The critical role of data in capital markets’ innovation

New ways of accessing data, and moves to incorporate alternative data sources, have the potential to transform capital markets.

The critical role of data in capital markets’ innovation

New ways of accessing data, and moves to incorporate alternative data sources, have the potential to transform capital markets.

Data availability and usage underpins most aspects of innovation in capital markets.

If you take the four technologies the Association for Financial Markets in Europe has identified as being potential change-makers ­– data and analytics, cloud computing, artificial intelligence (AI) / machine learning, and distributed ledger technology – you can see how data is the thread that runs through them. AI and machine learning need large data sets to train and run algorithms on. The public cloud is an essential part of making data available and accessible. And data is the foundation of distributed ledger technology use cases.

So, what are the next data-based innovations we’ll see in capital markets?

Data availability is driving financial market evolution

Data fuels the markets, creating a self-reinforcing cycle of liquidity. Regulation, such as Europe’s MiFID II, drives the publication of more quote and trade data, making intraday market data available, meaning it’s easier to price more accurately on an intraday basis. This has driven increased volumes of electronic execution, both bilaterally and on trading venues, which in turn produces more market data. And so, the cycle goes round, with data driving market evolution.

The cloud supports new forms of data access

Cloud computing is changing how capital markets provide, consume and use data, shifting data from being a product to a service. Today, fintechs are shaking up the market data industry by offering firms access to data via public clouds, as and when required, so they can tap into new sources of liquidity. Now, firms can easily access new exchanges or trading venues for pricing data. This is invaluable in times of high market volatility, when liquidity can be hard to locate.

Big data unlocks fresh vistas of innovation

Access to large sets of raw data is opening up new possibilities for financial institutions. I see quantitative analysts are increasingly exploring non-traditional data sources to extract differentiating, actionable insights. This alternative data can be anything from public survey and polling data (used by hedge funds to gauge the likely outcome of the Brexit referendum in 2016, and to inform trading decisions), through to consumer spending data, weather data and satellite imagery of supermarket parking lots (which can be used to build a picture of the behavioural trends that can influence equity prices).

I know incorporating this alternative data into mainstream financial institutions has its challenges. This is data with a wide range of sources and formats, and it’s typically unstructured, so it’s not easy to process. Textual data requires the application of natural language processing. And non-textual data, such as imagery, needs complex algorithms that have large processing and memory requirements. Increasingly, it’s cloud infrastructure that makes it possible to process this data, cost-effectively and efficiently. So far, firms are only in the early days of using alternative data. It’s already clear though, that this relatively untapped area is fertile ground for the creation of pioneering data products and for future innovative uses of data.

An exciting future lies ahead

I predict that, as capital markets really start exploring the role and adoption of big data (particularly from alternative sources), we’ll see some compelling innovation in terms of predictive and behaviour analysis, in ways we can’t currently foresee. For example, there’s a lack of meaningful data from traditional sources in ESG investing and the general move towards sustainable finance. How could big data transform that? It’ll be very exciting to see how firms start to use their initiative to address these gaps using AI and machine learning techniques on alternative data sources. One thing is for sure – the role of data in capital markets innovation is set to grow even further.