According to data from Abecs (Brazilian Association of Credit Card and Service Companies), R$ 4.1 trillion in purchases were made with credit, debit, and prepaid cards in 2024, representing a 10.9% increase compared to the previous year. Such movement has been demanding solutions that structure financial processes within companies, in order to promote significant advances in the integration between pricing, payments, and operations, with support based on artificial intelligence (AI).
According to Lígia Lopes, CEO ofTeros, an intelligent automation company that transforms data into results, traditionally, the processes of acquisition, sales, onboarding, billing, loyalty, and pricing were operated by separate, non-communicating departments. This fragmentation generated inefficiencies, increased costs, and hindered strategic decision-making.
Now, with AI and automation, it is possible to integrate these decisions directly into real-time production flows, ensuring greater efficiency, reduced bottlenecks, and a smoother consumer experience. "Old logic treated payment as the final stage of the financial journey. We reverse that thinking. Today, payment and pricing should be at the center of the operation, informing the process from the beginning. This shift in mindset is what makes companies more efficient, personalized, and competitive," says Lígia.
The specialist explains that this transformation is directly linked to the evolution of technological infrastructure in companies. The trend is that, just as the financial and health sectors have been doing, companies in other segments will start investing in their own data and integration platforms. In this context, efficient management of APIs and information flows becomes essential, especially in light of the multiplication of internal and external data sources.
A practical example cited by the specialist for the possibility of this integration is Uber, where the payment occurs at the beginning of the journey, not at the end. This model enables a fully smooth and integrated process thanks to embedded technology and illustrates how payment can be repositioned within the productive journey, creating a more efficient and satisfying experience for the consumer.
Another key point is the role of Open Finance as foundational technology. Alongside the bank data sharing initiative, Open Finance also represents a technical standard that allows different institutions and systems to interconnect securely and scalably. This pattern is being expanded to what experts already callOpenXan open and standardized approach for integrating various types of data and services.
"This standardization enables the creation of automated decision rules that operate within the actual flow of operations. Instead of isolated and disconnected decisions, companies begin to operate with embedded intelligence, connecting their legacy systems with new layers of automation, without the need for major restructuring," complements Lígia.
She also emphasizes that adopting modular models allows companies to update or replace components of their solutions without interrupting production processes, which favors scalability and constant adaptation to new regulatory or market behavioral requirements. With this, decisions such as granting credit, approving payments, or setting prices are made during the process, not just at the end of the purchase journey.
"The advancement of artificial intelligence allows these decisions to soon be made based on rules written in natural language, validated by trained models, with automatic optimization suggestions. This represents a huge technological leap, as well as operational and strategic for organizations," concludes the CEO.
