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Quantexa has published a report in conjunction with AI Forum, the leading independent research and information source for the worldwide Artificial Intelligence (AI) community. The State of AI in Financial Services: Global Survey Results shares findings based on a survey of over 600 senior business and technology managers in the global financial services industry, looking at how AI is being applied to various business use cases.
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.
“Data is becoming ever more important as organizations increasingly digitize,” said Vishal Marria, CEO and founder of Quantexa. “However, these huge waves of data often lead to decision gaps that plague organizations, leaving them unable to extract meaningful value. AI and technological advances such as entity resolution are helping close this data decision gap in a strategic and measured way, allowing organizations to connect siloed data to create a meaningful connected view, that directly leads to higher accuracy, productivity and ultimately trusted decision making.”
"Barriers to success for AI projects can be daunting", says incoming Chair of the AI Forum Advisory Board, Ian Gilmour. "An important takeaway from the feedback from respondents is the need for an organization to work with skilled third-parties to augment in-house AI expertise and increase the probability of success. The fact that such a high percentage of firms are only in the test and learn phase speaks volumes about the gap between expectations and capability. This report provides essential input for business strategy, helping budget committees to identify and resource AI projects that deliver a competitive advantage"
