Fraud prevention is the biggest driver for investments in AI-enabled risk decisioning this year; according to Provenir, the AI-powered risk decisioning software provider for the fintech industry,
This is according to the latest study from Provenir, which canvassed the views of 100 decision-makers from fintechs and financial services firms across Europe.
The response found that other major drivers for investments in AI-enabled risk decisioning include automating decisions across the credit lifecycle (68 per cent), competitive pricing (65 per cent) and cost savings and operational efficiency (61 per cent).
The survey also highlights the role that alternative data can play in the fight against fraud, with 68 per cent of those surveyed choosing to incorporate alternative data for the purpose of improving fraud detection.
Access to data is the biggest challenge to an organisation’s risk strategy (88 per cent), closely followed by a lack of a centralised view of data across the customer lifecycle (74 per cent).
Overall, the findings show that current confidence in credit model accuracy is low, with only 22 per cent of respondents believing that their organisation’s current risk model is accurate at least most of the time.
No respondents believed that their organisation’s risk model is completely accurate.
“The risk of fraud has heightened across the entire financial services landscape, and with attacks only becoming more sophisticated and widespread, it is positive to see that more firms are turning to AI-enabled technologies to minimise these threats,” said Carol Hamilton, SVP, global solutions at Provenir.
“The key benefit of using AI-enabled decisioning for fraud detection is its ability to get smarter with each decision it processes. So, as fraudsters evolve their methods, AI models can use real-time data to identify new patterns, learn, and adapt to constantly detect fraud threats and minimise risk.”
