Artificial intelligence’s impact on the payments landscape is nothing short of transformative – from personalised customer experiences and seamless cross-border transactions to enhanced security and prompt fraud detection, AI-driven innovations are reshaping how we interact with money. While AI is a good enabler, the human factor remains irreplaceable, especially in complex business operations. In 2024, the industry’s overall focus will be placed on security measures and internally tailored and created AI solutions to ease processes on a new level.
Financial institutions and businesses are leveraging AI to enhance payment systems, making them more efficient, secure, and customer-centric than ever before. AI brings increased automation, smarter decision-making, and personalised experiences and revolutionises fraud detection, benefiting the finance industry. All of this contributes to improved efficiency and higher profits – the AI in fintech market size, according to Mordor Intelligence, is estimated to grow from USD 44.08 billion in 2024 to USD 50.87 billion by 2029 (Source). So, the question arises: which areas will be most affected by this transformational source?
It is important to emphasise that the entire fintech industry is knowledge-intensive, and behind every AI technological innovation stands a human professional. AI is a good enabler, a tool doing great pre-work and easing processes, but when the business runs complicated operations, the human factor in service is irreplaceable. The art is to use it to create a symbiotic collaboration between AI and human specialists, complementing human abilities and reducing the amount of manual work and number of man-hours rather than replacing professionals in the payments industry. Therefore, if a business integrates AI into its operations, it does not automatically imply employee job loss.
The human factor is significant in customer service, bringing added value that AI cannot replace. AI’s algorithms empower businesses to predict and analyse customer preferences, delivering personalised product recommendations. In my opinion, businesses need to develop their own AI engines or platforms rather than use and rely on generic ones, ensuring that AI is a good facilitator. Consider this example – when a customer interacts with AI during a call, and a customer service specialist takes over, all relevant information is already available in front of him, ensuring a much faster and more efficient solution for a consumer in need. AI-driven payment platforms, utilising data analytics, adapt payment options to individual preferences, improving seamless experience, customer loyalty, and satisfaction.
AI will play a pivotal role in the future of enhanced fraud detection and prevention in fintech, especially due to the rising number of digital transactions. For instance, it is predicted that the total value of the AI financial fraud detection and prevention market in 2027 will reach USD 10 billion (Source), reflecting a 57% growth compared to 2022. By continuously monitoring transactions, AI identifies and flags potential money laundering activities, facilitating further investigation. With its advanced algorithms, AI enhances the accuracy and speed of identifying illicit financial behaviour, strengthening fraud prevention measures and ensuring a secure and compliant financial ecosystem. Machine learning algorithms can quickly spot patterns and anomalies, helping financial institutions safeguard their customers’ assets and maintain trust in the payment ecosystem. In other words, by utilising AI-powered fraud detection and prevention measures, fintech companies can ensure the safety of their customers’ assets, establish a secure environment, and meet regulatory requirements.
Higher transaction volumes demand greater efficiency and speed. Thus, AI plays a transformative role in cross-border transactions, revolutionising the global economy. AI empowers real-time currency conversions and compliance checks, improving security and eliminating customer bottlenecks, resulting in faster and cost-effective cross-border payments. Additionally, AI-driven analytics analyse market trends and risk factors, aiding decision-making and risk management for businesses involved in cross-border deals. This technology streamlines the international payment process, reducing fees and providing transparency to users during international transactions. For instance, consumers can send money from the UK to India using many different chains of correspondent banks. AI comes in handy in terms of optimizing this flow by processing historical data, thereby making transaction time faster and cost-efficient.
Since Fintech has gone through significant disruption in the past few years, the industry is not expected to consolidate AI’s growth and machine learning resources fully. Still, AI is a trend, and a wide range of AI applications will be utilised in fintechs and banks in 2024, the biggest focus being placed on security measures and customising self-built tools to facilitate processes. Fraud risk management tools and generative AI solutions for automated compliance functions will be seen as the top priority. At the same time, the industry proactively needs to address security risk control and prevention models associated with AI integration in business operations. In the age of AI, the most crucial matter is to ensure data security. Despite societal concerns about potential security risks, this technology is a force for good when adopted and regulated correctly, bringing positive changes for both consumers and business operations.
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