10,000+ institutions
Designed for statement processing across thousands of financial institutions nationwide.
Lender filtration with SubScrub
Scrub statements, filter funders, and submit cleaner files.
SubScrub scans merchant business bank statements, extracts key points, and helps place each file with the appropriate lender or funder. It also alerts your team to potential fraud signals in less than five seconds.
Scrubbing banks made easy
Built around the real MCA submission process
Statements can be uploaded by the merchant or broker. Once loaded, brokers click SubScrub, review extracted data, and filter the file to approved API lenders or submit the traditional way by email to underwriting.
Key statement intelligence
- Average daily balances
- Number of positions
- Negative days
- Average gross deposits
- Accounts in recovery
- Questionable transaction flags
OCR / IDR extraction
Convert PDF statements and extract data with speed and accuracy.
Automated organization
Streamline payee names and categorize transactions quickly.
Automated learning
Flag questionable transactions and metadata that may have been manipulated.
Automated bank statement analysis
Turn raw bank statements into lender-ready underwriting signals
SubScrub helps brokers move beyond manual statement review by extracting the numbers funders ask for, organizing transaction behavior, and surfacing issues before the file is submitted.
Deposit intelligence
Read average gross deposits, revenue patterns, monthly activity, deposit frequency, and cash-flow consistency.
Balance and risk signals
Surface average daily balances, negative days, low-balance patterns, NSF-style behavior, and accounts in recovery.
Position review
Identify number of positions and repayment behavior so brokers understand stacking and exposure before selecting funders.
Transaction organization
Normalize payee names, categorize transaction activity, and reduce the manual review time for brokers and openers.
Fraud and metadata alerts
Flag questionable transactions, manipulated-looking metadata, and suspicious statement patterns before underwriting receives the file.
Submission-ready summary
Give brokers a clear snapshot of merchant strength, weaknesses, missing items, and lender-fit opportunities.
Relationship-based lender matching
Match the merchant to the funders your brokerage actually works with
Submission CRM does not force a generic lender list. Your team loads the lenders and funders you have relationships with, including ISO or funder rep details, guideline minimums, average values, maximum values, and submission preferences.
After SubScrub analyzes the statements, lender filtration compares the merchant profile against those requirements so brokers can prioritize better-fit funders and avoid wasting submissions.