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All Journal The Eastasouth Journal of Information System and Computer Science
Kusumba, Surender
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Computer Science & IT

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Achieving Financial Certainty: A Unified Ledger Integrity System for Automated, End-to-End Reconciliation Kusumba, Surender
The Eastasouth Journal of Information System and Computer Science Vol. 1 No. 01 (2023): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v1i01.842

Abstract

Modern enterprises face mounting challenges in maintaining financial data integrity across fragmented system landscapes. Traditional reconciliation processes rely heavily on manual intervention and periodic batch processing. These methods introduce operational inefficiencies and elevate the risk of financial misstatement. Accounts Payable, General Ledger, Treasury, and Standard General Ledger systems operate independently with limited integration. Data moves between these platforms through scheduled transfers that create timing mismatches and semantic inconsistencies. Finance teams spend extensive time comparing reports and investigating discrepancies during period-end closing cycles. Human error compounds these challenges as staff manually validate thousands of transactions. The lack of real-time visibility prevents early detection of errors and fraud. Organizations need transformative solutions that automate reconciliation workflows and provide continuous financial assurance. Unified Ledger Integrity Systems address these critical gaps through centralized data architectures and intelligent automation. These platforms ingest transaction data from disparate sources into a single reconciliation engine. Rules-based matching algorithms identify corresponding transactions across systems automatically. Machine learning models enhance matching accuracy over time by learning from historical patterns. Exception management workflows route unmatched transactions to appropriate team members for investigation. Continuous processing occurs throughout the business day rather than in periodic batches. This architectural shift enables finance organizations to transition from reactive auditing to proactive data quality management. Real-time exception flagging allows immediate investigation while transaction context remains fresh. Comprehensive audit trails satisfy regulatory compliance requirements and support external auditor reliance on internal controls. Organizations adopting these platforms experience substantial reductions in closing cycle times and improvements in data accuracy. Finance professionals redirect their efforts from manual validation to strategic exception analysis. The technology establishes a resilient foundation for corporate governance and enables agile decision-making based on high-confidence financial information.
Accelerating AI and Data Strategy Transformation: Integrating Systems, Simplifying Financial Operations Integrating Company Systems to Accelerate Data Flow and Facilitate Real-Time Decision-Making Kusumba, Surender
The Eastasouth Journal of Information System and Computer Science Vol. 2 No. 02 (2024): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v2i02.866

Abstract

The rapid advancement of artificial intelligence (AI) and data-driven technologies has intensified the need for organizations to integrate heterogeneous systems and redesign their data strategies to support real-time decision-making and financial efficiency. This study investigates how system integration accelerates AI and data strategy transformation and simplifies financial operations in the Energy and Utilities sector in the United States. Using a quantitative research design, data were collected from 250 professionals in 2024 through a structured questionnaire measured on a five-point Likert scale. The data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS 3) to examine the relationships among system integration, data architecture and integration, AI and business intelligence capability, real-time decision-making, and financial operational performance. The results reveal that system integration significantly enhances data integration and AI-enabled analytical capability, which in turn improves real-time decision-making. Real-time decision-making emerges as the strongest predictor of improved financial operational performance, particularly in budgeting and forecasting processes. Furthermore, the findings demonstrate that the impact of system integration on financial performance is largely mediated by data integration, AI and BI capability, and decision-making capability. This study contributes to the digital transformation literature by providing empirical evidence from a multi-cloud context and offers practical insights for Energy and Utilities organizations seeking to leverage AI and data strategies to achieve agile, data-driven financial management.
Strengthening True Performance Accountability: Seamless Integration Between Financial Systems and The Cloud to Gain Real-Time Insights into Budget Costs Kusumba, Surender
The Eastasouth Journal of Information System and Computer Science Vol. 2 No. 01 (2024): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v2i01.867

Abstract

Strengthening performance accountability has become increasingly important for organizations operating in complex and data-intensive environments, particularly within the energy and utilities sector in the United States. Fragmented financial systems and delayed budget reporting often limit transparency, weaken cost control, and constrain managerial accountability. This study examines how seamless integration between financial systems and cloud-based platforms facilitates genuine performance accountability through real-time budget insights. Adopting a quantitative research design, data were collected from 300 professionals working in finance, accounting, management, and information systems roles within U.S. energy and utilities organizations. The data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS 3). The findings reveal that financial system integration and cloud capability both have significant positive effects on real-time budget insights and true performance accountability. Moreover, real-time budget insights partially mediate the relationships between financial system integration and performance accountability, as well as between cloud capability and performance accountability. These results demonstrate that digital financial infrastructure strengthens accountability most effectively when it generates continuous, real-time budget visibility that supports timely decision-making and transparent financial oversight. This study contributes to the literature on digital finance and performance management by empirically positioning real-time budget insights as a critical mechanism linking cloud-enabled financial integration to accountability outcomes. Practically, the findings offer guidance for organizations seeking to enhance budget transparency and accountability through integrated and cloud-based financial systems.
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