AI-powered bank statement extraction, validation and financial analysis built for faster, more consistent lending decisions. Digital PDFs, scanned statements and images — transformed into structured financial intelligence.
Reviewing bank statements manually takes time, creates inconsistencies and makes it difficult for credit teams to identify important financial patterns across hundreds of transactions. BankStatementIQ automates the process.
Upload one or multiple bank statements in supported digital or scanned formats.
AI and OCR technologies identify statement information and convert transactions into structured data.
The system validates transaction data, balances, dates and statement consistency before analysis.
Financial behaviour, income patterns, obligations, anomalies and key credit indicators are calculated.
Credit teams receive a structured dashboard and transaction-level output for decision-making.
Files queue and process unattended. Completion notifications go out by email or WhatsApp with the report attached.
Bank statements are rarely standardised — different banks use different layouts, transaction descriptions and document structures. BankStatementIQ recognises banks and statement layouts automatically, including scanned and low-quality documents.
The original document stays on screen next to its extracted output — transaction dates, value dates, descriptions, debits, credits and running balances, preserved exactly as the bank recorded them and exported straight to Excel.
Every extracted figure traces back to the line it came from. Illustrative sample.
| Date | Description | Debit | Credit | Balance |
|---|---|---|---|---|
| 2025-06-10 | POS Purchase — Retail | 1.000 | 19546.983 | |
| 2025-06-09 | Salary Credit | 900.000 | 19547.983 | |
| 2025-06-06 | Inward Transfer | 2500.000 | 18647.983 | |
| 2025-06-04 | ATM Cash Withdrawal | 200.000 | 16147.983 | |
| 2025-06-02 | Utility Payment | 78.600 | 16347.983 | |
| 2025-06-01 | Cheque Clearing | 540.000 | 16426.583 |
Automatically identify recurring salary credits and income patterns.
Understand how money moves through the account.
BankStatementIQ automatically looks for patterns that would otherwise require manual transaction-by-transaction review.
Identify periods where the account balance falls below zero.
Highlight unusually large credits or debits compared with normal account behaviour.
Detect recurring transactions including salaries, rent, instalments and regular commitments.
Surface transactions that may indicate returned payments or bounced cheques.
Identify transactions involving foreign markets or currencies where relevant.
Highlight significant cash deposits or withdrawals based on configurable business rules.
Identify related incoming and outgoing transfers to prevent artificial inflation of account turnover.
Spot repeated narrations that may indicate structured or split transactions.
Catch inconsistencies between transaction dates, running balances and statement totals.
Automation should make analysis faster — not hide the underlying data. Policy checks are stated plainly: when a statement is shorter than your rules require, the system says so — and still reports complete figures for the months it found.
The platform complements your existing credit policies rather than forcing your organisation into a fixed analysis model.
Create reusable analysis and query configurations for different lending products. Define criteria, save templates and apply the appropriate view to statement data.
Process multiple statements through an automated AI pipeline instead of analysing them individually — organised into case folders, monitored in real time, and mergeable into consolidated multi-statement reports.
Bank statements contain highly sensitive financial information. The platform can be deployed within the institution's controlled infrastructure according to security and compliance requirements — down to which tabs each role can open.
Reduce the time spent manually reading and calculating information from lengthy statements.
Apply the same validation and analysis logic across every statement.
Identify patterns that are difficult to recognise through manual review alone.
Automate repetitive extraction and calculation activities.
Analysts spend more time evaluating applicants and less time preparing data.
Maintain transaction-level visibility behind every metric and flag the system produces.
Thirteen slides covering extraction, validation, financial analysis and deployment — the document to forward to a credit committee or an IT reviewer.
Transform unstructured bank statements into structured, validated and actionable financial intelligence.
