Analyzer guide

Bank statement analysis, automated

Upload any bank statement PDF and get a structured analysis — categorised transactions, cash-flow signals, salary detection, and a lending-ready report — in under a minute.

Cash-flow signals

Average and end-of-month balance, inflow / outflow trend, negative-balance days, obligation-to-income ratio.

Income detection

Salary auto-detected with employer and cadence. Freelance and rental income separated from other credits.

Risk flags

Bounced cheques, EMI misses, high-value cash deposits, and running-balance mismatches surfaced automatically.

How the analysis works

  1. 1. Upload

    PDF, CSV or image of the bank statement — 1 to 12 months per file, up to 50 MB.

  2. 2. Extract

    Bank-specific parser plus OCR fallback pulls every transaction with date, amount, description, running balance.

  3. 3. Categorise

    Rule-based plus LLM-assisted categorisation, tuned per country (GST for India, VAT for UK/UAE/ZA, Schedule-C for US).

  4. 4. Score

    Cash-flow signals computed: salary, EMIs, bounce rate, volatility, average balance, negative-day count.

  5. 5. Report

    Downloadable JSON, PDF report, or Excel workbook with per-month sheets. API returns the same shape.

Who uses bank statement analysis

Lenders & NBFCs

Underwrite personal, SME and MSME loans in minutes with an API that returns a scorecard, not just data.

CAs & bookkeepers

Skip manual data entry — get categorised transactions and cash-flow snapshots ready for the ledger.

Finance teams

Monthly close, expense audit, and vendor-payment reconciliation from a single statement upload.

Why Convert Bank Statements over spreadsheets or manual review

  • 200+ bank templates — India, US, UK, UAE, ZA, AU and more.
  • Running-balance reconciliation flags parser drift before you trust the numbers.
  • Salary and EMI detection out of the box — no custom rules to write.
  • One JSON shape across every bank so integrations stay simple.
  • Country-tuned categories: GST, VAT, Schedule-C, FBR, FIRS.
  • Free tier processes in the browser — nothing uploaded for anonymous users.

How to analyse a bank statement

From raw PDFs to a lending-ready signal report in three steps.

  1. Step 1

    Upload 3–12 months of statements

    Add every account for the applicant or entity. Multiple PDFs are merged into one timeline and duplicates are removed.

  2. Step 2

    Automatic categorisation

    Transactions are classified into salary, EMI, rent, subscriptions, cash deposits, transfers and taxes, with recurring patterns and counter-parties identified.

  3. Step 3

    Read the signal report

    Average and end-of-month balance, inflow trend, obligation-to-income ratio, bounce count and negative-balance days — exportable as JSON, Excel or a PDF report.

FAQs

What is bank statement analysis?

Bank statement analysis is the process of extracting transactions from a bank statement (PDF, CSV or image), categorising them, and computing behavioural signals — average balance, salary regularity, EMI load, bounced-cheque count, cash-flow volatility — that lenders, CAs, and finance teams use to make decisions.

How does bank statement analysis improve lending decisions?

Lenders score applicants on cash-flow signals derived from 3–12 months of statements: net inflow trend, salary consistency, obligation-to-income ratio, bounce rate, negative-balance days, and volatility. Automated analysis turns a 2-hour manual review into a 30-second report and removes human bias.

What signals does Convert Bank Statements compute?

Average and end-of-month balance, salary detection with employer, recurring debits (EMIs, rent, subscriptions), inward and outward cheque returns, high-value transactions, cash deposits vs digital, GST outflows (India), UPI vs card mix, and negative-balance day count.

Is it accurate for scanned PDFs?

Yes. OCR handles image PDFs; running-balance reconciliation catches any parser drift and flags it before the report is generated.

Can I export the analysis?

Yes — download the full analysis as JSON, PDF report, or a structured Excel workbook with per-month sheets. API also available for lenders integrating into their loan-origination stack.

What questions does statement analysis answer?

Whether income is regular and from whom, how much of it is already committed to debt, whether the account runs negative, how volatile cash flow is month to month, and whether there are returned cheques or unusual cash activity.

How many months of statements are needed?

Three months shows current behaviour; six to twelve months is needed to see seasonality, salary changes and bounce history. Lenders typically require six.

Can it detect a tampered statement?

Yes — the running-balance reconciliation, font and layout consistency checks, and PDF metadata inspection flag edited pages for manual review.

Does it work across multiple banks?

Yes. Statements from different banks and currencies are normalised into one timeline before the signals are computed.

What is a bank statement?

A bank statement is a periodic document issued by your bank listing every transaction on an account for a period — usually one month. It shows the opening balance, each debit and credit with a date and description, and the closing balance. Banks issue it as a PDF, a printed copy, or a downloadable CSV/OFX file.

How do I get a bank statement?

Sign in to your bank's internet banking or mobile app, open the account, choose Statements (sometimes 'e-statements' or 'Documents'), pick a date range, and download the PDF. Most banks keep 12–24 months online; older periods are requested from a branch or support. You can upload the downloaded PDF here directly — no need for the CSV version.

How long should I keep bank statements?

As a rule of thumb keep them seven years if they support a tax return, three years for general business records, and at least one year for personal budgeting. Digital copies count in most jurisdictions, so converting statements to Excel or CSV is a valid way to archive them in a searchable form.

Related

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