Financial analysis & operational intelligence
Agents that read financial data and documents, interpret them and support decisions.
Financial analysis & operational intelligence is an Aginies solution package for the Fintech & Payments sector in the “financial analysis & operational intelligence” area. What the agents do: The financial assistant answers questions straight from statements, ledgers and reports; every figure links to its source; the invoice-processing agent extracts the document, matches it to order and receipt, and flags exceptions. Expected outcomes: reconciliation and invoice cycles drop from days to hours; decisions taken on current, source-linked data; exceptions and risk patterns visible before they materialise. The package uses the Entity extraction, Multi-source RAG, ERP / core tools (MCP), Anomaly detection capabilities of the Aginies platform and can be watched live through the Merchant operations assistant: POS, settlement, refund and limit, Payment reconciliation exceptions, Supplier invoice three-way match, BNPL instant instalment decision scenarios in the agent library.
Finance teams stitch data together by hand across invoices, statements and investment instructions. Reconciliation exceptions surface late; by the time the analysis is ready, the decision window has closed.
- 01The financial assistant answers questions straight from statements, ledgers and reports; every figure links to its source.
- 02The invoice-processing agent extracts the document, matches it to order and receipt, and flags exceptions.
- 03Investment instructions are analysed: amount, instrument, limits and suitability rules are checked.
- 04Above-threshold transactions and anomalous patterns reach the finance manager with a reasoned summary.
- Revenue, cost and cash data collected and validated from several sources
- Variance analysis, anomaly detection and root-cause explanation
- Management report draft: tables, charts and commentary with sources
- Q&A: data-backed answers to questions such as “why did marketing cost rise this month?”
- Read access to the data warehouse or ERP reporting layer
- Chart of accounts, cost centres and KPI definitions
- Report templates and distribution list
Derived from the linked scenarios: the supervisors, specialist agents, models and systems that run this package.
Summed from the simulation definitions of the linked scenarios; recalculated for your scale in the discovery session.
- Reconciliation and invoice cycles drop from days to hours
- Decisions taken on current, source-linked data
- Exceptions and risk patterns visible before they materialise
| Monthly report preparation time | 60–70% shorter |
| Time to detect an anomaly | From month-end to the same week |
| Report statements with a source | 100% |
Target ranges from comparable deployments; baseline and target are fixed together in the first week of the pilot.
Scenario-level approval rules plus the package’s general controls.
- Merchant operations assistant: POS, settlement, refund and limitRefund > 25,000 or limit increase > 50% → risk team approval
- Payment reconciliation exceptionsSingle break > 10,000 or total > 50,000 → finance manager approval before adjustment
- Supplier invoice three-way matchPrice deviation > 2% or > 1,000 TL → buyer approval
- BNPL instant instalment decisionBasket > 15,000 or bureau score < 1,200 → underwriter approval
- packageReports are distributed with the finance manager’s approval; the agent drafts
- packageRole-based data access; payroll and salary data under a separate policy
- 1 · Documents and rule set · 2 weeksDocument types, field dictionary, matching and tolerance rules written with the finance team; a sample set labelled.
- 2 · Parallel run · 4 weeksAgent and current process handle the same documents; the difference report reviewed weekly, cut-over when the accuracy threshold is met.
- 3 · Close integrationTied to the month-end calendar; exception queue, audit trail and reconciliation reports opened to internal audit.
This package’s scenarios in the agent library
Merchant operations assistant: POS, settlement, refund and limit
The merchant writes on WhatsApp; POS fault, settlement query, refund and limit increase are resolved in one dialogue.
Payment reconciliation exceptions
PSP settlement files matched to the ledger; small breaks fix themselves, large ones go to finance approval.
Supplier invoice three-way match
Invoice, PO and goods receipt matched in SAP automatically; only out-of-tolerance lines reach a buyer.
BNPL instant instalment decision
Checkout instalment decision in seconds from bureau and open-banking data; large tickets go to underwriting.
Time to move from experimenting with AI to transforming with it.
In a 30-minute discovery session we take your 2–3 priority business problems, show a live demo of a similar scenario, and draft a roadmap that starts with the Value layer.
- Your 2–3 priority problems
- Live demo of a similar scenario
- Roadmap starting with value analysis