Generative Artificial Intelligence (GenAI) is at the center of technological discussions in 2024, leading to changes in many sectors. This trend is no different in payments, one of the pillars of modern finance. With the potential to move billions of dollars, gen AI is transforming everything from basic day-to-day operations to personalization and security strategies.
Today, we will explore the impact of this technology on payments, the challenges it brings, and the main opportunities for companies.
The GenAI revolution
Unlike traditional AI, which performs specific tasks, generative AI goes beyond, adapting to new contexts and creating new solutions. This ability to “think and create” is transforming financial services, including payments, by reimagining how solutions are delivered and problems are solved.
According to McKinsey, generative AI has the potential to add between $2.6 trillion and $4.4 trillion to the global economy annually. In addition, productivity in the financial sector could increase by up to 30% by 2028, benefiting everything from traditional banks to innovative fintechs.
Generative AI in the payment cycle
The payment journey goes far beyond a simple transaction – it involves several steps that need to work in an integrated and efficient way. From data capture and authentication to processing, approval, and financial reconciliation, each phase carries its challenges.
This is where genAI comes in, bringing innovative solutions to optimize and automate the entire process. With its ability to adapt and learn continuously, generative AI is transforming this journey into something more agile, secure, and strategic. Check out some of its main uses in the financial sector:
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Process automation
Companies are using generative AI to automate repetitive tasks and reduce human error. An example is the use of automated invoice reading systems to extract critical data and process it quickly. Tools such as Paymo’s PM Payments allow payments to be made directly from an invoice with a single click, eliminating the waiting time for manual transfers and ensuring greater agility.
In addition, generative AI’s power to understand structured and unstructured data makes it ideal for financial operations on a global scale, where language barriers and different document formats could delay processes.
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Fraud and security
The fight against fraud is one area where generative AI is already bringing impressive results. With the ability to analyze billions of pieces of data in seconds, generative models identify patterns of usual behavior and flag atypical transactions. Visa, for example, has introduced Visa Account Attack Intelligence (VAAI), which uses AI to predict attacks in online transactions, protecting companies against fraud that would cost billions.
By combining traditional fraud detection algorithms with the power of GenAI, companies can respond more efficiently to emerging threats, reducing friction for legitimate customers while making the job of scammers more difficult.
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Personalization and customer experience
In the digital world, personalization is the key to attracting and retaining customers. Generative AI analyzes consumer behaviors and transaction records to offer recommendations adapted to each user. For example, advanced systems can suggest payment methods, offer personalized discounts, or even predict the customer’s next purchases.
Also, chatbots equipped with Generative AI are already helping financial institutions to offer real-time support, with contextualized responses that increase customer satisfaction. This eliminates long waits and improves the customer experience with the service.
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Dynamic pricing
Generative AI is also changing the way banks and fintechs set prices for financial products like loans and insurance. By combining market data, customer behavior, and historical patterns, the technology adjusts prices in real time to reflect demand and minimize risk.
This strategy, widely used by platforms such as Amazon and Uber, is now coming to the financial sector. For consumers, this can mean more competitive rates, while companies can optimize their profit margins.
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Reconciliation and operational efficiency
For companies that handle thousands of transactions a day, manual reconciliation can be a time-consuming and error-prone process. With Generative AI, systems can identify inconsistencies automatically, simplifying audits and financial reporting. This not only saves time but also reduces operating costs.
Managing the risks of Generative AI
The adoption of Generative AI in payments, while promising, brings significant challenges that require close attention. The use of large volumes of data, which are essential for its operation, increases the risk of privacy violations, making strong governance and regulatory compliance indispensable. In addition, AI models can reflect or amplify biases present in training data, which requires constant auditing to ensure fair decisions. Another crucial point is the need for reliability and transparency, especially in sensitive areas such as credit approval and fraud detection, where decisions must be explainable and understandable to everyone involved.
Besides the technical and regulatory aspects, the adoption of Generative AI also raises ethical and economic issues. Companies need to balance enthusiasm for the opportunities with the responsibility to avoid negative impacts, such as the reproduction of harmful stereotypes or intellectual property violations. On the economic level, the transformation in skills and occupations will require investments in qualifications and clear strategies for managing transitions in the labor market. For a fair and sustainable use of AI, companies must share learnings transparently with governments and other sectors, promoting a balance between innovation and responsibility.
Shaping the future of payments with GenAI
Generative AI is bringing operational efficiency, large-scale personalization, and improved security to payments. However, to take advantage of the full benefits of this technology, companies need to keep in mind challenges like data privacy, transparency, and integration with existing systems. Success will depend on the ability to innovate with responsibility, placing customers’ needs at the center of technological solutions.
At Luby, we are prepared to help financial institutions sail through this digital transformation. Our expertise in technological solutions for the financial sector allows us to develop strategies that effectively integrate Generative AI, leading to tangible results such as reduced operating costs, increased revenues, and secure, personalized experiences for customers.
Do you want to transform your payment operation with Generative AI? Contact us!
