Authors :
Tuyisenge Marie Josee; Dr. Wilson Musoni
Volume/Issue :
Volume 10 - 2025, Issue 3 - March
Google Scholar :
https://tinyurl.com/5jr4bwwn
Scribd :
https://tinyurl.com/mprmc2dx
DOI :
https://doi.org/10.38124/ijisrt/25mar1746
Google Scholar
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Note : Google Scholar may take 15 to 20 days to display the article.
Abstract :
Recent technological advancements, particularly in banking and financial services, have profoundly influenced
the development and use of applications. The increasing demand for modern banking systems to address consumer
expectations, speed up market entry, enhance user experiences, improve security, and optimize system efficiency has led to
the adoption of new technologies. This trend has sparked the creation of numerous banking-specific modernization solutions.
Within the interconnected banking, financial services, and insurance (BFSI) sectors, the need for effective enterprise
application integration (EAI) is crucial for gaining both technological and business advantages. Real-time data streaming
through technologies like Apache Kafka has become essential for enabling seamless communication between systems. Kafka,
a widely used distributed streaming platform, surpasses traditional message queues in scalability, message retention, data
replication, and processing order, making it an essential part of modern banking systems. Unlike batch processing, which
processes large volumes of data at set intervals and can cause delays in transactions, streaming technologies eliminate lag
by processing data continuously in real-time, significantly enhancing the speed and accuracy of financial operations. The
shift from batch systems to real-time streaming allows BFSI applications to process transactions and settlements more
quickly, reducing processing times and improving operational efficiency. Additionally, the use of Kafka enhances the
security and reliability of data transfers, making it a valuable tool for modernizing banking infrastructures. Therefore,
integrating real-time streaming technologies like Kafka not only improves system performance but also boosts security,
scalability, and operational effectiveness, enabling financial institutions to better meet customer demands in an increasingly
digital economy.
References :
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- david. (2023). realtime notification. Retrieved from https://ultimatemember.com/extensions/real-time-notifications/#:~:text=Add%20a%20real%2Dtime%20notification,when%20user%20role%20is%20changed.
- Erin Brenner,Stan Carey. (2023). Monitoring. Retrieved from https://www.vocabulary.com/dictionary/monitoring
- Hassanalieragh, M., Page, A., Soyata, T., Sharma, G., Aktas, M., Mateos, G., ... & Andreescu, S. . (2015). Health monitoring and management using Internet-of-Things (IoT) sensing with cloud-based processing: Opportunities and challenges. . IEEE international conference on services computing (pp. 285-292). IEEE.
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- Nurdin, M. R. F., Hadiyoso, S., & Rizal, A. . (2016). A low-cost Internet of Things (IoT) system for multi-patient ECG's monitoring. September). A low-cost Internet of Things (IoT) system for multi-patient ECG's monitoring. In 2016 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) .
- Saddam. (2015, november 4). Automatic Water Level Indicator and Controller using Arduino. Retrieved june 29, 2023, from circuitdigest: https://circuitdigest.com/microcontroller-projects/water-level-indicator-project-using-arduino
- wikipedia. (2023). what is alerting. Retrieved from https://en.wikipedia.org/wiki/Alerting_system
- wikpedia. (2024, january 06). Meaning of Health_care. Retrieved from wikipedia.org: https://en.wikipedia.org/wiki/Health_care#:~:text=For%20other%20uses,and%20individuals%2C%20influenced
Recent technological advancements, particularly in banking and financial services, have profoundly influenced
the development and use of applications. The increasing demand for modern banking systems to address consumer
expectations, speed up market entry, enhance user experiences, improve security, and optimize system efficiency has led to
the adoption of new technologies. This trend has sparked the creation of numerous banking-specific modernization solutions.
Within the interconnected banking, financial services, and insurance (BFSI) sectors, the need for effective enterprise
application integration (EAI) is crucial for gaining both technological and business advantages. Real-time data streaming
through technologies like Apache Kafka has become essential for enabling seamless communication between systems. Kafka,
a widely used distributed streaming platform, surpasses traditional message queues in scalability, message retention, data
replication, and processing order, making it an essential part of modern banking systems. Unlike batch processing, which
processes large volumes of data at set intervals and can cause delays in transactions, streaming technologies eliminate lag
by processing data continuously in real-time, significantly enhancing the speed and accuracy of financial operations. The
shift from batch systems to real-time streaming allows BFSI applications to process transactions and settlements more
quickly, reducing processing times and improving operational efficiency. Additionally, the use of Kafka enhances the
security and reliability of data transfers, making it a valuable tool for modernizing banking infrastructures. Therefore,
integrating real-time streaming technologies like Kafka not only improves system performance but also boosts security,
scalability, and operational effectiveness, enabling financial institutions to better meet customer demands in an increasingly
digital economy.