You're right. As someone who does freelancing, I understand the feeling that one minute you're shopping and the next minute you're considering if homelessness is as bad as they say 🤣🤣
Freelancers and entrepreneur do face irregular income patterns. I was actually basing the project on three customer types at first: freelancers, salaried workers, and small businesses with custom data generation and ML training. But with less than 2 weeks for the prototype, we had to make a decision: the perfect the ML models or focus on the TigerDB database capabilities?
I went for the later and we used the safe "Give Me Some Credit" model and focused our innovation on making TimescaleDB think like a credit analyst.
Yeahhh... The current system punishes non-traditional income even when someone's successful and growing. A freelancer making
variable income will be misrepresented. That's not just unfair - it stifles entrepreneurship.
Your vision is very much feasible. I am working on an architecture that can track real-time income patterns, payment behavior during high/low periods, and customer-specific risk profiles. Dynamic payment schedules that adjust to actual monthly income are the natural next step.
I got the inspiration for the project when I heard about @Moniepoint expansion and wanted their attention. I also wanted to finally dive into MLOps.
Thanks for validating we're solving a real problem. The future of credit should understand that freelancers and entrepreneurs aren't really "risky", they are just different.
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Hiii Anna! @annavi11arrea1
Thank you for your feedback!
You're right. As someone who does freelancing, I understand the feeling that one minute you're shopping and the next minute you're considering if homelessness is as bad as they say 🤣🤣
Freelancers and entrepreneur do face irregular income patterns. I was actually basing the project on three customer types at first: freelancers, salaried workers, and small businesses with custom data generation and ML training. But with less than 2 weeks for the prototype, we had to make a decision: the perfect the ML models or focus on the TigerDB database capabilities?
I went for the later and we used the safe "Give Me Some Credit" model and focused our innovation on making TimescaleDB think like a credit analyst.
Yeahhh... The current system punishes non-traditional income even when someone's successful and growing. A freelancer making
variable income will be misrepresented. That's not just unfair - it stifles entrepreneurship.
Your vision is very much feasible. I am working on an architecture that can track real-time income patterns, payment behavior during high/low periods, and customer-specific risk profiles. Dynamic payment schedules that adjust to actual monthly income are the natural next step.
I got the inspiration for the project when I heard about @Moniepoint expansion and wanted their attention. I also wanted to finally dive into MLOps.
Thanks for validating we're solving a real problem. The future of credit should understand that freelancers and entrepreneurs aren't really "risky", they are just different.