Collaborating Authors

UK regulators host first Forum to assess use of AI in financial services


The Financial Services AI Public Private Forum brings the UK's Financial Conduct Authority (FCA) and Bank of England (BoE) together with AI experts from financial services, tech, and academia, to assess whether additional guidance or regulation is needed to support the safe adoption of AI in financial services, per the FCA. The Forum will host a series of quarterly meetings and workshops over the next year to discuss AI uses and benefits, constraints to deployment, and potential risks. The FCA and BoE opened the Forum to membership applications in October 2019, following the publication of their report on the application of AI in UK financial services. The Forum aims to tackle AI-related risks amid rising adoption within UK financial services. We think the Forum should add more fintech members to get a better understanding of AI use in the UK and establish guidelines.

The State Of AI Adoption In Financial Services


Strengthening customer relationships by providing exciting new services that protect everyone's health while saving valuable time is proving to be the financial services' greatest challenge. Fast-tracking contactless, digital support across all channels generates terabytes of data a day that is essential for training supervised machine learning algorithms. Unsupervised machine learning algorithms rely on terabytes of data to discover previously unknown patterns in financial services data. AI is emerging as a new engine of growth by providing useful insights and intelligence in anxious, uncertain times. Financial Services firms are increasing their adoption AI and machine learning to capitalize on the data from new digitally driven channels.

Why now is the right time for AI in financial services


After being a topic of great interest for years since John McCarthy first coined the term in 1956, artificial intelligence is finally out of the lab. Industry leaders are increasingly integrating AI into their value propositions. Ford, the iconic car maker that pioneered the moving assembly line to bring the first common man's car on the roads a hundred years ago, is making investments in artificial intelligence (AI) firms, such as Argo to repeat history with its first autonomous vehicle. A hundred years on, the company is working towards employing AI for automated breakpoint repair, eliminating the need for human intervention. Meanwhile, much has been written about the success of AI in retail.

Open source's slowly growing role in Fintech


Most of the time when a business realizes a process helps them they embrace it. This insight came from the Fintech Open Source Foundation's (FINOS) 2021 State of Open Source in Financial Services Survey. This survey, conducted with Linux Foundation Research, Scott Logic, Wipro, and GitHub, found that despite open-source financial services adoption being widespread, there's much more left to be done. That's because many financial firms don't fundamentally understand open source's role in their business and governance strategy. When asked about whether organizations were "open source first" in the survey, 75% said "no" or "they didn't know."

Artificial Intelligence Adoption in Financial Services To Increase by 2022


The latest survey from the World Economic Forum reveals AI adoption will increase across the financial industry within the next two years. A joint survey released by the World Economic Forum and Cambridge Centre for Alternative Finance (CCAF) reveals that while only 16% of companies in the financial sector are using AI tools today, over the next two years, the number is bound to increase to a huge 64% of all financial services brands. What is even more interesting is that 77% of them say they expect AI will become essential to their business. The survey titled'In Transforming Paradigms: Global AI in Financial Services Survey' is based on more than 150 senior financial services executives in FinTech and incumbent financial institutions. As per the survey, the majority of enterprises – 60%- invest less than 10% of R&D resources in AI despite evidence of accelerating returns.