The financial services sector faces a turning point in 2025 and there says Carol Hamilton. And staying at the forefront is not just about managing credit risk and preventing fraud. On the other hand, it is about taking advantage of AI, a better data orchestration and the end of fragmented decision strategies.
But it means much more than just modernizing decision systems. Obtaining a correct risk decision will not come from any isolated solution. On the other hand, there must be a change of strategy towards a holistic approach to the decision of credit risk and fraud prevention. And for that work approach, it means aligning data automation and decision processes to maximize the impact.
A reactive approach for risk management will not effectively combat fraud and will manage credit risk. In a nutshell, a reactive approach is no longer enough. Financial institutions must adopt a proactive and promoted strategy that integrates the risk decision throughout the customer life cycle.
A successful approach includes in real time, decision of power of AI, with models driven by AI who learn and adapt continuously to new fraud patterns.
“It is a critical moment for a change in a very reactive risk management approach to something much more driven by intelligence, proactive and dynamic so that this credit risk is dynamically administered,” says Hamilton.
Fraud and credit risk are often managed in separate silos, says Hamilton. The result is inefficiencies and lost ideas. A unified decision approach allows a better risk assessment, faster response times and improved customer experiences.
Consequently, financial institutions must invest in unified decision platforms to eliminate silos, reduce inefficiencies and improve the accuracy of risk assessment.
While financial services providers recognize more and more that AI can improve credit risk assessments, strengthen fraud detection and improve operational efficiency, that is only part of the equation. It is true that the adoption of AI is accelerating, but the bad data integration remains a significant barrier.
The financial institutions that adopt this transformation will be better positioned to mitigate the risks, boost growth and offer higher experiences of the client.
The scope of the challenge faced by the sector was highlighted by a global survey conducted by coming earlier this year.
The key decision makers of financial services providers worldwide were surveyed to understand their decision and fraud challenges in the client’s life cycle, decision investment priorities and AI opportunities.
He revealed that almost half of all financial services executives have difficulty administering credit risk and detection and preventing fraud.
The survey also revealed that many are renewing their strategies for decision and prevention of credit risk fraud in 2025, with an AI playing an outstanding role.
Almost 60% say they find it difficult to deploy and maintain risk decision models.
55% of executives recognize the value of AI to make simplified strategy decisions, and in their ability to provide recommendations for performance improvement with AI.
37% say they fight with the effective data orchestration for the prevention of application fraud, specifically in not being able to easily ingest and integrate new data sources.
36% have the challenge of using AI and automatic learning for fraud prevention.
The key priorities for customer management and accounts are the decision promoted by events (65%), eliminating friction throughout the customer life cycle (44%) and the increase in customer life value (44%). More than half of respondents agree that the greatest challenge of data they face is to easily integrate data sources into decision processes.
“I would say that the investment is definitely happening, and there are many more projects that are trying to take off and start too. It is the execution, although it is still the challenge. So we are seeing the investment, but I think that AI is still going through a transition from organizations that think they can adopt it in their business and make it effective.”
Hamilton suggests that organizations should consider starting a small one and scaling intelligently to mitigate risk and guarantee a measurable impact. That would mean starting with AI projects that offer a rapid return on investment, such as credit score and automated client decision, or perhaps slightly less regulated areas, such as fraud detection. A gradual approach, focused on the first victories, will generate confidence in the strategies promoted by AI while demonstrating tangible commercial values.
“US and Canadian banks are leading the position in the adoption of AI, with almost two thirds of them investing in the integrated intelligence now, higher than any other region. So that is a really positive signal, but integration remains a challenge for US banks.
“The compliance and security concerns that we see higher in EMEA than in other regions, and many of them call it as a barrier to adopt AI. The challenge for European banks is that, although they are rich in data, they often fight to orchestrate that together, to unlock his power.
“It is a critical moment for companies to act, but I think it is a very positive sign that there is so much energy so that these projects awake to unify the decision, bring AI and optimize data integration.
“The end point is that the discussion is often based on the premise of reducing risk and stopping the bad, but in reality we have not spoken half of what we could around the power to unlock new opportunities for innovation and growth also for these organizations.
“Because if you really understand who you are doing business and the threat or risk of being considered, you will find that where it is a small threat and a small risk, they could be a fantastic customer for you, who wants that time and energy to get involved in the right way to boost the value for them and their business.”
That is the challenge and the potential prize. The AI that allows proactive participation and personalized offers that drive loyalty and maximize the value of the client with decision models fed with AI that guarantee a more client -centered approach that can be dynamically adapted to customer behavior in real time. Eliminating unnecessary friction while strong risk controls are maintained is easy to summarize to execute.
Banks that can deliver more intelligent experiences, faster and client -centered with AI and data and ideas in real time and ideas and take advantage of hyper customization to increase commitment and life for life, will be the winners.
The “decision of decision, prevention and reward of fraud and reward” to come from ‘Carol Hamilton, prevention and reward “was originally created and published by International retail bankerA brand owned by Globaldata.
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