Today, UiPath, Inc. announced a milestone for enterprise business orchestration. One of Mexico’s largest financial institutions, Banco Azteca, has revamped its automation program with UiPath Maestro™. Now the bank manages over 8,800 enterprise processes and more than 300 production automations. Banco Azteca uses a governed, unified operating model to better coordinate people, AI agents, systems and third-party partners.
Banco Azteca’s Automation Journey: From RPA to Full Orchestration
Banco Azteca’s automation journey began in 2020. Since then, it has created an internal AI and RPA Center of Excellence. This in-house hub grew into more than 20 business analysts, data scientists and developers. The program also enjoyed executive sponsorship by Manuel Delgado Forey, Chief Operating Officer and Head of Customer Service at Banco Azteca. Therefore, the bank has developed one of the most mature enterprise automation programs in Latin America.
Banco Azteca has a large branch network and a digital banking platform that assists millions of customers each day. The bank runs thousands of time-sensitive processes every day. These processes include customer service, compliance, fraud prevention, back office operations and post sales support. The need for intelligent and scalable enterprise business orchestration, therefore, became critical for sustained growth.
UiPath Maestro Enables Orchestrated Operations at Scale
As the automation program matured, Banco Azteca realized that automating individual tasks was no longer enough. Instead the bank focused on orchestrating entire business processes. Banco Azteca deployed more than 300 production automations with UiPath Maestro. These automations harness AI and agentic solutions to automate compliance, fraud prevention, legal, procurement, HR, customer service, social media and other core functions.
Therefore, the bank scaled more than 8,800 automated processes across the organization. This output is equivalent to the work of over 3,300 full-time employees. Also, teams across all functions are dealing with growing workloads, while focusing on higher value decisions.
“As our automation program matured, we realized the next opportunity wasn’t automating more tasks. Instead, our focus moved to coordinating entire business processes. Business orchestration allows us to connect people, AI, systems, and partners so work keeps moving while our teams stay focused on higher-value decisions,” said Manuel Delgado, Chief Operating Officer & Head of Customer Service, Banco Azteca.
Elektra Post-Sales Orchestration: A Flagship Use Case
A perfect example of enterprise business orchestration in action is Elektra’s post-sales operation. Elektra.mx is the retail e-commerce site of Group Elektra, parent company of Banco Azteca. The platform also processes requests related to cancellation, delivery and orders that require ongoing coordination with third-party sellers.
Before, all seller interactions were handled manually by employees. All incoming communication is now automatically processed via an orchestrated workflow. The workflow frames outreach to sellers, sends follow up requests, and tracks responses in real time. It also highlights exceptional cases and only reveals exceptions to employees when human judgment is required. And so customer resolution times improved drastically. The operation also got full visibility on all active cases.
Next Steps: AML Surveillance and Smart ATM Optimization
Banco Azteca plans to expand enterprise business orchestration to anti-money laundering (AML) programs going forward. Also, the bank is looking to monitor smart ATMs to optimize the distribution of cash based on real-time customer demand. These next steps continue to signal the evolution from task-level automation to enterprise-wide, governed and scalable operations.
“Banco Azteca’s journey is a powerful example of how automation has changed,” said Ben Fiechtner, President, Americas & Strategic International Markets, UiPath. “Moving from individual automations completing individual tasks to a fully orchestrated operating model unlocks speed, capacity, and production at scale. With people, AI agents, and systems work together across an entire enterprise, you have measurable results and a governed foundation the bank can keep building on as it takes on AML and intelligent ATM monitoring next.”
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News Source: Businesswire.com
