Core Banking System

• 1. Fragmented and Disjointed Systems: We have multiple legacy systems that are not integrated or compatible with each other, leading to data silos, manual reconciliation, and inefficiencies in managing financial operations. This fragmentation complicates decision-making, data reporting, and regulatory compliance.

  2. Slow and Inefficient Processes: Legacy systems often lead to delayed data. This is especially problematic for central banks, which need accurate and real-time data to inform monetary policy, manage liquidity, and comply with regulatory requirements.

  3. High Operational Costs: Maintaining and supporting multiple outdated systems is costly in terms of hardware, software, and human resources. These systems require frequent patches and manual interventions, driving up operational costs and diverting resources from other critical activities.

  4. Regulatory and Compliance Challenges: As regulatory requirements evolve, central banks need systems that can adapt quickly to new rules and compliance standards. Legacy systems may lack the flexibility to integrate with new regulations, making it harder to ensure compliance and increasing the risk of fines or penalties.

  5. Limited Customer and Stakeholder Service: Central banks often interact with commercial banks, the government, and other financial institutions. Disjointed systems may make it harder to provide timely, accurate information to stakeholders or to respond effectively to their needs, negatively impacting the overall service quality.

• 1. Streamlining Operations: Simplifying and automating critical banking functions such as currency issuance, monetary policy implementation, liquidity management, and transaction processing, allowing for more efficient operations across different departments.

  2. Improving Data Accuracy and Consistency: Centralizing data storage and processing, ensuring that information is accurate, consistent, and accessible across all functions in real-time. This enables better decision-making and reduces the risks associated with manual data reconciliation.

  3. Enhancing Regulatory Compliance: Facilitating adherence to regulatory requirements by automating compliance checks, reporting, and audits. This ensures that the central bank can meet legal and regulatory standards more easily and avoid penalties.

  4. Enabling Real-Time Processing: Supporting real-time or near-real-time processing of transactions, market interventions, and policy implementation, allowing the BI to respond more quickly to economic changes, currency fluctuations, or financial crises.

  5. Increasing Operational Efficiency: Reducing the operational costs associated with maintaining multiple legacy systems and processes. A CBS allows for centralized management of services, which lowers redundancy and enhances overall productivity.

  6. Improving Stakeholder Interaction and Customer Service: Facilitating better interactions with commercial banks, government agencies, and other financial institutions by offering more efficient data sharing, reporting, and processing capabilities.

  7. Enhancing Business Continuity and Disaster Recovery: Ensuring the continuity of banking operations in the event of a disaster or system failure by providing robust backup, recovery, and failover mechanisms.

• 1. System Downtime and Availability: Ensure the CBS is available and functioning without interruptions. Ideally, the system should have high availability (99.9% uptime or higher).

  2. Transaction Processing Time: Reduce the time required to process transactions, improving operational efficiency and real-time processing capabilities.

  3. System Response Time: Ensure the system provides fast responses for queries, such as customer account balance checks or transaction history requests, to enhance user experience.

  4. Transaction Error Rate: Percentage of transactions with errors (e.g., failed payments, incorrect balance updates).

  5. Operational Cost Savings: Quantify the cost savings due to increased efficiency, reduced system maintenance, and automation of manual processes.

  6. Security Incident Rate: Number of security incidents or breaches reported.

  7. Business Continuity and Disaster Recovery Performance: Time taken to recover after a system failure or disaster.

  8. Data Accuracy and Consistency: Accuracy and consistency of data across the system (e.g., account balances, transaction records).

  9. Customer Impact (End-User Metrics): Ensure that the new system leads to a better overall experience for both internal and external users, improving satisfaction and engagement.

BI internal team, Ministry of Finance of Republic of Indonesia, banks, and PERURI

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Limited use for BI, Ministry of Finance of Republic of Indonesia, conventional banks, and PERURI