Zeneth UW Suite reads business bank statements the way a senior underwriter would, only faster and without the coffee break. Drag up to 12 months of PDFs in, get a full structured breakdown out: revenue, NSFs, negative days, recurring obligations, stacking patterns, and a deal verdict. Built for MCA brokers, ISO shops, and lending teams who need speed without sacrificing rigor.
Ask any broker or underwriter where the time goes on a deal and you will hear the same answer. The paperwork is easy. The application is easy. The lender research is easy. Reviewing three to twelve months of bank statements line by line, cross-referencing recurring payments, tallying NSFs, spotting stacking, estimating average daily balance, this is where the hours disappear. It is also where most of the errors happen, because by the time an underwriter is on month eight of a statement review, attention fades and numbers get missed.
AI bank statement analysis software eliminates this bottleneck. Instead of an underwriter squinting at a PDF, a trained model reads every transaction in parallel, classifies it, and surfaces the data points that matter. A deal that used to take 45 minutes of manual review now takes less than a minute, with better accuracy than a tired human can deliver.
Zeneth UW Suite is built around this idea. Upload, analyze, decide. That is the entire flow.
Every analysis produces a complete structured breakdown. Here are the data points you get for every bank statement upload.
Older bank statement parsers use regex patterns and templates mapped to specific bank layouts. They work fine when the merchant banks at Chase and uses a standard statement format. They break the moment you hit a non-standard layout, a restructured PDF, or a scanned image. Any MCA broker has seen this in the field: the parser returns garbage or skips entire months.
Zeneth UW Suite uses Claude AI to read statements the way a human would, interpreting the document rather than pattern-matching it. This has practical consequences.
| Capability | Zeneth AI Parser | Regex / Template Parsers |
|---|---|---|
| Standard bank layouts | 99%+ accuracy | 90 to 99% |
| Non-standard or custom layouts | 95%+ accuracy | Often fails entirely |
| Restructured or edited PDFs | Handles gracefully | Typically breaks |
| Scanned / image-based statements | Reads via OCR + AI | OCR-only, poor classification |
| Transaction classification | Contextual understanding | Keyword matching |
| Stacking pattern detection | Catches novel patterns | Only known patterns |
| Revenue exclusion (MCA deposits, transfers) | Accurate | Often wrong |
The accuracy difference compounds across a month of deals. If a regex parser breaks on 1 in 10 statements and you run 30 deals a month, that is 3 deals a month you cannot process, which translates to real commission lost.
Run your first deal free. 5 credits on signup, no card required.
Try It Free →The most common flow. You get statements from your merchant, drag them into Zeneth, and analysis runs. Supports PDFs from every major US bank including Chase, Bank of America, Wells Fargo, Capital One, US Bank, PNC, TD Bank, Citizens, M&T, Regions, Truist, Fifth Third, Huntington, and hundreds of smaller regional banks and credit unions. Upload 3 months, 6 months, 12 months, whatever you have.
Skip the PDF flow entirely. You connect your own Plaid account in broker settings (bring your own credentials, no markup from us), then generate a unique link and send it to your merchant. Merchant clicks, authenticates with their bank in under a minute, and 12 months of real transactions flow into your analysis. This is faster than waiting for PDFs and more accurate since it pulls live data, not potentially edited documents.
For complete pre-qualification, add a soft pull credit check alongside the bank statement analysis. Returns the FICO band, open tradelines, and public records flags without affecting the merchant's credit score. Use it to filter leads before investing broker time.
Many bank statement tools stop at data extraction. You get CSV output and have to do the underwriting yourself. Zeneth goes the full distance: parsing, classification, risk assessment, factor rate guidance, and lender matching are all one flow.
This means the broker goes from raw PDF to submission-ready decision in one flow. No exporting to Excel, no manual calculations, no hunting through spreadsheets for comparable deals.
This is a non-negotiable policy, not a marketing claim. Every bank statement you upload is processed in real-time memory and discarded the moment the structured analysis is produced. The PDF is never written to disk, never logged, never backed up, never retained in any form. Only the extracted analysis results (revenue numbers, verdict, score) persist in your deal history.
Why this matters: your merchants are trusting you with sensitive financial data. Every storage touchpoint is a compliance risk. Traditional bank statement tools keep the PDFs around forever, creating a liability chain. Zeneth removes that chain by refusing to be a custodian of the underlying documents.
Technical specifics: data in transit uses TLS 1.3. The analysis pipeline runs in isolated serverless functions that have no persistent storage attached. Your analysis history is stored in Supabase with row-level security, visible only to your account. Full details at zeneth-uw.com/privacy.html.
Bank statement analysis software is a tool that reads business bank statement PDFs and automatically extracts the data points lenders and brokers need for underwriting: monthly revenue, deposit count, ending and minimum balances, NSF charges, negative balance days, recurring obligations, and patterns that suggest stacking with other lenders. What used to take an underwriter 30 to 60 minutes per deal now takes 60 seconds.
Modern AI bank statement parsers achieve 99%+ accuracy on text-based PDF statements from major US banks including Chase, Bank of America, Wells Fargo, Capital One, US Bank, and PNC. Accuracy drops on heavily scanned or low-quality images of statements, where OCR is required. Zeneth UW Suite uses Claude AI for parsing, which consistently beats regex-based parsers on accuracy and handles non-standard statement layouts gracefully.
Yes. The AI identifies recurring daily or weekly withdrawals that match the payment pattern of merchant cash advances, business term loans, revenue-based financing, and factoring. It also catches the scenario where an advance deposit has recently landed but the corresponding daily remit has not yet begun, which is a common signal of fresh stacking that manual review misses.
PDF bank statements from every major US bank. The parser handles both text-based PDFs (direct bank exports) and image-based scanned PDFs. You can upload up to 12 months in a single analysis. Zeneth UW Suite also supports Plaid bank connection for real-time transaction data that skips the PDF upload entirely.
No. Zeneth UW Suite processes every statement in real-time memory and never saves the file to a database or disk. Once the structured results are produced, all source document data is discarded. Only the analysis output (revenue numbers, verdict, score) is retained in your history. This zero data retention policy protects both you and your clients.
Yes. The PDF report export can be configured to carry your agency's branding (logo, colors, company name). Merchants receive a polished professional report that looks like it came from your shop, not from Zeneth.
Currently the platform is optimized for US business bank statements. Canadian bank statement support is in development. For international business banking, contact us through the enterprise inquiry form on the homepage for specific currency and language requirements.
5 free credits. No demo. No card. Drag a statement in, get a deal answer out.
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