Finance process automation
AI and workflow automation can support repeatable finance processes, internal approvals, exception handling and routing between teams.
Financial Services
Reduce the manual work behind reporting and control
ETT helps regulated firms cut the manual handling behind management reporting, reconciliation exceptions and evidence preparation. Every workflow is designed with source traceability, permissions and an approval route a reviewer can follow.
Where we start
The workflows we lead with in this sector
Proposed use cases based on how this work is usually organized. None of these is a published client result.
Management reporting
Assembling a recurring report from ledger, CRM and spreadsheet sources, with every figure carrying the system and extraction time it came from, so a reviewer can trace it back rather than re-deriving it.
Reconciliation exceptions
Matching what can be matched automatically and routing what cannot to the right team with the break, the two sides and the age of the item attached.
Evidence preparation
Collecting the records a control test, internal audit or regulatory request asks for, in the format the requester expects, with an audit trail of what was pulled and by whom.
Regulated operations, not finance-department admin
For an authorised firm the work sits inside a regulated operating model: client-money reconciliations, suitability-file completeness, complaint handling and the SM&CR-style question of who is accountable for each control. Automation here is designed around the control owner, not around the spreadsheet.
How it would be measured
Measures to agree before anything is built
A baseline taken after the fact is not a baseline. These are the measures we would ask you to agree, and what each one means, so the before-and-after comparison holds up.
| Measure | What it means |
|---|---|
| Preparation hours | Person-hours spent assembling the report or evidence pack, measured over a comparable cycle before and after. |
| Exception age | How long an unmatched or unresolved item sits before it is closed. |
| Rework | How often a completed item has to be corrected after review. |
| Source traceability | The proportion of figures in an output that can be traced to a named system, record and extraction time without a person going to look. |
Who this is for
Head of Finance Operations, Head of Financial Control, or the COO of a regulated business unit, with the control owner and a technology stakeholder in the room.
What has to be true first
- Read access to the ledger, CRM and reporting sources in scope
- A named control owner who can approve what may be automated and what must stay with a person
- Agreement on the measurement period, so the before-and-after comparison is like for like
The challenge
What teams in this sector face
Financial services teams work in environments where accuracy, speed and accountability matter.
Reporting cycles, reconciliation checks, compliance tasks, audit preparation, customer queries and internal approvals often rely on large volumes of data moving across multiple systems and teams.
When those processes depend too heavily on manual handovers, duplicated checks or disconnected tools, work becomes slower and harder to track.
ETT helps financial services organizations identify where AI and automation can reduce friction, support better visibility and strengthen control across finance and operational workflows.
Where AI can support
Practical use cases
Financial reporting automation
Automation can help bring together data from different systems, support reporting workflows and reduce manual preparation.
Invoice and document handling
AI can help classify, extract and route information from invoices, statements, forms and supporting documents.
Compliance workflow automation
AI-supported workflows can help teams manage evidence, approvals, review steps, escalation and traceability.
AI agents for finance teams
AI agents can support internal queries, retrieve relevant information, summarize cases and help teams act with better context.
Example workflow
Example workflow: from finance query to controlled action
One request, end to end. Each stage shows what happens and the ETT solution behind it, with people kept in control wherever judgement is needed.
Illustrative workflow. The actions, integrations and controls are defined for each deployment. This is not a customer result.
- 01Finance queryAgentic AI and Automation
- 02Data retrievalData and Analytics for AI
- 03AI summaryData and Analytics for AI
- 04Workflow routingAgentic AI and Automation
- 05Approval / escalationvCISO for AI
- 06Audit recordvCISO for AI
Each stage in detail below, with the systems involved and where a person stays in control.
Finance query
A reconciliation check, reporting request or internal finance question arrives, and is captured as a structured task rather than another email in a queue. From the first moment it carries an owner, a deadline and an audit trail.
Typical technologiesLLM agentsEmail & TeamsWorkflow queue
How ETT helpsAgentic AI and AutomationData retrieval
The agent pulls the relevant figures across finance systems, CRMs, spreadsheets and documents in real time, instead of a person chasing each source. Every number arrives tagged with where it came from.
Typical technologiesDatabricksERP / general ledgerData & REST APIs
How ETT helpsData and Analytics for AIAI summary
It summarizes the position with the sources attached, so the team starts from context instead of raw data. Anomalies and exceptions are surfaced up front, not discovered later.
Typical technologiesOpenAIRetrieval (RAG)
How ETT helpsData and Analytics for AIWorkflow routing
The task is routed to the right people and steps, with permissions and ownership applied automatically. Hand-offs that used to sit in inboxes now move on their own.
Typical technologiesUiPathWorkflow orchestration
How ETT helpsAgentic AI and AutomationApproval / escalation
Approvals are requested where policy requires them, and anything sensitive or high-value escalates to a person with full context. The system never acts beyond the authority it was given.
Typical technologiesPolicy & RBACHuman-in-the-loop
How ETT helpsvCISO for AIAudit record
Every action, source and decision is written to an auditable trail, ready whenever auditors or regulators ask. Governance is designed in from the start, not bolted on afterwards.
Typical technologiesCaveloAudit logISO/IEC 42001
How ETT helpsvCISO for AIWhen it cannot complete
A source system is unavailable, a figure fails its validation check, or the request needs an approval nobody has granted. The task stops, keeps everything gathered so far, and goes to the named control owner with the reason attached. It is never completed on partial data and never silently retried.
Where to start
One reporting or reconciliation cycle, measured
Pick a single recurring cycle. We baseline the current preparation effort and exception profile, build the workflow with the approval route your control framework requires, and report the result against the same measure over an equivalent period.
The solutions involved
- AI Strategy and DeliveryFor identifying which finance use cases are viable, valuable and appropriate to prioritize.
- Agentic AI and AutomationFor automating workflows, routing tasks and connecting actions across finance systems and teams.
- Data and Analytics for AIFor building cleaner, more connected data foundations and operational dashboards.
- Data Discovery and Classification for AIFor locating, classifying and preparing sensitive or regulated data before it is used in AI workflows.
- vCISO for AIFor governance, risk, compliance and oversight around AI systems in regulated environments.
Analect: fewer tokens, less storage, proven on your documents.
ExploreFAQs
Common questions
How can AI automation support financial services teams?
AI automation can support reporting workflows, reconciliation, invoice handling, compliance processes, internal queries and data-heavy operational tasks.
Can AI be used safely in regulated finance environments?
Yes, but it needs the right controls. AI systems should be designed with governance, data protection, auditability, permissions and human oversight in mind.
What is finance process automation?
Using technology to reduce manual work across repeatable finance tasks such as reporting, approvals, reconciliation checks, invoice handling and internal routing.
Can AI help with compliance workflows?
AI can support compliance workflows by helping organize information, route tasks, manage evidence, support review steps and improve traceability. It should not replace proper compliance ownership or human judgement.
Why is data governance important for AI in finance?
Financial services data is often sensitive, regulated and business-critical. Strong data governance helps ensure AI systems use appropriate, reliable and controlled information.
Ready to explore AI automation for finance operations?
Request an AI session to explore where AI could support reporting, compliance workflows, finance processes and operational visibility across your organization.
Around four minutes. Indicative guidance based on your answers.