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Case Study

AI Copilot for Bantotal Core Banking

We innovatively crafted an AI copilot for Bantotal, named Bantotal Copilot. This solution transforms its system traces into natural language with GenAI, and streamlines their operations for testers, analysts, and developers alike.

Meet Our Client

Bantotal is one of the leading digital banking solutions in Latin America, impacting over 35 million people. It offers holistic solutions and best banking practices for financial institutions, simplifying and accurately resolving their operations.

  • Headquartered in Uruguay.
  • Launched in 1991.
  • Developed in multi-vendor environments.
  • Key in mission-critical banking operations.
  • Products: Bantotal Core, Bantotal Business Processes, Bantotal Microfinance, Bantotal Mobile Banking, Bantotal Comex, Bantotal Internet Banking, and Bantotal Treasury.

Understanding Challenges

Bantotal banking system consists of hundreds of thousands of programs, which have been built for more than three decades in multiple environments. This presents significant challenges in documentation and understanding of the system.

The complexity and evolution of Bantotal posed obstacles in maintaining updated documentation and achieving a complete understanding of the system, which is crucial for efficient development and problem-solving.

Illustration of a person at a laptop placing a chess piece on the screen and holding a connected-nodes icon, representing strategy and thoughtful decision-making.

Solutions and Activities

Our R&D team developed the Bantotal Copilot in collaboration with Bantotal’s R&D team and Microsoft's AI Co-Innovation Lab. This is an innovative AI copilot designed to address specific operational challenges and bridge the gap between technical complexity and operational efficiency.

We deployed this solution in a pre-production environment, showcasing its adaptability for broader applications across various operational teams.

The Bantotal Copilot can be activated both manually and automatically through an open-source Chrome and Microsoft Edge extension (Browser Copilot). With each user action, it delivers a succinct summary of Bantotal core, involving tables, programs, and web services.

By using the AI copilot, Bantotal users from financial institutions can access:

  • Execution Tree: Offers an in-depth view of operational flows, enabling precise troubleshooting.
  • Performance Insights: Identifies reasons for process delays, fostering swift resolutions.
  • Dynamic Prompt Customization: Users can create and save custom prompts on the fly, enhancing adaptability and future usability.
  • Utilization of Pre-configured and Custom Prompts: Enables a highly personalized and efficient user interaction.

Results and Achievements

The collaboration resulted in an innovative tool that improves operational efficiency, provides observability capabilities, and positions Bantotal at the forefront of banking innovation using artificial intelligence technology for process optimization.

Its implementation has led Bantotal to achieve tangible improvements across the board for all the teams that use Bantotal:

For Testers:

  • Enhanced system comprehension, enabling precise verification processes.
  • Boosted efficiency by quickly detecting and addressing anomalies in databases and transactions.

For Analysts:

  • Empowered them with system insights, and enabled them to navigate system modifications with greater accuracy and less dependency on the development team for information.
  • Streamlined the process of translating business requirements into technical specifications.

For Developers:

  • Reduced the time spent unraveling the functionalities of the complex Bantotal system, leading to quicker and more effective development cycles.
  • Fostered a deeper understanding of the system’s architecture, promoting more robust and continuous innovative solutions.

Overall, we enhanced system understanding, facilitated the updating and maintenance of documentation, and increased efficiency for development, testing, and analysis teams when interacting with the system.

As a result, we've not only empowered Bantotal and accelerated the ability to pinpoint and resolve errors but have also opened up avenues for continuous system enhancement and learning.

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