The financial services sector has faced an inflection point beyond Carol Hamilton since 2025. And moving forward isn’t just about managing credit risk and preventing fraud. Instead, it’s the end of AI utilization, better data orchestration, and fragmented decision-making strategies.
But that means more than just a modernisation decision-making system. Getting the risk decision correctly does not come from an isolated correction. Instead, strategies need to be changed towards a holistic approach to credit risk decisions and fraud prevention. And that means that approach works. That means coordinating data automation and decision-making processes to maximize impact.
A reactive approach to risk management will effectively fight fraud and not manage credit risk. Simply put, a reactive approach is not enough. Financial institutions need to embrace proactive, AI-driven strategies that integrate risk decisions across the entire customer lifecycle.
A successful approach includes real-time, AI-powered decision-making, with AI-driven models continually learning and adapting to new fraud patterns.
“It’s a critical moment for a transition from a highly reactive risk management approach to something more intelligence-driven, proactive and dynamic, so credit risk is managed dynamically,” says Hamilton.
Fraud and credit risk are often managed in separate silos, Hamilton says. As a result, we missed inefficiency and insights. A unified decision-making approach allows for improved risk assessment, faster response times and enhanced customer experience.
Therefore, financial institutions should invest in a unified decision-making platform to eliminate silos, reduce inefficiencies, and improve the accuracy of risk assessments.
Financial service providers are increasingly aware that AI can enhance credit risk assessments, enhance fraud detection and improve operational efficiency, but that is only part of the equation. While it is true that AI adoption is accelerating, it remains an important barrier with insufficient data integration.
Financial institutions embracing this transformation are better positioned to mitigate risk, drive growth and deliver a great customer experience.
The scope of the challenges facing the sector was highlighted by a global survey conducted by Provenir earlier this year.
Key decision makers for financial services providers were investigated to understand the challenges of risk decision-making and fraud across client lifecycles, investment priorities, and AI opportunities.
Almost half of financial services executives revealed they struggle to manage credit risk and detect and prevent fraud.
The survey also reveals that AI plays a prominent role as many people revamp their credit risk decision-making and fraud prevention strategies in 2025.
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Almost 60% find it difficult to deploy and maintain risk decision-making models.
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55% of executives recognize the value of AI to make streamlined strategy decisions and their ability to provide recommendations for AI-powered performance improvements.
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37% say they struggle with effective data orchestration to prevent application fraud, especially in that new data sources cannot be easily ingested and integrated.
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36% are challenged to use AI and machine learning to prevent fraud.
Key customer and account management priorities are real-time event-driven decision-making (65%), eliminating friction across the customer lifecycle (44%), and increasing customer lifetime value (44%). More than half of respondents agree that the biggest data challenge they face is the ability to easily integrate data sources into their decision-making processes.
“I think investment is definitely happening. There are also a lot of projects that are about to get off the ground and start. That remains a challenge, but I’m looking at investment, but I feel that AI is still moving an organization that is taking it in business and thinking about how to make it effective.”
Hamilton suggests that organizations should consider starting scaling smartly on small scales to mitigate risk and ensure measurable impact. That means starting with AI projects that provide fast return on investment, such as credit scoring and automated customer decisions, or there may be a slight fewer regulated areas such as fraud detection. A step-by-step approach focusing on early victory builds confidence in AI-driven strategies while demonstrating concrete business values.
“U.S. and Canadian banks are leading claims in AI adoption, with nearly two-thirds of them investing in AI, and now they’re higher than any other region. That’s a really positive sign, but consolidation remains a challenge for North American banks.
“We see compliance and security concerns as higher than in EMEA than in other regions, and many people call it a barrier to AI adoption. The challenge for European banks is that they are rich in data, but often struggle to coordinate it together and unlock its power.
“It’s a critical moment for businesses to act, but I think it’s a very positive indication that there’s so much energy to get these projects off the ground, to integrate decisions, bring in AI, and optimize data integration.
“The final point is that while discussions are often based on the premise that we reduce risk and stop the bad, we are not really talking about the power we can to actually lock in new opportunities for innovation and growth for these organizations.
“If you really understand the people who are doing business and the threats and risks they pose, you know that it is a small threat and a small risk.
That’s the challenge and a great potential award. AI enables proactive engagement and tailored offers, drive loyalty with AI’s powered decision-making models, maximize customer value, and ensure a more customer-centric approach that allows you to dynamically adapt to customer behavior in real time. Eliminating unnecessary friction while maintaining strong risk control is easy to summarize.
Banks who can use AI and real-time data and insights to deliver smarter, faster, faster, more customer-centric experiences and leverage hyper personalization to increase engagement and lifetime value will be the winner.
“Provenir’s Carol Hamilton on Credit Risk Decision Making, Fraud Prevention and Remuneration” was originally created and published. Retail Banker Internationala brand owned by GlobalData.
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