Financial Services Leaders Confront AI Growing Pains as Focus Shifts to Large-Scale Integration

While 91% have launched AI proofs of concept, only 36% are using widely across business functions

The largest financial services firms and insurance carriers are all-in on artificial intelligence (AI), with the vast majority (91%) launching point solutions and proofs of concept over the last year. However, according to new research conducted by EXL, a leading data analytics and digital operations and solutions company, challenges with accessing siloed data and concerns about risks associated with the technology are preventing large-scale, enterprise-wide integration.

The research, published in a report entitled 2024 EXL Enterprise AI Study: Bridging Strategy and Operations is based on a survey of 158 C-suite and other senior decision makers engaged in strategy, technology and business process at the top 20 non-bank lenders, top 100 insurance carriers and tier 1, 2, and 3 financial institutions. Its findings shine a spotlight on key focal points for AI and generative AI (GenAI) development as well as the challenges and obstacles they are facing as they implement these solutions throughout their businesses.

Recommended AI News: HPE Appoints Kristin Major Chief People Officer

Following are some of the report’s key findings:

• AI Pilot Projects Abound, But Most Remain Narrowly Focused: Amid a flurry of AI experimentation, just over one-third (36%) of financial services and insurance firms have implemented company-wide AI initiatives, while the majority (55%) have implemented AI for limited functions within their organizations.
• Business Development, Risk Management and Internal Operations Top Use Cases: Among firms that have integrated AI more widely into core business functions, the key areas of focus have been marketing and business development (47%), risk management/fraud detection (43%) and internal operations, such as claims management (42%) and back-office b****** and payments processing (37%).
• Data Silos Hinder Company-Wide AI Integration Efforts: Among firms that have implemented AI for limited functions, 74% say data silos have been a barrier to enterprise-wide implementation. Among that group, 33% say data is siloed within each business function and 41% say data is siloed in some business functions but shared among others.
• Trust Remains a Challenge for Large-Scale GenAI Projects: A total of 54% of total study respondents have implemented GenAI projects, with 27% having implemented them narrowly and 27% implementing more widely across business functions. Respondents’ biggest concerns regarding the use of GenAI are algorithms operating outside of intended parameters (44%), potential for new regulation to emerge (43%) protecting customer data (42%) and risk of biased decision making (42%)
• Top GenAI Use Cases Focused on Product Development, Customer Experience and Risk: Among firms that are already using GenAI, the top business functions being targeted are product development (93%), customer care/experience (82%), human resources (82%) and corporate strategy (75%). Among firms that plan to incorporate GenAI over the next 24 months, the top areas where they will be focusing the technology are regulatory compliance (52%), risk management (52%) and corporate strategy (52%).

Recommended AI News: DataRobot Introduces Catalyst Program to Help Organizations Accelerate Generative AI Into Production

“The findings of this report are very much aligned with what we’re seeing in our interactions with clients. Virtually every business leader recognizes the enormous potential in AI, particularly GenAI, and they are committing significant resources to build new solutions,” said Vivek Jetley, executive vice president and head of EXL analytics. “However, the number one obstacle preventing these projects from getting from concept to fully integrated, enterprise solution is data. Data is still too siloed and often locked in legacy systems, so businesses need help integrating that data so they can unlock the full power of AI.”

Recommended AI News: 5G-Advanced and 6G Networks Will Need Additional Spectrum

[To share your insights with us as part of editorial or sponsored content, please write to sghosh@martechseries.com]