Double-entry accounting based personal finance app

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Hello HN! I am Aswin Mohan, full-stack mobile + web developer and I built PaperMoney( https://getpaper.money ). PaperMoney is a double-entry accounting based personal finance app. It can help you keep track of your expenses, assets, liabilities and your net-worth. It is based on the command-line tools beancount and ledger. I had been using beancount to track my expenses for over two years. The plain-text accounting and reporting with fava was great, but I wanted a mobile based app to keep track on the go. Looked around existing solutions but everything fell short when compared to beancount. Also the major apps were not available outside the United States and only supported the dollar. They were based on assigning categories to a list of transactions which I found lacking coming from double-entry accounting. So I created Paper Money. It's based on double-entry accounting, you can add your chart of accounts and add balanced transactions. We'll use this to calculate your net-worth and the balances in your accounts. It's built using React Native for the frontend and Elixir and Phoenix on the backend. We have support for both Android and iOS. I have plans to add automated account syncing and automated expense tracking in future versions. The target audience currently is someone who is familiar with double-entry accounting but looking for a hosted mobile version. The future versions will be focused on more mainstream customers of personal finance apps, which means making the app more accessible for people without prior experience with double-entry accounting. I am available at aswin@getpaper.money if you have any questions or querires, and excited to hear your feedback! Links: Website: https://getpaper.money IOS: https://apps.apple.com/in/app/papermoney/id6737713983 Android: https://play.google.com/store/apps/details?id=com.papermoney... Video Demo of the App: https://www.loom.com/share/40cf50afe33f4e1cb4fa3e749c19a2e3?...

Visit product View on Hacker NewsNov 27, 2024

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, ios · Missing: supports, reddit linkedin, podcasting

95%95% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: ios, personal, apps · Missing: mobile apps, entrepreneurs, month

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: apple, google, apps · Missing: mac, agents, macos

61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, exist, existing · Missing: https docs, just released, lua

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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