Digital credit card with transparent pricing and app-native controls in Mexico
NOVACARD is a fintech credit card built for the Mexican market with a pricing model designed to eliminate hidden fees—a daily fixed cost replaces traditional annual charges, rotating interest, and opaque fees. The stack is operationally mature: PostgreSQL + SQL Server for transactional workloads, Kubernetes + Terraform for infrastructure, and Prometheus + Grafana + Zabbix for observability. Active engineering effort around collections automation and credit decisioning (test automation for scoring, decision accuracy modeling) signals scaling pain as the user base grows; their infrastructure and observability roadmap reflects engineering-led build for product stability at scale.
NOVACARD is a fintech startup offering credit cards to retail consumers in Mexico. The product emphasizes transparency: fixed daily costs, no hidden fees, and grace periods for payment flexibility. The company has over 90,000 active cardholders. The founding team is building collections infrastructure from scratch—a typical expansion phase for early-stage lending platforms—while simultaneously investing in operational maturity through infrastructure automation, incident prevention, and system observability. Operations span Mexico as the primary market with technical hiring also in Brazil, Serbia, Kazakhstan, and Armenia, suggesting a distributed engineering model.
NOVACARD runs PostgreSQL and SQL Server for databases, AWS for cloud infrastructure, Kubernetes for orchestration, and Prometheus + Grafana + Zabbix for monitoring and observability. Development uses Python, Go, and Bash; data pipelines use Fivetran; and ERP systems include SAP, Oracle, and NetSuite.
Active projects include launching a collections pilot program in Mexico, test automation for credit scoring, infrastructure automation and observability (Grafana and Zabbix dashboards), external data provider integrations, and improving credit decisioning accuracy.
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