Success Story FSI Sector

A leading Caribbean bank with more than 1.5 million users evolved its customer service ecosystem by implementing an agent-based architecture powered by Agentic AI. By replacing linear workflows with a network of autonomous agents on Amazon Bedrock, the institution was able to humanize its WhatsApp channel, resolving complex transactions in seconds and projecting 20% operational savings, all under a security framework that guarantees zero residual storage of sensitive data, directly improving efficiency and the experience of customers and partners.

ATMs and Inquiries in the Age of AI: The Bank That Deployed a Team of Autonomous Agents.

The main obstacle for this financial giant was not a lack of technology, but the saturation of its traditional channels. With a massive volume of daily interactions, the contact center relied on manual processes that generated friction: wait times that frustrated users and operations limited to office hours. The bank needed to move beyond simply “answering questions” and start “resolving requests” autonomously, regardless of the time of day or the complexity of the transaction.

To transform this reality, Insbuilt designed a Multi-Agent Collaboration architecture on Amazon Bedrock, where a Supervisor Agent coordinates a network of virtual experts specialized in balances, geolocation, and customer services. This serverless infrastructure leverages AWS Step Functions and AWS Lambda to orchestrate real-time reasoning, enabling the chatbot not only to converse through WhatsApp Business, but also to execute secure actions through integrations with the banking core. Security was elevated to a “transient privacy” standard, processing sensitive data exclusively in volatile memory and validating each session through security protocols designed to meet the strict requirements of the financial sector.

The impact redefined the bank’s relationship with its customers: availability increased to 99.5%, eliminating wait times and allowing human staff to focus exclusively on high-criticality cases. Automation not only projected a 20% reduction in operational costs, but also scaled efficiency by processing transactional inquiries in fractions of a second. Today, the institution has a solid Agentic AI foundation ready to deploy new “virtual specialists,” strengthening its leadership at the frontier of autonomous banking in the region

 
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