Accounts Reconciliation
Financial Spreading
Digital Archive
SchematicIQ
Loan Ops
KYC
Docutwin
Extract, interpret, and validate bank and credit card statements with high accuracy in seconds, regardless of file type or layout. AI automatically structures raw financial data and outputs it in CSV or Excel formats, or integrates it directly with your accounting system to support downstream workflows.
Book a Demo
Most organizations still depend on traditional bank statement processing systems that rely on basic OCR technology, which extracts characters without understanding context, structure, or layout. This leads to frequent errors, incomplete interpretations, and inefficiencies across financial workflows.
Financial teams process hundreds or even thousands of statements each day in formats such as EDI, XML, PDF, images, and paper, which breaks automation.
Nested tables, line breaks, hidden characters, multi-page statements, and bottom notes result in unreliable data extraction.
Template-based processing forces manual rework, introduces bias, and leads to inconsistent data standardization.
Teams often cannot identify duplicates, anomalies, or suspicious transactions, which makes meeting regulatory requirements for anti-fraud and AML checks impractical at scale.
Collatio Bank Statement Processing is Scry AI’s automation platform that converts bank and credit card statements into structured, analysis-ready financial data. It ingests scanned, native, image-based, or handwritten statements, classifies them, extracts transaction-level and account details, and standardizes balances across reporting periods. The system applies multi-engine AI validation to reconcile financial data, confirm accuracy and authenticity, and flag potential fraud. The processed outputs integrate securely with LOS, underwriting, risk, analytics, and ERP systems to support downstream decision-making.
Collatio Bank Statement Processing brings together advanced document intelligence, reconciliation logic, and financial analytics in a single workflow.
The platform automatically ingests files from email, cloud storage, SFTP, and bulk uploads. It then identifies and classifies bank statements across formats, layouts, and institutions without requiring manual sorting. The engine handles native PDFs, scanned PDFs, images, multi-page files, and layout variations, and thereafter routes each file to the correct processing pipeline with high confidence.
The system accurately extracts critical fields, including account details, opening and closing balances, transaction tables, running totals, and multi-page structures. Beyond raw extraction, semantic interpretation models understand the meaning behind values and descriptions. They interpret financial terms, map ambiguous transaction text to standardized labels, and resolve context-dependent patterns.
The engine cleans and standardizes transaction descriptions, resolves duplicates, harmonizes merchant names, and normalizes categories. Each record is enriched with metadata that includes transaction type, category, subcategory, timestamp alignment, geolocation indicators where available, counterparty insights, and behavior tags. This enrichment makes the output consistent and reliable for downstream scoring, reconciliation, and financial analysis.
The platform verifies opening and closing balances across periods, cross-checks transaction continuity, detects carryover discrepancies, and flags missing or duplicated entries. It also evaluates inflows and outflows against supporting financial evidence from documents such as payslips, GST reports, proofs of income, and expense declarations. This multi-layered reconciliation ensures financial integrity and eliminates manual continuity checks across multi-month or multi-account statements.
A unified intelligence layer evaluates financial behavior and risk signals in tandem. It categorizes inflows, expenses, recurring obligations, liabilities, and payment patterns to form a behavioral profile of income stability, spending themes, and liquidity discipline. In parallel, anomaly detection is enabled by reconciliation outputs that surface mismatched balances, discontinuous transactions, irregular carryovers, and values that do not align logically. Together, these frameworks provide a detailed, context-aware view of financial risk and support robust fraud detection.
The platform provides ready-to-use insights such as average balances, income consistency, overdraft frequency, spending clusters, and high-risk behavioral indicators through real-time reports and interactive dashboards. Risk indicators and deviation flags are presented visually, enabling underwriting, credit, and portfolio teams to evaluate financial profiles quickly and with consistent decision support.
The solution delivers clean, structured data to LOS/LMS platforms, underwriting systems, analytics dashboards, data lakes, or spreadsheets through APIs and bulk exports. This enables straight-through or near-straight-through processing (STP) decisioning. In addition, the system incorporates audit trails and detailed logs for each extracted value, including confidence scores, source document coordinates, validation outcomes, and user overrides. It supports audits, model governance, and regulatory reviews.
Deploying Collatio Bank Statement Processing delivers measurable operational and financial benefits for banks and other financial institutions, improving accuracy, efficiency, and processing speed at scale.
data-capture precision across critical bank-statement fields
validation accuracy with configurable Human-in-the-Loop (HITL) workflows
Document Types Supported with Multi-Language Capability to serve global portfolios
reduction in manual statement handling and interventions
Statements are imported from email inboxes, cloud storage platforms, Amazon S3, Google Drive, SFTP, and internal systems. All files are batched, tagged, and prepared for processing. Multi-format support includes native and scanned PDFs, images, and consolidated multi-account statements.
Using advanced OCR and document AI models, the system detects bank statements and classifies or indexes them by customer, account number, issuing bank, and statement period. It identifies layout, orientation, and page structure to ensure accurate extraction.
Advanced OCR combined with ML-based table detection extracts account details, balances, running totals, and transaction tables, even when they span multiple pages or appear in irregular layouts. NLP-driven semantic interpretation standardizes transaction descriptions, resolves merchant names, and enriches financial context for downstream analysis.
Opening and closing balances are matched across months. Transaction sequences are validated for continuity, missing entries, and duplicates. Inflow and outflow patterns are analyzed, and anomalies such as circular transfers, irregular deposits, or unusual spending are flagged when they appear across accounts.
Structured data is delivered to LOS, LMS, underwriting, and analytics systems via APIs or bulk exports. Reports summarize income trends, liquidity, and risk indicators. Every field includes confidence scores, source mapping, and audit logs to ensure end-to-end traceability.
Collatio can process a wide range of bank statement formats, whether they are structured, semi-structured, or unstructured. It also handles handwritten and low-quality documents such as physical copies, fax images, digital scans, image files, HTML exports, and other non-standard layouts.
Collatio is built on an enterprise-grade security and compliance foundation designed to support highly regulated financial environments and evolving global governance requirements.
Aligned with ISO 27001 and SOC 2, Collatio enforces consistent security controls across its infrastructure and operations to protect data confidentiality, integrity, and availability.
Built-in monitoring and anomaly detection support compliance with GDPR and other global data protection regulations.
End-to-end encryption, role-based access controls, and detailed audit trails provide secure access and traceability, with governance enforced throughout all workflows.
We are trusted by enterprises globally.
Connect with your existing enterprise platforms through APIs and direct data exchange, keeping your workflows intact and your teams in sync.
Unlike basic PDF converters that only convert PDFs to CSV or Excel, Collatio delivers deep data understanding, multi-bank reconciliation, confidence scoring, and straight-through processing.
Discover how SCRY AI solutions bring accuracy and innovation in document processing, conversational AI, and IoT operations.
Enterprise Knowledge
Agent
Realtime Intelligence
Customer Support 360
Analytica
CreditIQ
City Intelligence
Smart Utilities
Connected Worker & Assets
Drone Based Infra Monitoring
SceneTrack
