BrainBlog for AKKA by Eric Newcomer
AI agents are quickly becoming a point of competition among financial services companies, such as BNY and Citigroup. But challenges remain on their journey toward fully agentic systems.
BNY currently uses AI agents as employees, giving them logins, email addresses, and managers for supervision.
A BNY agent can autonomously detect and fix issues in code, although a human still approves a change before it’s deployed.
In January, Citi announced that it’s working on agentic AI systems for the “do it for me” economy, and in July started deploying agentic systems internally for developers to automate software patches and upgrades.
Citi predicts applicability to a broad range of additional use cases, including personalizing new product offers to customers, virtual financial planners, automating routine operational tasks, real time risk profiling for loans, cashflow forecasting, customer onboarding, and fraud detection.
Agentic AI systems have tremendous potential to reshape the financial services landscape, but financial services organizations face significant challenges moving from current “human in the loop” agents to fully autonomous agentic systems that can reason and take independent action.
A solution such as Akka’s Agentic Platform addresses such challenges by evaluating agents and agentic systems against a complex set of Service Level Aagrements (SLAs) that build trust in the underlying gen AI implementations — such as performance, reliability, availability, accuracy, and safety.
(Akka is widely used in the financial services industry for event driven architecture and IoT integration.)
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