Why your synthetic fintech data fails code review (and how mixture models fix it)

Every fintech developer has done this: you need test data, you reach for Faker, you generate ten thousand transactions, and your demo works. Then a data scientist on the buying side opens your dataset, runs one df.describe(), and the deal-killing question arrives: "Why are your transaction amounts uniformly distributed?" Real financial data has a shape. Synthetic data that ignores that shape is instantly recognizable — and in testing, ML training, or sales demos, instantly discrediting. I spent...