Fraud Detection on Every Bank Statement
AI-generated statements are a tidal wave. ExactSum now runs document forensics on every statement — file forensics, penny-perfect reconciliation and visual inspection — returning a plain-English verdict.
ExactSum Blog
Insights into bank statement analysis and lending technology
Top 3 Blogs to Read
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The Hidden Cost of 30 Minutes Per Case
Why the 30–60 minutes an underwriter spends per SME case quietly adds up to one of the biggest costs in your lending operation.
Auto-Approve, Refer, or Decline: The Decision Engine
How configurable underwriting rules turn parsed bank statements into automated decisions — clean files clear themselves, the grey area lands on a desk.
Fraud Detection on Every Bank Statement
Falsified statements aren't easy to spot any more. ExactSum now runs document forensics on every statement it processes — who produced the PDF, whether the numbers reconcile to the penny, and whether the figures were visually tampered with — returning Normal, Warning or High Risk with the findings spelled out.
Read more →The Bottleneck in Lending Isn't Underwriting Anymore. It's What You Do with the Freed Capacity.
AI has removed the underwriting bottleneck — first-pass statement work is done in minutes. The winners of the next cycle won't be the lenders with the fewest underwriters; they'll be the ones who worked out what to do with the freed capacity.
Read more →A Free Company Structure Checker: Owners, Directors & Filed Accounts in One View
Enter any UK company number and see its profile, directors, ownership (PSCs and corporate parents you can walk up), filed accounts and insolvency history — free, no sign-up.
Read more →Why Credit Analysts Need Rules, Not Robots
Credit underwriting is a judgement call. A rules-based decision engine doesn't replace the analyst — it gives them structured evidence so they can make better decisions, faster.
Read more →What Week One Looks Like When an Asset Finance Lender Switches On Automated Bank Statement Review
A UK asset finance lender went live with ExactSum. Here's what the first seven days actually looked like — not the pitch-deck version, the real one.
Read more →Agentic AI or Deterministic Engine? Why Underwriting Extraction Should Be Boring
For the specific job of turning a bank statement into structured underwriting data, an agent is the wrong shape of tool. Here's why deterministic wins.
Read more →Auto-Approve, Refer, or Decline: Introducing the ExactSum Decision Engine
Configurable underwriting rules turn parsed bank statements into automated decisions. Clean files clear themselves; the grey area lands on a desk.
Read more →The Hidden Cost of 30 Minutes Per Case
An underwriter spends 30 to 60 minutes reviewing statements on each SME case. Multiply that across hundreds of monthly applications and the hidden cost is larger than anyone realises.
Read more →382 Pages, 3,730 Transactions: Our Biggest Statement Yet
A lender uploaded a 382-page bank statement. Here's how ExactSum processed 3,730 transactions from a single PDF without breaking a sweat.
Read more →Bank Statement Analysis for Source of Funds Verification
How financial professionals use automated bank statement analysis for source of funds checks, AML compliance, and transaction verification.
Read more →Parsing Chase Bank Statements
Fee notices on page one, credits and debits in separate sections, no running balances - the hidden complexity of America's largest bank.
Read more →Parsing Bank of America Statements
Two-column summaries, a single ambiguous Amount column, dispute forms embedded in the PDF, and APR tables that aren't transactions.
Read more →Parsing Wells Fargo Bank Statements
A first page with no transactions, daily balances instead of running balances, and totals rows disguised as data.
Read more →Parsing Santander Bank Statements
Marketing noise, fee tables disguised as data, missing balances, and ordinal date formats - the hidden challenges of Santander statements.
Read more →Parsing Airwallex Statements
Clean modern design, multi-currency sections, currency suffixes instead of symbols, and variable-length statement periods.
Read more →Parsing First Capital Bank of Texas Statements
Stock photos in the summary, abbreviated labels, transactions fragmented across three sections, and the community bank problem.
Read more →User Feedback: "Very Easy to Use, Did Exactly What I Wanted"
Real feedback from a professional user who found us through ChatGPT and uses the service for account analysis.
Read more →API Access: Automate Your Bank Statement Analysis
Integrate bank statement analysis into your lending workflow with our REST API. Upload PDFs, get structured transaction data.
Read more →Parsing Starling Bank Statements
Landscape PDFs, headers on page one only, and why modern banks can be harder to parse than legacy ones.
Read more →Parsing Revolut Bank Statements
Multi-currency statements, reverse chronological order, and multiple accounts merged into a single PDF.
Read more →Parsing HSBC Bank Statements
The challenges of extracting data from HSBC's mainframe-era PDF statements - misaligned text, no running balances, and the mysterious D suffix.
Read more →Why We Built ExactSum
How working with lenders who process hundreds of bank statements daily led us to build an AI-powered analysis platform.
Read more →Parsing Barclays Bank Statements
The hidden challenges of parsing Barclays statements - missing years, dates that disappear, and phantom balance rows.
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