Data Detail is Crucial: To perform causal analytics like Marketing Mix Modeling, you must preserve raw, event-level data (joint distributions). Summary reports (marginals) discard the necessary context to attribute success to specific combinations of customer traits. Avoid the "Average" Trap: Aggregated data can hide the true story. Two completely different customer behaviors can look identical in summary reports, making accurate attribution impossible without the raw source

AI is redefining finance, but trust remains its currency. As AI systems make increasingly high-stakes decisions—who gets a loan, who’s flagged for AML, who receives an offer—the cost of error multiplies. The message for financial leaders is clear: A black-box AI might optimize for accuracy but can expose the bank to unseen bias, regulatory penalties, or wasted budgets. A Responsible AI framework builds resilience, customer confidence, and long-term value.