Driving the Agentic Shift in Banking Adoption Governance and Scale [Testμ 2026]

At Testμ Conf 2026, banking and AI leaders from Actinver and Linko argued that agentic AI should initially be confined to controlled, verifiable back-office and engineering workflows rather than customer-facing or money-moving decisions. They distinguished autonomous agents from human-approved copilots using reversibility, verifiability, and whether a cheaper, auditable rules engine could handle the task, while citing customer-record deduplication during onboarding as their sole production example, with human review for uncertain matches and nightly rechecks. The panel emphasized defining guardrails before deployment, testing agents across large sets of realistic scenarios rather than through single pass/fail outcomes, validating their tool-use trajectories and evidence as well as final answers, and requiring agents to stop and communicate clearly when uncertain. Speakers also called for continuous retesting after model updates, staged shadow-mode rollouts, complete observability, bounded fallback paths to deterministic rules or humans, and security layers for autonomous API use. They described voice agents as exploratory and complex, and argued that poor data quality and the integration layer between deterministic banking systems and non-deterministic agents are more significant challenges than legacy core systems.

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