1. Java: Trusted for secure, scalable banking systems with strong encryption and platform independence.
2. Python: Ideal for data analysis, fraud detection, and AI-based banking solutions with rich libraries.
3. SQL: Crucial for managing and querying financial data in robust relational databases.
4. C#: Powers enterprise-level banking apps with integration into .NET for enhanced performance.
5. R: Preferred for risk modeling, statistical analysis, and financial data visualization.
6. Scala: Combines functional and object-oriented programming for big data and real-time banking analytics.
7. Kotlin: Efficient for developing secure and user-friendly mobile banking applications.
8. Go: Enables high-performance backend systems for concurrent and reliable banking operations.
9. Ruby: Powers fast prototyping for banking tools with an emphasis on security and scalability.
10. MATLAB: Used for quantitative finance, portfolio optimization, and risk assessment in banking models.