Wo

World’s first £3 flat fee (0% FX markup) money transfer service

Hacker News

World’s first £3 flat fee (0% FX markup) money transfer service

Good morning everyone! My co-founder and I recently moved to the UK after working at Robinhood for over 5 years. We were stunned at the fees it was costing us to move money across borders with existing fintech solutions, so we decided to start Atlantic Money - the world’s first fixed fee (with no FX markup) money transfer product. For £3 you can transfer up to £1M. Let us know if you have any questions!

Visit product View on Hacker NewsMar 9, 2022

Actual performance

182points

212comments

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Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

30%30% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

18%18% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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