How CaixaBank drives partner and customer relationships through AI

Corporate policy explicitly incorporates the regulations into its global risk management system. In practice, any AI-based application must follow a clearly defined process before being implemented. “This means that any use of AI must be identified, evaluated, and monitored,” she says. “Before developing a use case, its type, value, and feasibility are validated, and then its risks are assessed. And once implemented, its performance is monitored.” Of course, in a financial environment, customer trust remains a most valuable asset.

Added AI agent muscle 

All this transformation strategy is finding a tangible application in one particular development: a contracting assistant that accompanies the client through digital channels. The system acts as a first point of contact when a user requests information about a product from the CaixaBank website or app. From there, it can answer questions, provide contextual information, guide the conversation, and, when necessary, transfer the interaction to a specialist without the customer having to restart the process. 

For the bank, this ability to understand context is a key differentiator. “Unlike a chatbot that answers a collection of FAQs, this agent is a contracting assistant that understands the context of the conversation with the customer, provides support, and can escalate to a human,” she says. For products like pre-approved loans, it can even lead the conversation to the final step before closing.