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MyLoans.ai – Found $20B Error in Education Dept. Student Loan Simulator

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MyLoans.ai – Found $20B Error in Education Dept. Student Loan Simulator

We've launched MyLoans.ai to tackle a huge problem: making it simpler to understand and choose your optimal student loan repayment plan. The Department of Education's loan simulator is flawed in a way that negatively impacts graduate students to the tune of $20 billion, leading to borrowers potentially overpaying sometimes up to over $100K on their student loans. Our analysis shows that inaccuracies in the income-based SAVE plan calculations could cost graduate borrowers significantly over 25 years. MyLoans.ai offers a calculator with the flaw removed, in order to help borrowers navigate their repayment options more effectively. The aim is to correct these costly errors and ultimately bring clarity to student loan management. Discover how we're addressing this issue and join the conversation on improving financial tools for millions. Feedback and insights are welcome as this is our first startup!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
75%75% 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: way, education · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
31%31% 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 · Missing: plus, platform, intuitive
28%28% 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
18%18% 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
15%15% 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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