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The status of AI adoption in financial services

The status of AI adoption in financial services

By G.H.

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November 23, 2020

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Companies

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Strengthening customer relationships by offering exciting new services that protect everyone's health while saving valuable time is proving to be the greatest challenge in financial services. 60 percent of banks have closed or reduced branch hours while accelerating new digital capabilities, including automated account creation (34 percent), remote identification and verification (23 percent) and contactless payments (18 percent), according to a Deloitte Digital report.


The fast, non-contact digital support on all channels generates terabytes of data per day, which is essential for training in 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 growth driver by providing useful information and insights in times of uncertainty and anxiety.

Where AI is adopted in financial services

Financial services companies are increasingly adopting artificial intelligence and machine learning to capitalize on data from new digital channels. An EIU (Economist Intelligence Unit) research report found that 86% of financial services executives plan to increase their AI-related investments until 2025.

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The study The road ahead: Artificial Intelligence and the Future of Financial Serviceswhich we suggest you take a closer look at, analyzes the sentiments of 200 CEOs and senior executives at leading investment banks, retail banks and insurance companies in North America, Europe and the Asia-Pacific region. In summary, the key findings of the study, which highlights the state of AI adoption in financial services, are as follows:

  • Investment banking firms are the main adopters of AI and machine learning technologies in financial services, followed closely by distribution. Investment banking operations rely on machine learning to refine algorithms and forecasting models to quantify and reduce risk. Retailers rely on predictive analytics to generate new ideas that can help them build customer loyalty and move customers from physical to digital channels.
  • 37% of financial services companies worldwide are adopting AI to reduce operational costs, followed by predictive analytics to improve decisions and increase employee ability to handle volume-based tasks. AI projects combine cost reduction, revenue savings and time savings through automation. North America leads all other regions in the use of AI to improve personalized service and customer satisfaction. The research team at The Economist found that 36% of large accounts also consider more effective marketing products and services to be a significant advantage, a view shared by only 23% of small retailers.
  • 33% of North American financial services companies expect artificial intelligence to change the way they innovate, placing them well ahead of all other regions. North American companies are also the most optimistic about AI's ability to enable them to launch new products and services (31%). APAC and North American financial services executives see this as a greater opportunity to penetrate new markets (at 30% and 27% respectively). According to the The EconomistThis reflects the higher rates of economic growth in both regions in general compared to the rest of the world and the level of investment in AI by individual companies to support business growth.


  • Customer and stakeholder satisfaction is the most important key measure of the success of an AI strategy in financial services today. AI projects in pilot phase and in production this year are based on improving revenue potential by removing cost and time barriers. Launching new digital channels and improving the customer experience the first time around puts greater emphasis on customer and stakeholder satisfaction this year.
  • The high cost of AI technology is preventing financial services companies from adopting it in more areas of their organizations. Cost constraints are slowing the adoption of AI more than any other factor today. Insufficient infrastructure and data quality are the second and third reasons cited for not adopting AI more broadly within an organization. The research team at The Economist found that 86% of financial services executives plan to increase investment in ATI-related technology over the next five years, with the strongest views expressed within APAC (90%) and North America (89%). Investment in AI technology could help address problems with existing systems that have proven, along with system upgrades, to be a costly constraint that financial services firms have faced for decades.