and profitable client demographic, as well as improving the servicing and profitability of existing clients.


Smart data also presents internal opportunities, as it can be used to boost employee productivity across the board. Metrics and data streams specific to each role can be configured to drive a dashboard that individuals can use to prioritise and streamline their workflow, by using automated and prioritised task alerts. Users therefore only see what they need to see in order to maximise their productivity. Furthermore, they will be able automate far more of their current routine tasks, so they can maximise the time they spend on value added activities that will drive overall FICC profitability.

The opportunity to boost FICC productivity with smart data also goes beyond just client facing roles. New technology such as intelligent automation is seen as essential for driving efficiency and minimising unnecessary cost throughout the FICC business6,7. Trade allocation, settlement, reconciliation and exception handling, corporate actions dissemination etc are all areas where inefficiencies can be removed in this way. But this is only possible when smart data and the right tools are available to help accomplish this.

This makes it possible to form a far more nuanced and holistic client view that can be reflected to good effect, such as in pricing activity. Therefore, those FICC businesses that invest in making their data smart will not only have a competitive edge over new non-bank competitors (who do not have that data in the first place) but also over other FICC businesses who persist with dumb data.

This would be true in the general sense in any situation, but is especially important in todays environment with the rapid pace of development in AI/ ML/NLG. Taking optimal advantage of these technologies requires clean consistent data and (especially in the case of ML and AI) the more and smarter the data, the better the outcome. FICC businesses that invest in making their data smart are therefore ideally positioned to leverage it for generating greater profitability and cost savings across both existing and new products/services.

It is also worth noting that smart data is equally applicable to other parts of the business outside FICC. Organizations looking to get the maximum return on their smart data investment will also extend the concept into other areas, such as equities. By doing so, they will have access to 360 degree visibility of their enterprise, but also its client relationships and the opportunity to maximise their profitability.


Making data smart completely transforms this situation: fast and productive multi-dimensional analysis becomes possible across multiple time frames while incorporating multiple data and analytical sources. Both human and machine decision making is thereby enhanced.

This capability would be beneficial for FICC businesses at any time, but in an environment as demanding as the current one, it is almost a necessity. Client relationships, market share, regulatory compliance and operational efficiency will all benefit as a result.

Matt Hodgson, CEO and Founder of Mosaic Smart Data.