Limited & narrow data pose challenges in accurate financial analysis. To build an effective model, you need diverse data from multiple sources, geographies, and use cases. Open banking, card transactions, bank statements—embrace comprehensive information! 💪💡

Quality matters too! Data labeling, QA, merchant databases, and search engine results are vital. Benchmarking ensures accuracy. Measure, optimize, and make better business decisions! 📈✅

#DataDrivenDecisions #MachineLearning #FinancialData #Underwriting #RiskAssessment #TransactionEnrichment #InHouseModeling #DataCategorization Read about insufficient data pitfalls of in-house transaction model building and advantages of outsourced models