Predictions for ArtificiaI Intelligence and Fintech for 2020

Throughout the past year, the use of artificial intelligence (AI) and other forms of technology within the financial services industry has continued apace. This will increase further as it dovetails with enriched natural language processing (NLP) through 2020 and into the coming decade and lead to more personalisation of services. Indeed, as noted in Crowdfund Insider, the European Union is to invest €100 million in artificial intelligence and blockchain start-ups next year, to boost the EU-wide innovation ecosystem.

Globally, the Fintech revolution offers solutions to all manner of issues, and as we see in so many sectors, algorithms and AI can locate data and highlight trends. In doing so, such technologies operate automatically – and therefore can carry out functions much quicker than by human effort – and at a reduced financial cost as technology mitigates the need for large data-crunching teams.

More specialisation in 2020

AI has been increasingly prevalent with data-rich sources, in particular, those with numeric content and alternate data. As the technology matures, techniques such as context-sensitive Rich NLP will unlock complex unstructured documents and improve the results and insights that can be extracted.

External innovators will proliferate

As we are seeing in Europe, the premise of ‘open banking’ allows authorised Fintechs to provide financial services and products to customers that traditional banks have not previously offered. It has revolutionised the market for app-based mobile services, with many young customers in particular regarding this way of banking as the norm, and not seeing a need to ever go into a high-street bank.

For business-to-business trade, the use of technology has myriad uses and there have been significant advancements across the financial markets. There are many areas that can, and do, benefit from engagement with external innovators, and this will increase. Smaller companies are often more agile in their technological creativity as they don’t have as many hoops to jump through in order to get approval on decisions. Large institutions will continue to take advantage of smaller companies’ innovations by buying in services that might be too costly for them to produce in-house.

Such interactions don’t have to be high-profile banner-making projects. Successful projects, as with start-ups, set small achievable deliverables with their own specific steps within a defined long-term strategy. The important thing is to remain resolutely focused on the immediate requirements without getting carried away with the bigger potential. It is all too easy to overload requirements or involve too many people and lose the immediate narrow focus that actually delivers results. Company executives should remember not to try to run before they can walk!

More need for actionable insights

In the financial services arena, tightening regulations and increasing cost pressures mean that market participants will need to trade in ways that are smarter – and more effective than competitors – and this will require gaining the best insights. Smarter trading will add intrinsic value to a company’s own processes and provide a better financial offer to clients, and therefore lead to an overall competitive advantage in any given financial services sector.

The irony is that investment banks and other financial services institutions are sitting on large repositories of unstructured information, but they don’t always know how to use it. It is a bit like owning a library but not knowing which shelves contain the books required to find the right material. New tools are needed to assess information and create real insights enabling the user to optimise decision-making, for example to carry out a trade or not. The goal is to discover what is relevant in a quicker and more effective way.

Financial research underpins progress

When it comes to honing and modernising information processing, the creation and use of financial research has lagged far behind the consumption of material in other financial services areas. On a daily basis, a bank produces and receives thousands of pages of research on everything from the global economy to any particular company’s share price. Currently, however, sales/trading desks and portfolio managers’ primary tools for extracting the relevant insights from this deluge of information is an inefficient and slow search through an email inbox or via traditional research portals that rely upon classic full-text search techniques which were not designed for this type of content.

There is another way.

Moving forward with AI and Rich NLP

Instead of thinking about a research report in its entirety, the challenge is to understand a document as a series of interrelated insights and details, some of which will intersect with other potential areas of interest and additional articles.

As such, the area of financial research is ripe for change in the coming years. Applying Rich NLP and machine learning technologies to research will provide a smart and ever-increasing matrix of knowledge. By tagging each and every paragraph of every document in context in real-time, a body of research can be transformed from a series of unstructured documents sitting in a digital library into a huge and complex web of granular pieces of tagged information. This ‘Document Atomisation’ will unlock the value buried deep within the research without requiring the analyst to change how they write or publish their articles.

Once the insights in the research have been atomised it opens opportunities that previously had seemed out of reach. One of the main benefits is increased personalization so that each and every individual market participant can receive and access financial research that is tailored to granular needs.

The ability to harness information that is relevant to any given market with pinpoint accuracy will be the way forward for financial players in 2020 and beyond.


Rowland Park is co-founder and CEO of the financial research company, Limeglass.   Limeglass has developed next-generation financial technology to atomise financial research. Park is a proven entrepreneur and leader with over thirty years’ experience in the financial services research industry. He has a successful track record of founding and growing start-ups including IDEA Global and 4CAST, which provided cutting-edge business intelligence and research tools focused on macroeconomics, policy and financial markets.

Simon Gregory is CTO and co-founder of Limeglass.  Gregory has over twenty years’ worth of experience developing online financial market software to his role as CTO at Limeglass. His track record of producing flexible, scalable solutions that are robust and stand the test of time is testament to his innovative approach to technology.

Sponsored Links by DQ Promote


Send this to a friend