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.
Insights into bank statement analysis and lending technology
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Why the 30–60 minutes an underwriter spends per SME case quietly adds up to one of the biggest costs in your lending operation.
How configurable underwriting rules turn parsed bank statements into automated decisions — clean files clear themselves, the grey area lands on a desk.
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Read more →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 →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 →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 →Configurable underwriting rules turn parsed bank statements into automated decisions. Clean files clear themselves; the grey area lands on a desk.
Read more →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 →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 →How financial professionals use automated bank statement analysis for source of funds checks, AML compliance, and transaction verification.
Read more →Fee notices on page one, credits and debits in separate sections, no running balances - the hidden complexity of America's largest bank.
Read more →Two-column summaries, a single ambiguous Amount column, dispute forms embedded in the PDF, and APR tables that aren't transactions.
Read more →A first page with no transactions, daily balances instead of running balances, and totals rows disguised as data.
Read more →Marketing noise, fee tables disguised as data, missing balances, and ordinal date formats - the hidden challenges of Santander statements.
Read more →Clean modern design, multi-currency sections, currency suffixes instead of symbols, and variable-length statement periods.
Read more →Stock photos in the summary, abbreviated labels, transactions fragmented across three sections, and the community bank problem.
Read more →Real feedback from a professional user who found us through ChatGPT and uses the service for account analysis.
Read more →Integrate bank statement analysis into your lending workflow with our REST API. Upload PDFs, get structured transaction data.
Read more →Landscape PDFs, headers on page one only, and why modern banks can be harder to parse than legacy ones.
Read more →Multi-currency statements, reverse chronological order, and multiple accounts merged into a single PDF.
Read more →The challenges of extracting data from HSBC's mainframe-era PDF statements - misaligned text, no running balances, and the mysterious D suffix.
Read more →How working with lenders who process hundreds of bank statements daily led us to build an AI-powered analysis platform.
Read more →The hidden challenges of parsing Barclays statements - missing years, dates that disappear, and phantom balance rows.
Read more →