Challenges in Handling Real-Time Payments

Despite the success, real-time payments present significant challenges for banks:

1.Scalability Issues: Legacy banking infrastructure struggles to handle the massive surge in transaction volumes.

2.Fraud and Security Risks: Instant payments increase the risk of fraud, phishing, and cyberattacks. For example, SIM swap fraud and social engineering attacks have become more prevalent with the rise of UPI.

3.Regulatory Compliance: RBI mandates stringent data security and transaction monitoring requirements.

4.Transaction Failures & Downtime : Even a few minutes of downtime can impact millions of users and erode trust.

5.Reconciliation & Settlement Delays : Ensuring accurate reconciliation in real-time across multiple banking entities is a challenge.

How Banks Can Prepare for the Future

Given the constraints of legacy infrastructure and the gradual adoption of public cloud, Indian banks must take a strategic and incremental approach to modernization with the following strategies:

1.Incremental Core Banking Modernization

Rather than a full rip-and-replace approach, banks should adopt progressive modernization by gradually migrating specific workloads to modern architectures.

Implement middleware layers and APIs that enable real-time transaction processing while coexisting with legacy systems.

Invest in low-code and no-code platforms to accelerate the modernization of backend processes without significant development efforts.

Utilize containerized solutions such as Kubernetes to manage scalability without overhauling core banking platforms immediately.

2.Hybrid Cloud Strategies for Scalable Processing

Since public cloud adoption is progressing at a slower pace, banks should prioritize a hybrid cloud approach, leveraging private cloud for critical workloads while gradually shifting non-core functions to public cloud environments.

Use edge computing for localized transaction processing, reducing dependency on centralized systems and minimizing latency.

Deploy cloud-based disaster recovery (DR) solutions to ensure business continuity and resilience.

3.AI & ML for Fraud Prevention

Deploy AI-driven fraud detection systems to analyze transaction patterns and flag suspicious activities in real time.

Implement biometric authentication and AI-based risk scoring mechanisms for enhanced security.

Integrate AI-driven anomaly detection to identify and mitigate potential fraud attempts proactively.

4.24x7 High-Availability Systems Without Complete Overhaul

Implement active-active disaster recovery models to ensure zero downtime without requiring a complete infrastructure overhaul.

Utilize load balancing and traffic routing technologies to optimize transaction flow and reduce processing delays.

Adopt microservices-based architecture selectively in new implementations while maintaining compatibility with existing monolithic systems.

Deploy self-healing networks using AI to predict failures and take proactive recovery measures.

5.Real-Time Reconciliation & Settlement Solutions Without Disrupting Legacy Systems

Rather than fully replacing existing reconciliation processes, implement real-time reconciliation layers that integrate with legacy back-end systems.

Utilize blockchain and smart contracts to automate reconciliation, ensuring transparency and auditability.

Deploy RPA (Robotic Process Automation)or IPA (Intelligent Process Automation) for settlement operations, reducing manual intervention while improving accuracy.

Introduce AI-powered liquidity management tools that predict cash flow needs and optimize real-time settlements without manual interventions.

6.Compliance-Driven Innovation

Enhance compliance frameworks with automated regulatory reporting and AI-driven monitoring.

Implement secure data encryption and privacy-enhancing technologies to meet regulatory guidelines while modernizing legacy systems.

Adopt RegTech (Regulatory Technology) solutions to streamline compliance processes and reduce operational overhead.

Conclusion

The rapid rise of UPI, IMPS, and RTGS has set new benchmarks in digital payments, but banks must balance modernization with cost constraints and operational realities. Given the capital-intensive nature of core banking transformation and the slow pace of public cloud adoption, banks should focus on incremental modernization, hybrid cloud strategies, and AI-driven efficiencies. By taking a phased approach and integrating modern solutions with existing infrastructure, banks can ensure a resilient, scalable, and future-ready real-time payments ecosystem without causing significant disruptions to ongoing operations.

Contact Us

If you have any questions, feedback, or would like to discuss how your organization can navigate the evolving landscape of real-time payments, feel free to reach out to us. We’d be happy to assist you with insights, strategies, and solutions tailored to your needs.
Email: abhijit@eklogi.com
Website: www.eklogi.com
Follow us on to stay updated on the latest trends and innovations in the banking and payments industry.