The Influence of Data Structures on Optimal Algorithm Design and Performance in Fintech

This Present Study Topic is ‘The Influence of Data Structures on Optimal Algorithm Design and Performance in Fintech’ The efficient data structures play a critical role in improving algorithm design, computational speed, scalability, and memory optimisation within fintech systems. Recent fintech studies emphasise that modern financial platforms process massive real-time transactional data, requiring optimised algorithms supported by advanced data structures such as trees, graphs, hash tables, heaps, and distributed ledgers. Financial Technology applications, including digital banking, fraud detection, blockchain, algorithmic trading, and risk management, rely heavily on these computational techniques to maintain performance and security. Artificial Intelligence and reinforcement learning demonstrated that optimal algorithm design supports decision-making, portfolio optimisation, fraud detection, and automated trading systems. Researchers concluded that the integration of suitable data structures with intelligent algorithms improves prediction accuracy, computational efficiency, and operational scalability in fintech applications. These technologies are becoming increasingly important in modern digital financial ecosystems driven by big data and real-time analytics.