The global business spend on AI-enabled financial fraud detection and prevention strategy platforms will exceed $10 billion globally in 2027; rising from just over $6.5 billion in 2022.
Growing at 57% over the period, the report predicts that as fraudsters become more sophisticated in their attacks, merchants and issuers will become more adept at utilising highly advanced AI-enabled fraud detection methods to combat crime. The report identified the ability of AI to recognise fraudulent payment trends at scale as being critical to provide improved fraud prevention.
AI-enabled fraud detection and prevention market platforms use AI to monitor transactions and identify fraudulent transaction patterns; reducing fraud risks by blocking transactions in real-time.
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Cost savings to drive AI use
The research analysis predicts cost savings from AI deployment will be critical to taking system use beyond regulatory compliance. Providing a genuine return on investment on fraud prevention services, with improving models and greater data access creating a virtuous circle of improvement.
It forecast growth of 285%, with cost savings reaching $10.4 billion globally in 2027, from $2.7 billion in 2022.
Research author Nick Maynard explains further: “By leveraging AI, businesses can shift their fraud management resource to where it matters, investigating the key issues, rather than dealing with endless false positives, boosting efficiency.”
Differentiation key to success for vendors
Additionally, the fraud detection report found that AI is increasingly standard within financial fraud prevention services; making differentiation a challenge. The research recommends vendors focus on access to transaction and trends data, as gaining the best level of network intelligence will allow businesses to benefit from fraud information from beyond just their own transactions; significantly improving fraud prevention.
The research recommends vendors make partnerships with third parties, such as credit bureaus and payment networks, to improve data coverage.