Scaling KYC/KYB with AI in Emerging Markets - Any Practical Wins?
Hey everyone, been following a lot of the talk around leveraging AI/ML for more efficient KYC/KYB processes, especially in fintech. It makes intuitive sense for speeding up onboarding and potentially reducing false positives/negatives.
My question is specifically for those operating or looking to expand into emerging markets – think LatAm or parts of APAC, where the identity infrastructure might be less standardized and regulatory landscapes can shift pretty rapidly. Has anyone here actually implemented AI-driven solutions for KYC/KYB in these regions with tangible success? I'm curious about the real-world hurdles you faced – data quality, model training with diverse datasets, integration with local databases, and perhaps most critically, gaining regulator comfort with automated decision-making. Are you seeing significant reductions in operational costs or improvements in fraud detection? Or are we still largely in the 'proof-of-concept' stage for these trickier jurisdictions?
Definitely agree on the potential, especially in markets with less mature identity systems. My main concern would be the availability and quality of training data for AI models in those regions. How are you approaching data collection and verification for your models?