The value of market and transactional data is nothing new. It’s the lifeblood of financial markets and an integral component in every market participant’s toolkit. Every institution uses its data differently - but what unites many of them is that they are not fully maximising its value. 

In the Fixed Income, Currencies and Commodities (FICC) markets, this is particularly apparent. All FICC businesses are under unparalleled pressure due to the changing risk conditions and scrutiny that has increased largely as a result of the constraints of new regulatory initiatives.

Firms across the sell-side, buy-side as well as exchanges and CCPs, are all struggling to unlock the value in their data to help them to tackle these critical challenges. Thankfully, there is a solution: advanced analytics. 

However, it’s not quite as simple as flicking a switch and suddenly extracting actionable insight from your data. All analytics programmes must begin with putting fundamental data foundations in place. Without the right preparatory work, valuable insights may remain inaccessible. 

Quality over quantity is also key. Consuming vast swathes of market data is no longer the be-all and end-all of data usage. Instead, intelligent data analytics is based around the premise that less data that is more comprehensive is better than vast quantities that lack value.

Despite this, some market data vendors are still trying to sell unyielding swollen data sets that are incoherent, unwieldy and require huge amounts of time to extract anything of any value. 

For a bank to truly transform its FICC business, it must turn its big data into smart data. But how can this be achieved? Banks’ technology teams can’t possibly work across every possible project and explore the full potential in all emerging fields such as data science and AI simultaneously. Even the largest firm would struggle to find the internal resources to ensure each avenue is explored thoroughly.

Knowing when to engage the help of specialist fintech partners is a critical step towards gaining a competitive edge. Perhaps the most obvious question a firm should ask is: what is this project’s chance of success?

In today’s environment banks must do everything in their power to ensure they minimise innovation risk - and the quickest route to success is partnering with innovative fintech startups to implement best-in-class solutions quickly and efficiently, with predictable and transparent costs.

One step at a time: the journey to successful analytics

Like all FICC market participants, banks sit on a vast untapped bedrock of market and transactional data. This data is a precious commodity, but the majority of these institutions are unable to harness it in a way that allows them to provide added value services direct to customers and generate more income for themselves. 

In the era of COVID-19 and the subsequent shift to a digital working environment, banks have to be smarter than ever when it comes to gaining a comprehensive view of their data and extracting value from it. While people are speculating that the end of the ‘new normal’ might be on the horizon, the impact it has on the way we work and where we work from is undoubtedly set to remain, with efficiency being the key. 

The journey to a successful data analysis programme begins with the normalisation of transaction and market data. Aggregating, standardising and enriching data sets are the foundation of any successful analytics programme.

From this solid foundation, advanced analytics tools can then begin to deliver value, providing insights across the organisation. The critical gain firms will experience on this journey is analysis and reporting becoming dynamic, actionable and profitable.

Tackling complexity

When you consider how many clients that banks cover, all with different needs, demands, areas of expertise and areas of focus, this journey can be daunting and complex. But as the financial services industry has transitioned towards a remote working future for the time being, effectively monitoring internal teams and external clients is more essential than ever before.

This challenge can be overcome most effectively by engaging a specialist analytics firm to cleanse, normalise and enrich raw transaction data. This provides a consolidated real-time view and analysis of the transactions flowing through the organisation, delivered in a language that financial market professionals can understand.

One area that has garnered much attention of the financial markets over the recent years is the utilisation of Artificial Intelligence (AI). Institutions utilising AI have been reported to have a 58% chance of improving profitability. However, the ability to use AI techniques effectively depends on having access to complete and high quality data - a challenge that financial institutions rank as in the top three key hurdles to AI implementation.

In order to act seamlessly and efficiently banks have to be able, at the drop of a hat, to answer questions like, who are their best clients? Which asset class is seeing the most business? and many more. The answers to these questions lie in transaction data, real-time analytics and AI, however the vast majority of banks do not have their data in a place where this is even possible.

What this tells us is that banks must address the fundamentals of their data business before expanding onwards into further technological development. The pandemic has created an uncertain and challenging operating environment, but a carefully planned programme that combines cutting-edge data analytics and AI technology holds the key to driving growth and turning the tide of decline.

In addition, as regulations look set to continue to increase over the near future, competent data sets will not only allow institutions to manoeuvre the new regulatory landscape but also have a significant impact on profitability from the insights that can be delivered as a result of this.

The next six months will be a critical period for all sell-side businesses and partnering with a specialist analytics firm to effectively harness the value locked within data can help ensure an efficient and profitable transition to a post-COVID world.