Artificial intelligence (AI) is set to play a significant role as many financial services firms revamp their credit risk decisioning and fraud prevention strategies in the coming year, according to a new survey by Provenir, the AI decisioning solution provider.
Nearly half of all financial services executives are struggling with managing credit risk and detecting and preventing fraud, according to the Provenir survey of 200 decision-makers at financial service providers across the globe.
Over half of all respondents plan to invest in risk decisioning solutions and AI/ embedded intelligence in 2025 and beyond. Currently, nearly 60 per cent of respondents say they find it difficult to deploy and maintain risk decisioning models.
In light of this, Provenir found that 55 per cent of executives recognise that AI could help make streamlined strategy decisions, and in its ability to provide AI-powered performance improvement recommendations, and 53 per cent see the value in the ability to automatically tune models to make better, more accurate decisions.
“Financial institutions are keenly aware of today’s increasingly complex threat landscape and must adopt new approaches for improved risk decisioning and fraud prevention across the customer lifecycle while providing frictionless and personalised customer experiences,” explained Carol Hamilton, chief product officer at Provenir.
“With an AI decisioning platform more closely aligning credit and fraud risk teams, financial services executives can ensure holistic, end-to-end decisioning with a complete view of customers across the entire lifecycle.”
Leveraging AI to combat fraudsters
Key priorities for customer and account management are real-time, event-driven decisioning (65 per cent), eliminating friction across the customer lifecycle (44 per cent), and increasing customer lifetime value (44 per cent). Meanwhile, over half of respondents agree the biggest data challenge they face is being able to easily integrate data sources into decisioning processes.
Survey insights also reveal the pitfalls of operating multiple decisioning systems across the customer lifecycle. Fifty-nine per cent of respondents say this is causing a lack of seamless data flow and unified insights, while 52 per cent say it creates operational inefficiencies. Additionally, 28 per cent said it contributes to an inconsistent customer experience.
When asked about data and fraud, 37 per cent say they struggle with effective data orchestration for application fraud prevention, specifically in not being able to easily ingest and integrate new data sources, while 36 per cent are challenged in using AI and machine learning for fraud prevention. Nearly one-third of respondents agree that the most important aspect of comprehensive fraud strategies is the ability to break down data silos between fraud and credit risk teams.
