According to data from Abecs (Brazilian Association of Credit, Debit, and Prepaid Card Companies), R$ 4.1 trillion in purchases were made with credit, debit, and prepaid cards in 2024, representing a 10.9% growth compared to the previous year. This activity has been demanding solutions that structure financial processes in companies to promote significant advancements in the integration between pricing, payments, and operations, supported by artificial intelligence (AI).
According to Lígia Lopes, CEO of Teros, a company specializing in intelligent automation that transforms data into results, traditionally, the processes of acquisition, sales, onboarding, billing, retention, and pricing were managed by separate and non-communicating departments. This fragmentation led to inefficiencies, increased costs, and made strategic decision-making difficult.
Now, with AI and automation, it is possible to integrate these decisions directly into productive workflows in real time, ensuring greater efficiency, reduced bottlenecks, and a smoother consumer experience. ‘The old logic treated payment as the final step of the financial journey. We flipped this thinking. Today, payment and pricing should be at the center of operations, informing the process from the start. This shift in mindset is what makes companies more efficient, personalized, and competitive,’ says Lígia.
The expert explains that this transformation is directly linked to the evolution of technological infrastructure in companies. The trend is that, just as the financial and healthcare sectors have been doing, companies across other segments will invest in their own data and integration platforms. In this context, efficient API and information flow management becomes essential, especially with the proliferation of internal and external data sources.
A practical example cited by the expert for this integration is Uber, where payment occurs at the beginning of the journey rather than at the end. ‘This model enables a fully fluid 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 aspect is the role of Open Finance as foundational technology. Alongside the initiative for banking data sharing, Open Finance also represents a technical standard that allows different institutions and systems to securely and scalably interconnect. This standard is expanding into what experts are already calling OpenX, an open and standardized approach for integrating diverse types of data and services.
‘This standardization is what enables the creation of automated decision rules that function within real-time operational workflows. Instead of isolated and disconnected decisions, companies now operate with embedded intelligence, connecting legacy systems with new automation layers without requiring major restructuring,’ adds Lígia.
She further highlights that adopting modular models allows companies to update or replace components of their solutions without disrupting production processes, which favors scalability and constant adaptation to new regulatory or market demands. As a result, decisions such as credit approval, payment authorization, or pricing can be made mid-process rather than only at the end of the purchasing journey.
‘The advancement of artificial intelligence will soon enable these decisions to 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 an operational and strategic one for organizations,’ concludes the CEO.
