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Heron Data: AutoSpread

Standardise any chart of accounts in minutes

Say 'goodbye' to 'stare and compare' manual spreading of management accounts, tax returns, balance sheets, or P&Ls. Upload them to Heron via our portal, email, API and receive normalised, clean, and structured output piped directly to where you need it.

Top comment

👋 Hi Hunters, Jamie here from Heron Data. We partner with 100+ Banks, Fintechs, and other Business Lenders to automate mindless repetitive processes like parsing bank statements & application forms into your CRM. Financial statements are essential to most banks underwriting process but a massive pain to parse or 'spread'. Tax returns, balance sheets, and P&Ls provide unique insight into a company's financial health - they are the source for calculating datapoints like inventory turnover, quick ratio, and debt:assets, components of most credit models. Our customers can often reach a speedy lending decision once they have the datapoints they need from financials. However, unless they can hook into a customer's accounting platform directly with a tool like Codat or Rutter the only way to calculate (or 'spread') these ratios reliably from financials in PDF or Excel is by hand. Spreading financials for each company takes them 20-90 minutes... and it's really boring. Until now that is - say hello to AutoSpread! 🤖 Use ML, not human endurance to spread financials. Send what you have to Heron in the format you have it and get it back ready for your credit models or human judgement to analyse 🔌 Heron can ingest docs via email, API, or portal. We'll classify docs, parse or spread them, and push the results into wherever you want them e.g. CRMs like SalesForce, your own propriety software, or an email inbox as an Excel attachment 🗣️ Our software works with financials in most languages - never google translate Dutch line items again 💯 Output quality is our problem, not yours. We stand by our results and will review the docs we can't validate to be correct so you can spend your time on better things OK, but why does all this matter? A high degree of manual intervention makes underwriting a small commercial loan expensive and reduces access to credit, especially for smaller (<$250,000) loans according to research from FinRegLab. This means less access to affordable credit for small businesses, less growth, and more SMBs going under. What's more, humans are amazing at complex processes that require thought and judgement - like making an underwriting decision after reviewing all the data. We are terrible at copy and pasting numbers from a PDF into an Excel all day. Focus on the former, let us automate the latter and make financial services better for businesses :).