The impetus for this paper came after the financial crisis of 2007-2008, its global consequences and specifically how incomplete information "information asymmetry" between local banks and regulators extremely affected the banking sector. Financial institutions and regulators are-from a technical point of view-not yet fully integrated and standardised. The inaccuracy in banks' data and the long (quarterly) intervals between reports to the regulators leads to delayed interventions by local supervisory regulators. Most regional banks use an internal ratingsbased approach (IRB) that allows them to use their own methods to calculate credit risks, which makes it difficult for regulators to verify and validate the banks' data without a standardised procedure and the benefit of fully automated connectivity for the regulatory reporting system through sophisticated IT tools. The importance of this issue, for the central banks, motivates the researcher to investigate and seek technology solutions in the interests of maximising the technical efficiency of the regulatory banking system. This paper is focused on the banking regulatory reporting system that uses IRB approach to evaluate credit risk. Due to the importance and the sensitivity of IRB approach on the banking credit risk assessments, a case study is examined and a tailored regulatory reporting system framework is proposed. The proposed framework integrates a private cloud computing network with standardised, automated and integrated features that would provide regulators and practitioners with a new method to enhance the regulatory reporting system.

Purpose-This paper firstly examines how business process change decisions (BPCDs) were implemented in a government organisation bound by tightly-coupled temporal constraints (TTCs). Secondly, it focuses on how to achieve optimal and efficient BPCDs that require tight compliance with regulators' temporal constraints. Finally, it formulates a rigorous framework that can facilitate the execution of optimal BPCDs with maximum efficiency and minimal effort, time and cost. Design/methodology/approach-Decision making biases by individuals or groups in organisations can impede optimal BPC implementation; to demonstrate this a case study is investigated and the formulated framework is applied to tackle these failings. Research findings-The case study analysis shows 76% of the BPCDs implemented were inefficient, mostly due to poor decisions and these resulted in negative ripple effects. In response, the newly developed hierarchical change management structure (HCMS) framework was employed to empower organisations to execute high velocity BPCDs, enabling them to handle any temporal constraints imposed by regulators or other exogenous factors. The HCMS framework was found to be highly effective, scoring an average improvement of more than 100% when measured using decision quality dimensions. This paper would be of value for business executives and strategic decision-makers engaging with BPC. Research limitations/implications-The HCMS framework has been applied in a single case study as a proof of concept. Future research could extend its application to broader domains that have multi-attribute structures and environments. The evaluation processes of the proposed framework are based on subjective metrics. Causal links from the framework to business process metrics will provide a more complete performance picture. Practical implications-The outcome of this research assists in formulating a systematic BPCD framework that is otherwise unavailable. The practical use of the proposed framework would potentially impact on quality outcomes for organisations. The model is derived from decision trees and analytical hierarchical processes and is tailored to address this problematic area. The proposed HCMS framework would help organisations to execute efficient BPCDs with minimal time, effort and cost. The HCMS framework contributes to the academic literature on BPCD that leverages diverse stakeholders to engage in BPC initiatives. Originality/value-The research presents a novel framework − the hierarchical change management structure − that provides a platform for organisations to easily determine and solve hierarchical decision structure problems, thereby allowing them to efficiently automate and institutionalise optimal BPCDs.

in 2011. He is currently a doctoral researcher at Griffith University in the area of business process change. His current research interests include business process management, business process change, regulatory policy implementation and computational models and governance frameworks. Steve Drew AbstractThe hierarchical elicitation workshop is a new initiative designed and developed to address common shortcomings in business process change initiatives in organisations, particularly those with tight temporal constraints imposed by exogenous bodies. This paper presents a systematic solution to deal with dramatic BPC under tight temporal constraints in large business and government organisations. In an empirical case study, the hierarchical elicitation workshop is developed and trialed. Based on the Software Engineering Institute's Quality Attribute Workshop methodology, a step-by-step process was carried out to elicit and validate the required BPC factors. Engaging internal stakeholder teams to consider implications for BPC with respect to factors such as organisational objectives and strategies, governance, business process architecture and applications, a prioritised list of change actions was systematically elicited and then implemented. The HEW framework and process was successfully applied to elicit BPC factors in this case study, with an immediate and effective implementation of process change. This paper will be of particular interest to researchers of change management and business development.

He is currently a doctoral researcher at Griffith University in the area of business process change. His current research interests include business process management, business process change, regulatory policy implementation and computational models and governance frameworks.