Algorithmic underwriting for consumer credit using non-traditional data was one of the most ambitious bets in European fintech a decade ago. Kreditech was founded in Hamburg in 2012 with the thesis that machine learning models trained on thousands of data points — far beyond traditional credit scoring inputs — could underwrite consumers in markets where conventional credit bureau coverage was thin. The company expanded across emerging markets, particularly in Latin America, Eastern Europe, and Asia, lending to consumers who were credit-invisible to traditional underwriters. The technology was genuinely advanced for its time, the addressable market was enormous, and the funding it attracted reflected the ambition — over $300 million across multiple rounds, including investments from PayU and other major institutional backers. The execution proved harder than the technology. Operating in multiple emerging markets simultaneously, navigating diverse regulatory regimes, and managing the credit performance of underbanked borrower populations created complexity that challenged the company's ability to scale profitably. Kreditech rebranded to Monedo and entered insolvency proceedings in 2020. Its story is one of the more instructive in European fintech — a technology-led approach to a real market opportunity that ultimately demonstrated the gap between algorithmic possibility and operational sustainability in consumer lending across emerging markets.