Financial AI is the most strategic AI sector in London benefitting from scale and access to large and local clients, according to a recent CognitionX report commissioned by Sadiq Khan, Mayor of London.
One of the measures used by CognitionX is the presence of AI suppliers, defined as companies that sell at least one AI product as well as those that do AI research.
There are now over 12,000 AI suppliers globally, with London home to 140 serving the financial sector. San Francisco and New York beat out London, but the figure represents 77% of the size of the finance AI supplier base in the Bay Area according to CognitionX’s international comparisons.
Some of the “notable AI companies” in the report include Acorn Machine (OakNorth), Moneyfarm, Heckyl, BMLL, Cube, Cleo, Previse, Ravelin, and Featurespace.
OakNorth, for example, has raised £306m in funding of which some will go to Acorn Machine, a machine learning-based platform licensed to lenders.
Also mentioned in the report was AlgoDynamix, which uses unsupervised machine learning for risk forecasting in the financial industry.
AI adoption in finance varies according to use case of which there is a very broad range, wrote researchers. Those use cases include fraud detection, credit and payment data analysis, customer engagement, analysis of company data, algorithmic trading, market analytics, regulatory compliance and risk management.
“In retail banking, expert interviews highlighted that AI adoption was still in its early days. Customer facing applications faced a number of adoption barriers such as regulatory and GDPR compliance while back office applications faced fewer barriers,” according to the report.
Cited experts said that financial AI has plenty of room to run. Joanne Smith, CEO of regtech startup Recordsure, commented that “adoption of AI in finance remains nascent” indicating large untapped demand over the medium and longer term.
London was also a strong contender for AI services in insurance and law, which, when combined with finance, are expected to have “network effects”.
“Cross-sector AI applications could be transformational. For instance, the legal market is testing sophisticated AI-driven document review solutions which have clear use cases in finance and insurance,” researchers said in the report.