Inter & Co recorded 65.6% CDI (Certificado de Depósito Interbancário) funding costs in Q4 2024, the lowest rate among Brazilian financial institutions serving over 20 million clients. Traditional banks in Brazil operate 15-20 percentage points higher, a gap comparable to digital-versus-traditional spreads in India's UPI-based lenders and Southeast Asian neobanks.
Both Inter and Nu Holdings deployed production AI credit models during 2025. Nu's nuFormer system processes loan applications using machine learning trained on over 100 million customer data points. The technology maintains risk-adjusted net interest margins despite government FGTS (employment guarantee fund) program changes that reduced industry margins, according to CFO Guilherme Lago.
Inter's newer client cohorts transact faster and more frequently than earlier users, indicating improved targeting from algorithmic underwriting. The bank became Brazil's fastest-growing financial institution among those exceeding 20 million clients, growth correlating with real-time risk pricing unavailable to competitors without comparable AI systems.
The funding cost advantage creates a compounding cycle: lower deposit rates improve margins, funding customer acquisition, which generates more training data for credit models. This flywheel allows digital banks to underprice traditional lenders while maintaining profitability, a pattern visible across emerging markets from Jakarta to Lagos.
Brazil's Central Bank requires identical minimum capital ratios regardless of underwriting technology. AI models help digital banks optimize within these constraints by identifying lower-risk borrowers who receive identical treatment under traditional methods. The regulatory framework mirrors approaches in Mexico, Colombia, and other Latin American markets balancing fintech innovation with systemic stability.
The 2026-2027 period will test whether AI credit advantages survive economic cycles. Brazilian interest rates remain volatile, and machine learning models trained during growth periods may underperform in downturns. Non-performing loan rates will determine if current efficiency gaps reflect permanent structural advantages or temporary market conditions, with implications for digital banking strategies across developing economies where similar AI deployment is accelerating.
Sources:
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