Finzly brings agentic AI to payments and operations
Finzly is extending its payments platform with agentic AI woven across the stack. The company's Agentic Galaxy introduces deployable AI agents that help banks and credit unions move faster, reduce operational drag, and deliver smoother customer experiences.
At the core is a set of specialized AI modules that touch every layer of payment processing and operations. Workflows across payments, FX, and virtual accounts get automated, exceptions get handled faster, and users get assistive tools that cut manual steps without adding complexity.
What's new: intelligence embedded, not bolted on
Instead of treating AI as a sidecar, Finzly builds it into the ISO 20022-native architecture that powers its Galaxy suite of money movement products. That means fewer extra layers, fewer brittle integrations, and efficiency gains you can measure.
As one industry advisor noted, this approach puts intelligence deep in the core of payments and operations, helping institutions move from a reactive stance to an ongoing cycle of improvement.
How operations teams benefit
- Exception handling: Auto-triage, summarize case context, propose next actions, and route for quick approvals.
- Payment routing: Optimize across ACH, wires, RTP, and FedNow based on cost, cutoff times, and SLAs.
- ISO 20022 enrichment: Fill missing fields, validate formats, and flag data quality issues before release.
- Sanctions and fraud review: Reduce false positives with AI-assisted screening and transparent rationales.
- Reconciliation: Match transactions to virtual accounts, highlight breaks, and suggest fixes.
- FX operations: Quote selection, margin checks, and exception workflows with clear audit trails.
- User assistance: On-screen guidance inside ops consoles to complete tasks in seconds instead of hours.
Finzly keeps a human-in-the-loop governance model to preserve accuracy, accountability, and compliance. AI drives scale and speed; people keep final control where it matters.
Why this matters now
- Stay competitive: Embedding AI in core processing automates operations and accelerates product delivery.
- Increase efficiency: Agents streamline payments and deposits, reduce errors, and free teams for higher-value work.
- Adapt with confidence: Continuously learning systems help institutions keep up with regulatory change and market shifts.
Practical metrics to track
- Straight-through processing (STP) rate and rework volume
- Average time-to-resolution for exceptions and investigations
- Queue size, backlog age, and after-hours interventions
- Hold durations and release times for payments under review
- Operational cost per payment and per exception
- Sanctions false-positive rate and case handling time
- SLA adherence across rails and cutoff compliance
- FX spread leakage and margin protection
Getting started: an ops-focused checklist
- Pick 3 high-friction workflows with measurable impact (e.g., sanctions review, returns, routing).
- Define policies and approval thresholds; codify what requires human signoff.
- Connect data sources and logs so agents can explain decisions and produce audit trails.
- Pilot in shadow mode, compare outcomes, then phase to supervised production.
- Set alert severity tiers and escalation paths; tune weekly based on case data.
- Close the loop: use outcomes to retrain models and retire low-value manual checks.
- Coordinate with compliance and risk early; document controls and testing.
- Prep change management: short training, playbooks, and KPIs on a single page.
Standards and infrastructure
Deep alignment with ISO 20022 helps with richer data, cleaner reconciliation, and better screening. For background on the standard, see SWIFT's overview of ISO 20022 here.
As instant rails expand, intelligent routing and exception handling become a must-have. Learn more about the FedNow Service from the Federal Reserve here.
Bottom line for operations leaders
Finzly's Agentic Galaxy brings AI into the core of payments and operations, not as an add-on but as part of the foundation. The result: fewer handoffs, fewer delays, and more clarity in decision-making-while keeping governance tight.
If you're leveling up team skills around AI in financial operations, explore focused resources on AI for finance and automation here.
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