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How to Use AI in Bank Statement Processing

Nanonets

Set up rule-based workflows to identify and remove any duplicate entries and human review for complex or ambiguous transactions. Regularly analyze reasons for variances (for eg: format differences, fraud, duplicate records) Discrepancy identification During reconciliation, any mismatches are flagged for further review.

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Best Accounts Payable Software of 2023

Nanonets

AI-enabled accounts payable software like Nanonets can extract accounts payable data from various sources and convert them into structured digital information that can be further processed or fed into ERPs or databases. and databases (MySQL, PostGres, MSSQL, etc.) There is no standard structure or function to accounts payable software.

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What is two-way matching and how does it work?

Nanonets

Managing multiple invoice formats: Large organizations handle purchase orders and invoices from various sources in diverse formats such as word documents, spreadsheets, XML documents for EDI, PDFs, images, and paper documents. Invoices and POs can also be imported into Nanonets from your mail, apps and databases.

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How to automate data extraction in healthcare: A quick guide

Nanonets

You can also set up database matching to verify extracted information against existing patient records, billing systems, or insurance databases. The validation workflow enables you to detect and flag duplicate documents to prevent issues like double billing. Nanonets integrates with over 5,000 applications through Zapier.