Report Details
Publish Date: March 2022
Publisher: AI Forum
Pages: 15
Tables, Charts and Figures: 10
We are in the heart of a digital age, facilitated by falling costs for data storage and processing, increasing connectivity and rapid advances in digital technologies. Artificial intelligence (AI) technologies are becoming progressively important. Worldwide revenues for the AI market, including software, hardware and services, is estimated to have grown 15.2% in 2021 to $341.8 billion, according to the International Data Corporation (IDC).
There are many benefits of deploying AI. Financial institutions are finding that AI can help improve customer experiences, boost revenues and lower operational costs. In this survey, we seek to acquire insight into respondents’ views on topics such as decision making, the most popular use cases, the key obstacles to success and the return on investment (ROI) in AI.
Key findings
The survey showed data management and relationship network understanding are crucial baselines for successful AI initiatives. One third, 33%, of respondents cited data readiness, the ability to integrate internal and external data sources and making AI operational as the top three challenges for AI adoption.
The report also found strong early adoption, but highlighted 32% of financial services organizations saw very limited or zero return on investment. Over a quarter of respondents had either kicked off (13%) or adopted (18%) an AI program; however most (35%) said that they are in the test-and-learn phase of AI adoption, signaling that AI in the financial services industry is still ripe for mass adoption and growth.
Other key findings include:
- Traditional AI use cases for AI in financial services, related to customer onboarding and risk detection – especially KYC, AML and fraud detection accounted for 29% of primary uses cases. However, the joint most common use cases included data managements) and customer insights, which both polled 13%.
- Effective AI implementation is still a hurdle for organizations; the largest challenges cited were data readiness (18%), integrating internal/external data sources (15%), making AI operational (14%) and the availability of skills (14%).
- There is still room for improvement on ROI in AI initiatives; 41% of respondents said that they’re seeing good ROI from AI projects over multiple years, but only 8% cited having seen outstanding results from AI within a few months.
Survey
In mid-2021, Quantexa and AI Forum conducted a survey of over 640 senior business and technology managers from a broad cross section of financial institutions. While nearly 48% of respondents came from Banking, other sectors such as professional services (13%), technology (10%) and insurance (12%) were also well represented.
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