Designing Dynamic Questionnaire Engines for Risk-Based Account Review Workflows
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DOI:
https://doi.org/10.67228/pbmpew97Published 06-29-2021
Dynamic Questionnaire, Dependent Questions, Looping Workflow, Risk Scoring, Audit Trail, Workflow Automation, Review Lifecycle, Regulated Accounts Issue
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ArticlesHow to Cite
[1]A. Potharaju, “Designing Dynamic Questionnaire Engines for Risk-Based Account Review Workflows”, IJADSMC, vol. 4, no. 1, pp. 01–37, Jun. 2021, doi: 10.67228/pbmpew97.Abstract
Regulators are putting more pressure on financial institutions to do risk-based reviews of accounts. But the traditional approach is to send out paper questionnaires with the same questions for everyone, regardless of the individual customer profile. This inflexibility results in duplicated data collection, longer review cycles, lower reviewer productivity and poor adaptability to changing risk profiles. To address these inefficiencies, this paper proposes a holistic framework of a dynamic questionnaire engine to adapt account review workflows in real-time. The proposed enterprise architecture has conditional logic and dependent question structures, automated looping, configurable risk scoring, and workflow orchestration. The system dynamically builds the appropriate questions based on the type of account, transaction patterns, historical review information and the policies of the organization, rather than static forms. Automatically triggers review priority, escalations and other verifications. Fully compliant with integrated audit trails that capture every reviewer action, scoring decision and workflow transition. Results show that this adaptive framework removes redundant data collection, accelerates review cycles, simplifies policy updates without code refactoring and significantly enhances operational governance.
References
[1] Alter, S. (2013). Work system theory: Overview of core concepts, extensions, and challenges for the future. Journal of the Association for Information Systems, 14(2), 72–121.
[2] Dumas, M., La Rosa, M., Mendling, J., & Reijers, H. A. (2018). Fundamentals of business process management (2nd ed.). Springer.
[3] Hall, J. A. (2018). Accounting information systems (10th ed.). Cengage Learning.
[4] International Organization for Standardization. (2018). ISO 31000:2018 Risk management—Guidelines. ISO.
[5] Kimball, R., & Ross, M. (2013). The data warehouse toolkit: The definitive guide to dimensional modeling (3rd ed.). John Wiley & Sons.
[6] Laudon, K. C., & Laudon, J. P. (2020). Management information systems: Managing the digital firm (16th ed.). Pearson.
[7] Marakas, G. M., & O'Brien, J. A. (2013). Introduction to information systems (16th ed.). McGraw-Hill Education.
[8] Object Management Group. (2014). Business Process Model and Notation (BPMN) Version 2.0.2. Object Management Group. https://www.omg.org/spec/BPMN/2.0.2/
[9] Project Management Institute. (2017). A guide to the project management body of knowledge (PMBOK® Guide) (6th ed.). Project Management Institute.
[10] Stair, R., & Reynolds, G. (2019). Principles of information systems (13th ed.). Cengage Learning.
[11] Turban, E., Pollard, C., & Wood, G. (2018). Information technology for management: Driving digital transformation to increase local and global performance, growth, and sustainability (11th ed.). John Wiley & Sons.
[12] van der Aalst, W. M. P. (2016). Process mining: Data science in action (2nd ed.). Springer.
[13] Weske, M. (2019). Business process management: Concepts, languages, architectures (3rd ed.). Springer.
[14] Workflow Management Coalition. (1999). Workflow management coalition terminology and glossary (Document WFMC-TC-1011). Workflow Management Coalition.
[15] Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.
[16] Association of Certified Anti-Money Laundering Specialists. (2021). Anti-money laundering risks in financial institutions. ACAMS.
[17] Basel Committee on Banking Supervision. (2019). Guidelines on corporate governance principles for banks. Bank for International Settlements.
[18] Deloitte. (2020). Digital transformation in financial services: Risk, compliance and operational resilience. Deloitte Insights.
[19] Financial Action Task Force. (2013). International standards on combating money laundering and the financing of terrorism & proliferation (The FATF Recommendations). FATF. (Updated through 2020).
[20] Gartner. (2020). Market guide for intelligent business process management suites. Gartner Research.
[21] Hammer, M., & Champy, J. (2009). Reengineering the corporation: Manifesto for business revolution (Rev. ed.). Harper Business.
[22] Inmon, W. H. (2005). Building the data warehouse (4th ed.). John Wiley & Sons.
[23] International Organization for Standardization. (2015). ISO 9001:2015 Quality management systems—Requirements. ISO.
[24] Kelleher, J. D., & Tierney, B. (2018). Data science. MIT Press.
[25] Kroll, J. A., Huey, J., Barocas, S., Felten, E. W., Reidenberg, J. R., Robinson, D. G., & Yu, H. (2017). Accountable algorithms. University of Pennsylvania Law Review, 165(3), 633–705.
[26] Mell, P., & Grance, T. (2011). The NIST definition of cloud computing (NIST Special Publication 800-145). National Institute of Standards and Technology.
[27] National Institute of Standards and Technology. (2020). Security and privacy controls for information systems and organizations (Special Publication 800-53 Rev. 5). U.S. Department of Commerce.
[28] Object Management Group. (2013). Decision Model and Notation (DMN) Version 1.0. Object Management Group.
[29] O'Leary, D. E. (2004). On the relationship between REA and SAP. International Journal of Accounting Information Systems, 5(1), 65–81.
[30] Oracle Corporation. (2020). Oracle business process management suite: Technical overview. Oracle Corporation.
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How to Cite
[1]A. Potharaju, “Designing Dynamic Questionnaire Engines for Risk-Based Account Review Workflows”, IJADSMC, vol. 4, no. 1, pp. 01–37, Jun. 2021, doi: 10.67228/pbmpew97.