Agentic AI in finance speeds up operational automation
Agentic AI delivers results in finance only when it sits on a clean, well-governed data foundation. That's the focus of SEI's engagement with IBM Consulting: redesign processes, upgrade critical systems, and build a data-enabled core that scales. The goal is simple-consistent client experiences and faster, more reliable operations.
The ROI doesn't come from picking a model. It comes from auditing workflows and removing repetitive admin work that burns hours and attention. Many firms see up to a 40% cut in processing time when automation handles standard queries and basic data entry. That time is then shifted to high-value client work.
Audit first: SEI and IBM's approach
Adoption fails when new tech is bolted onto broken pipelines. SEI and IBM are running a discovery phase that maps current systems, data architecture, and daily routines with subject matter experts on both sides. This upfront work strengthens governance and risk controls while revealing where agents can safely slot in. The IBM Enterprise Advantage platform is the backbone guiding deployment to improve decision-making and elevate the client experience.
Sean Denham, Chief Financial and Chief Operating Officer at SEI, said: "As SEI enters its next phase of growth, investing in how we operate is just as critical as investing in what we deliver. IBM brings deep industry and technical expertise that will build on our strong operational foundation and strategic vision. By deploying and scaling AI across the enterprise through a disciplined, data-driven approach, we will work more efficiently, innovate faster, and scale with confidence."
Glenn Finch, Head of US Financial Services at IBM Consulting, added: "SEI has a long-standing reputation for operational excellence and building integrated solutions in a complex, highly regulated industry. By combining SEI's deep knowledge of its business with IBM's expertise in process intelligence and agentic AI, we can unlock new levels of efficiency across the enterprise. With streamlined operations and data-centric insights embedded into how work is performed, SEI is strengthening its ability to scale while further differentiating itself in the market."
Direct human oversight to value creation
Agentic systems take on repetitive, rules-based work so teams can focus on clients and complex problem-solving. Output quality gets more consistent, and handoffs become smoother. As Denham put it: "Automation will enable our teams to spend less time on manual, repetitive work and more time on higher-value, relationship-driven activities-further elevating service quality, strengthening trust among our clients, and creating more opportunities for professional growth."
Where agents pay off first
- Client intake triage and routing across channels (email, portal, voice notes).
- KYC/AML pre-checks, onboarding checklists, and document collection nudges.
- Document classification, data extraction, and structured entry into core systems.
- Reconciliations, exception triage, and queue prioritization by risk and SLA.
- Standard client inquiries, case summaries, and follow-up task creation.
- Recurring report generation, variance explanations, and compliance attestations.
Guardrails that make it safe
- Data hygiene: clear ownership, lineage, and refresh schedules for source systems.
- Access controls and PII handling baked into every integration.
- Human-in-the-loop for exceptions, final approvals, and model drift reviews.
- Audit trails for prompts, actions, and decisions-tied to policy.
- Change management: role design, training, and measurable adoption plans.
90-day playbook for operations leaders
- Days 0-30: Map top 10 processes by volume and SLA pain. Capture current cycle time, touch time, rework, and exception rates. Identify structured data gaps.
- Days 31-60: Pilot 2-3 agent use cases with clear boundaries (e.g., intake triage + data entry). Stand up human review and escalation paths. Track quality and time saved.
- Days 61-90: Expand integrations, harden controls, and move to production for the best pilot. Update SOPs, training, and performance dashboards.
Metrics that prove it
- Cycle time and average handle time.
- Straight-through processing rate and exception rate.
- FTE hours saved and SLA adherence.
- Defect/rework rate and audit findings.
- Client CSAT/NPS for impacted journeys.
Tech stack notes
Agentic AI works best when paired with process intelligence, event logs, and clean integration into core platforms (CRM, portfolio/accounting, case management). Retrieval over governed data and real-time monitoring turn "just automation" into reliable operations. For SEI, SEI is partnering with IBM Consulting with IBM Enterprise Advantage as the technical base to drive consistent, auditable outcomes across the firm.
Bottom line
Don't start with code. Start with the map. Thorough process discovery, strong data hygiene, and clear guardrails let agentic AI reduce waste and improve P&L without adding risk. Get the foundation right, then scale with confidence.
For deeper practical guides and examples, see AI for Finance and AI for Operations.
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