Technological innovation and disruptive technology are rapidly becoming game changers in the financial markets sector. For our clients, the adoption of new tech in the retail sector is helping to drive the increasing customer expectations of their corporate clients and the shifting landscape of regulation and cybersecurity means that market infrastructure is under pressure to respond.

For us, it is obvious that blockchain, or distributed ledger technology (DLT), has received the most hype in the media in recent years and is also arguably the furthest down the line to becoming an industry standard for certain processes. Last year the Bundesbank launched a pilot for a blockchain-based securities settlement platform, while a number of other working prototypes and pilots are currently underway for custody and post-trade clearing.

While DLT has been the transformative technology that has caused the most excitement in recent years, rapid advancements in AI, or machine learning, are now causing a significant stir. It’s becoming clear to many of our clients that AI has the potential to deliver significant competitive advantage and real value in financial markets and perhaps a lot more quickly than the industry would have guessed.

This “stir” around AI has also resonated with the media, where we are seeing a seeing a significant increase in machine learning related stories. Looking back across the past month, 125 articles relating to blockchain appeared in six of the core banking titles, yet there were 153 articles around AI. While blockchain is still taking up a significant number of column inches, it looks like interest could be plateauing as another disruptive tech takes centre stage.

Yet while there is an abundance of content on the possibilities of AI and how it will revolutionise different aspects of the industry, there are fewer stories about this technology being put into practice and this is therefore something that journalists are keen to hear about. As a general trend, we saw that a lot of the blockchain content focused on funding of new schemes and proof of concepts, while the content on AI was on possible best use cases. This reflects what we are seeing take place in the market.

Across financial services, robo-advice is an area where AI has been able to take off quite quickly, but for financial markets, most machine learning technologies remain in their infancy. The main challenge for many of our clients and other players in the market of meeting the ever-evolving regulatory changes taking place have taken a large role in dictating how and where budgets and resources are allocated.

However, there are several areas identified where AI presents a significant opportunity for wealth generation in financial markets. The use of predictive analytics for the assessment of market impact of trade executions is one, where expectations are that it will lead to enhanced execution strategies for a strategic competitive advantage.

Firms are also increasingly going to be able to use AI technologies that are primarily used for non-wealth generation purposes as alternative wealth generators. RegTech presents a number of opportunities here. For example, Natural Language Processing and other compliance led machine learning technologies capture vast quantities of data, which was previously unavailable. Firms are already looking at how these unwanted regulatory costs can be used as revenue creators.

Bringing these ideas and technologies to fruition may still take some time, although most of the industry experts we speak to acknowledge that this is now happening much faster than initially thought. From a media perspective, blockchain may be the reigning industry buzzword champion, but it is already receiving some heavy competition from AI as recognition grows for the ultimate transformative impact that machine learning could have on financial markets.