IA is now integrating financial sector processes at the beginning of the payment journey.

According to data from Abecs (Brazilian Association of Credit Card and Services Companies), R$4.1 trillion in purchases were made using credit, debit, and prepaid cards in 2024, representing a 10.91% increase compared to the previous year. This significant transaction volume necessitates solutions that structure financial processes within companies, thereby fostering significant advancements in the integration of pricing, payments, and operations, with support based on artificial intelligence (AI).

According to Lígia Lopes, CEO of Teros, a smart automation company that transforms data into results, traditionally, the processes of acquisition, sales, onboarding, collections, retention, and pricing were operated by separate, non-communicating departments. This fragmentation generated inefficiencies, increased costs, and hampered strategic decision-making.

Now, with AI and automation, it's possible to integrate these decisions directly into production workflows in real time, ensuring greater efficiency, reducing bottlenecks, and a smoother consumer experience. "The old logic treated payment as the final stage of the financial journey. We've inverted that thinking. Today, payment and pricing should be at the center of the operation, informing the process from the start. This change 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 already done, companies in other segments will begin investing in their own data platforms and integration solutions. In this context, efficient API management and information flow becomes essential, especially given the proliferation of internal and external data sources.

A practical example cited by the expert for this integration possibility is Uber, where payment occurs at the start of the journey, not the end. "This model allows a completely fluid and integrated process thanks to the embedded technology, and illustrates how payment can be repositioned within the productive journey, creating a more efficient and satisfactory experience for the consumer."

Another key point is the role of Open Finance as foundational technology. Along with the initiative of sharing banking data, Open Finance also represents a technical standard that allows different institutions and systems to interconnect securely and scalably. This standard is being expanded to what experts already call... OpenXAn open and standardized approach to integrating diverse data types and services.

"This standardization enables the creation of automated decision rules that function within the actual operational flow. Instead of isolated and disconnected decisions, companies begin operating with embedded intelligence, connecting their legacy systems with new layers of automation without requiring major restructuring," complements Lígia.

She further highlights that adopting modular models allows companies to update or replace components of their solutions without disrupting production processes, which promotes scalability and constant adaptation to new regulatory or market behavioral requirements. This means decisions like granting credit, approving payments, or setting prices can now be made midway through the purchase process, rather than only at the end.

"The advancement of artificial intelligence allows these decisions, soon, to be made based on rules written in natural language, validated by trained models, with automatic optimization suggestions. This represents a giant technological leap, as well as operational and strategic one for organizations," concludes the CEO.