Q: How We Test and Score Bank Statement Converters

We test ChatGPT - GPT-5 the same way a finance team would: by running real bank statements through the converter and comparing the output CSV against a manually verified "golden" reference. Our benchmark score combines two critical factors: 1) Extraction Accuracy (75.2%) - Did the converter correctly extract every transaction? We compare the output CSV field by field—dates, amounts, descriptions, and balances. Critical fields like transaction amounts are weighted more heavily than optional fields like reference numbers. 2) Statement Integrity (40.0%) - Does the converted data pass accounting sanity checks? We verify row counts, debit/credit totals, chronological order, and date validity. If these checks fail, the CSV isn't safe to import into QuickBooks, Xero, or your accounting system—even if individual fields look correct. Final Score: 75.2% × 40.0% = 30.1%. Both factors must score well for the overall accuracy to stay high. This prevents converters from scoring well on extraction but producing unusable data, or vice versa. Based on the overall score, we assign a usability rating: Use it (98%+) means safe for accounting workflows; Use caution (90-98%) means needs manual review before import; Do not use (<90%) means too many errors for actual use.

Q: Benchmark Scope & Limitations

Our benchmark currently tests converters using a 5-page DBS Bank (Singapore) statement in English. We apply the same testing methodology to every tool, measuring both Extraction Accuracy and Statement Integrity consistently to ensure fair, apples-to-apples comparisons. We're testing DBS Bank (Singapore) statements, English language, standard PDF format with tabular transaction data, and multi-page statements with running balances. We're expanding our benchmark to cover more banks, languages, and statement formats. Bank statement templates vary significantly—different layouts, date formats, currency conventions, and multi-currency statements all affect converter accuracy. Results from one bank may not generalize to others. Important: These benchmarks test ChatGPT - GPT-5 on a specific statement format. Your results may vary depending on your bank's template, statement language, and format complexity. We recommend testing any converter with a sample of your own statements before using it in production.

Question 1

How Accurate Are Bank Statement Converters?

Accepted Answer

When you convert a bank statement PDF to CSV, accuracy is critical. Missing transactions, incorrect amounts, or flipped debits and credits can break downstream workflows, trigger reconciliation errors, and waste hours on manual fixes. This benchmark evaluates ChatGPT - GPT-5 against a manually verified statement to measure real-world accuracy. For production use: 99%+ accuracy is safe for accounting workflows with minimal manual review needed; 95-98% accuracy is usable with careful review, check critical fields manually; <95% accuracy is high risk with missing transactions or balance errors likely. Both Extraction Accuracy (capturing fields correctly) and Statement Integrity (balancing checks, row counts, date validity) must score well for a converter to be production-ready. Even if individual fields look correct, a tool that fails integrity checks can break your accounting workflow.

Question 2

How We Test and Score Bank Statement Converters

Accepted Answer

We test ChatGPT - GPT-5 the same way a finance team would: by running real bank statements through the converter and comparing the output CSV against a manually verified "golden" reference. Our benchmark score combines two critical factors: 1) Extraction Accuracy (75.2%) - Did the converter correctly extract every transaction? We compare the output CSV field by field—dates, amounts, descriptions, and balances. Critical fields like transaction amounts are weighted more heavily than optional fields like reference numbers. 2) Statement Integrity (40.0%) - Does the converted data pass accounting sanity checks? We verify row counts, debit/credit totals, chronological order, and date validity. If these checks fail, the CSV isn't safe to import into QuickBooks, Xero, or your accounting system—even if individual fields look correct. Final Score: 75.2% × 40.0% = 30.1%. Both factors must score well for the overall accuracy to stay high. This prevents converters from scoring well on extraction but producing unusable data, or vice versa. Based on the overall score, we assign a usability rating: Use it (98%+) means safe for accounting workflows; Use caution (90-98%) means needs manual review before import; Do not use (<90%) means too many errors for actual use.

Question 3

Benchmark Scope & Limitations

Accepted Answer

Our benchmark currently tests converters using a 5-page DBS Bank (Singapore) statement in English. We apply the same testing methodology to every tool, measuring both Extraction Accuracy and Statement Integrity consistently to ensure fair, apples-to-apples comparisons. We're testing DBS Bank (Singapore) statements, English language, standard PDF format with tabular transaction data, and multi-page statements with running balances. We're expanding our benchmark to cover more banks, languages, and statement formats. Bank statement templates vary significantly—different layouts, date formats, currency conventions, and multi-currency statements all affect converter accuracy. Results from one bank may not generalize to others. Important: These benchmarks test ChatGPT - GPT-5 on a specific statement format. Your results may vary depending on your bank's template, statement language, and format complexity. We recommend testing any converter with a sample of your own statements before using it in production.

ChatGPT - GPT-5Bank Statement Converter Accuracy Test

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How We Test and Score Bank Statement Converters

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