Agentic AI Financial Statement Analysis for Spreading and Risk Review
Transform complex balance sheets, profit and loss statements, cash-flow statements, notes and schedules into mapped spreads, ratios, scorecards and analyst-ready memos. Apply your taxonomy, formulas and review rules without the Excel back-and-forth.
- Template and format agnostic
- 25+ languages supported
- Your taxonomy, your rules
Document intelligence by 
within the Cygnet Finalyze experience
within the Cygnet Finalyze experience
Why change Challenges this solution is built to solve
Financial statements are information-rich but difficult to operationalize. Data is buried across tables, notes and schedules, while different accounting labels and formats make manual spreading slow and inconsistent.
Messy, non-standard documents
Public and private company statements vary by format, terminology, language and disclosure level.
Hours of manual spreading
Analysts copy, map and validate hundreds of line items before they can begin meaningful risk analysis.
Important data buried in notes
Debt, related parties, contingencies and segment details may sit outside the main statements.
Inconsistent analyst outputs
Different taxonomies, formulas and spreadsheet versions create review and governance risk.
How it works From raw data to a governed business decision
GLIB.ai agentic document intelligence navigates unstructured financials, while Cygnet Finalyze connects the resulting spreads and risk insights to enterprise credit workflows.
Upload at scale
Process audited reports, private-company financials, management accounts and supporting schedules.
Classify and extract
Identify statements, tables, notes and line items across complex document structures.
Map to your taxonomy
Categorize source line items to your chart of accounts or spreading template.
Calculate and reason
Generate ratios, scorecards, trends, validations, risk findings and narrative summaries.
Review and export
Use human-in-the-loop controls before publishing spreads, memos or API outputs.
AI-first architecture Intelligence that understands, evaluates and acts
AI is used where it creates measurable value: structuring data, identifying context, detecting risk, explaining findings and routing exceptions, while keeping people and policy in control.
Layer 01 Deep Document Understanding
Reads main statements, notes, schedules and tabular disclosures across public and private financials.
Layer 02 Adaptive Financial Mapping
Maps varied accounting labels into an institution-defined taxonomy and applies validation logic.
- Custom taxonomy
- Historical consistency
- Formula controls
Layer 03 Analyst Decision Support
Generates ratios, scorecards, risk summaries and credit memos with reviewer oversight.
- Financial ratios
- Risk signals
- 1-page memo
- HITL review
Business Impact
Banks, Rating Agencies & Financial Institutions
Apply the same intelligence foundation to the decisions and workflows that matter most to
this segment.
Where It Helps
Priority use cases
- Automate corporate and SME financial spreading
- Support rating, audit, compliance and credit review
- Generate consistent ratios and committee-ready summaries
- Process portfolio statements at scale
Operating Model
What changes for teams
- Fewer manual preparation steps
- Consistent evidence and risk logic
- Exception-led analyst review
- Structured integration into existing systems
Business Impact
NBFCs & Specialized Lenders
Apply the same intelligence foundation to the decisions and workflows that matter most to
this segment.
Where It Helps
Priority use cases
- Accelerate secured, SME and corporate underwriting
- Reduce dependency on manual Excel spreading
- Configure product-specific scorecards and covenants
- Integrate outputs into LOS and appraisal workflows
Operating Model
What changes for teams
- Fewer manual preparation steps
- Consistent evidence and risk logic
- Exception-led analyst review
- Structured integration into existing systems
Business Impact
Corporates & Large Enterprises
Apply the same intelligence foundation to the decisions and workflows that matter most to
this segment.
Where It Helps
Priority use cases
- Assess customers, vendors and acquisition targets
- Benchmark entity and subsidiary financial performance
- Support treasury, investment and counterparty reviews
- Standardize internal financial health assessments
Operating Model
What changes for teams
- Fewer manual preparation steps
- Consistent evidence and risk logic
- Exception-led analyst review
- Structured integration into existing systems
Why Cygnet Finalyze Move beyond disconnected data tools
The differentiator is not AI as a label. It is verified data, specialized document intelligence, explainable risk logic and integration into the decisions your teams already make.
Traditional approach
- Copy-paste from PDFs into spreadsheets
- Fixed templates that fail on new formats
- Main-statement extraction without note context
- Different formulas across analysts
- Manual memo and scorecard preparation
AI-native Cygnet approach
- Agentic navigation of complex financial documents
- Adaptive mapping to your taxonomy
- Deep extraction from notes and schedules
- Automated ratios, scorecards and data-grounded memos
- Human-in-the-loop validation and governed overrides
Governed AI Enterprise control around every AI-assisted output
Support faster decisions without turning models into a black box. Review, override, trace and integrate outputs within your own governance model.
Your Taxonomy
Use proprietary line-item mapping, chart of accounts and spreading standards.
Formula & Validation Control
Configure ratios, thresholds, formulas and consistency checks.
Human-in-the-Loop
Review extracted values, mappings and conclusions before finalization.
Source Referencing
Trace outputs back to the originating page, table or note.
Version Control
Maintain document, review and output versions for auditability.
Secure Enterprise Integration
Connect through REST APIs and webhooks to existing risk systems.
- Loan Origination
- Credit Appraisal
- Rating systems
- Audit platforms
- ERP / financial systems
- Data warehouse
- REST APIs
- Webhooks
Frequently asked questions Questions credit, risk and technology teams ask
It can process audited annual reports, balance sheets, profit and loss statements, cash-flow statements, notes, schedules and private-company management accounts in varied formats.
No. It can map line items, create spreads, calculate ratios, apply validations and scorecards, and generate data-grounded credit summaries or memos.
Yes. Institutions can configure their chart of accounts, spreading taxonomy, ratios, validation rules, scorecards and thresholds.
Agentic AI navigates complex document structures, interprets context and adapts to variations instead of relying only on fixed coordinates or templates.
Yes. Analysts can validate, override and approve extracted values, mappings and outputs before they are finalized.
GLIB.ai provides advanced financial-document intelligence. Cygnet Finalyze connects those outputs with broader credit assessment, verified-data and enterprise integration workflows.