Towards a Formal Framework for Partial Compliance of Business Processes

• URL: http://arxiv.org/abs/2012.13219v1
• Date: Thu, 24 Dec 2020 12:38:40 GMT
• Title: Towards a Formal Framework for Partial Compliance of Business Processes
• Authors: Ho-Pun Lam and Mustafa Hashmi and Akhil Kumar
• Abstract summary: In this paper, we formulate an evaluation framework to quantify the level of compliance of business processes across different levels of abstraction. Our approach can also add social value by making social services provided by local, state and federal governments more flexible and improving the lives of citizens.
• Score: 0.5156484100374059
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Binary "YES-NO" notions of process compliance are not very helpful to managers for assessing the operational performance of their company because a large number of cases fall in the grey area of partial compliance. Hence, it is necessary to have ways to quantify partial compliance in terms of metrics and be able to classify actual cases by assigning a numeric value of compliance to them. In this paper, we formulate an evaluation framework to quantify the level of compliance of business processes across different levels of abstraction (such as task,trace and process level) and across multiple dimensions of each task (such as temporal, monetary, role-, data-, and quality-related) to provide managers more useful information about their operations and to help them improve their decision making processes. Our approach can also add social value by making social services provided by local, state and federal governments more flexible and improving the lives of citizens.

Related papers

• Unlocking Sustainability Compliance: Characterizing the EU Taxonomy for Business Process Management [2.474551220017185]
  The EU has developed the taxonomy of sustainable activities, which describes when exactly business practices can be considered sustainable. We investigate in how far these criteria can be used for conformance checking, that is, assessing in a data-driven manner, whether business process executions adhere to regulatory constraints. We find that many constraints of the taxonomy are useable for conformance checking, particularly in the sectors of energy, manufacturing, and transport.
  arXiv  Detail & Related papers  (2024-08-21T07:30:11Z)
• Identification of Regulatory Requirements Relevant to Business Processes: A Comparative Study on Generative AI, Embedding-based Ranking, Crowd and Expert-driven Methods [10.899912290518648]
  This work examines how legal and domain experts can be assisted in the assessment of relevant requirements. We compare an embedding-based NLP ranking method, a generative AI method using GPT-4, and a crowdsourced method with the purely manual method of creating labels by experts. A gold standard is created for both BPMN2.0 processes and matched to real-world requirements from multiple regulatory documents.
  arXiv  Detail & Related papers  (2024-01-02T12:08:31Z)
• Flexible categorization for auditing using formal concept analysis and Dempster-Shafer theory [55.878249096379804]
  We study different ways to categorize according to different extents of interest in different financial accounts. The framework developed in this paper provides a formal ground to obtain and study explainable categorizations.
  arXiv  Detail & Related papers  (2022-10-31T13:49:16Z)
• Relational Action Bases: Formalization, Effective Safety Verification, and Invariants (Extended Version) [67.99023219822564]
  We introduce the general framework of relational action bases (RABs) RABs generalize existing models by lifting both restrictions. We demonstrate the effectiveness of this approach on a benchmark of data-aware business processes.
  arXiv  Detail & Related papers  (2022-08-12T17:03:50Z)
• A Modular Framework for Reinforcement Learning Optimal Execution [68.8204255655161]
  We develop a modular framework for the application of Reinforcement Learning to the problem of Optimal Trade Execution. The framework is designed with flexibility in mind, in order to ease the implementation of different simulation setups.
  arXiv  Detail & Related papers  (2022-08-11T09:40:42Z)
• Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications [85.24952708195582]
  This study examines the goals, community practices, assumptions, and constraints that shape NLG evaluations. We examine their implications and how they embody ethical considerations.
  arXiv  Detail & Related papers  (2022-05-13T18:00:11Z)
• Towards a multi-stakeholder value-based assessment framework for algorithmic systems [76.79703106646967]
  We develop a value-based assessment framework that visualizes closeness and tensions between values. We give guidelines on how to operationalize them, while opening up the evaluation and deliberation process to a wide range of stakeholders.
  arXiv  Detail & Related papers  (2022-05-09T19:28:32Z)
• Inverse Online Learning: Understanding Non-Stationary and Reactionary Policies [79.60322329952453]
  We show how to develop interpretable representations of how agents make decisions. By understanding the decision-making processes underlying a set of observed trajectories, we cast the policy inference problem as the inverse to this online learning problem. We introduce a practical algorithm for retrospectively estimating such perceived effects, alongside the process through which agents update them. Through application to the analysis of UNOS organ donation acceptance decisions, we demonstrate that our approach can bring valuable insights into the factors that govern decision processes and how they change over time.
  arXiv  Detail & Related papers  (2022-03-14T17:40:42Z)
• Trustworthy Artificial Intelligence and Process Mining: Challenges and Opportunities [0.8602553195689513]
  We show that process mining can provide a useful framework for gaining fact-based visibility to AI compliance process execution. We provide for an automated approach to analyze, remediate and monitor uncertainty in AI regulatory compliance processes.
  arXiv  Detail & Related papers  (2021-10-06T12:50:47Z)
• On the Composition of the Long Tail of Business Processes: Implications from a Process Mining Study [0.0]
  Digital transformation forces companies to rethink their processes to meet current customer needs. Business Process Management (BPM) can provide the means to structure and tackle this change. Most approaches to BPM face restrictions on the number of processes they can optimize at a time due to complexity and resource restrictions. Investigating this shortcoming, the concept of the long tail of business processes suggests a hybrid approach that entails managing important processes centrally, while incrementally improving the majority of processes at their place of execution.
  arXiv  Detail & Related papers  (2020-11-26T09:04:15Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.