Towards Routines Mining – Designing and Implementing the Argos Miner, a Design Science Artifact for Studying Routine Dynamics with Process Mining

ABSTRACT Auditors face new challenges when auditing internal controls due to the increasing integration of information systems for transaction processing and the growing amount of data. Traditional manual control testing procedures become inefficient or require highly specialized and scarce technical knowledge. This study presents audit procedures that follow a new approach. Instead of manually testing internal controls, automated procedures search for the absence of those controls. Process mining techniques are combined with advanced statistical analysis where process mining serves as a data analysis technique to create process models from the recorded transaction data. These are searched for critical data constellations in combination with an exploratory factor analysis to identify systematic deficiencies in the internal control system. The manual and time-intensive inspection of individual controls is replaced by automated audit procedures that cover the totality of recorded transactions. The study follows a design science approach and uses case study data for illustration.

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How Low Can We Go? Proposing Quantifying the Going Concern Survival Index (GCSI) and One Month Resilience Index (OMRI) as Metrics of Firm Risk in the Wake of the Coronavirus Crisis

Journal of Emerging Technologies in Accounting ◽

10.2308/jeta-2020-060 ◽

2020 ◽

Author(s):

Glen L. Gray ◽

Michael Alles

Keyword(s):

Process Mining ◽

Design Science ◽

Science Research ◽

Cash Flows ◽

Net Income ◽

Firm Risk ◽

Going Concern ◽

The Future ◽

Going Concern Opinion ◽

Resilience Index

The coronavirus crisis disrupted business survivability. Measures, like going concern opinion and bankruptcy predictors, depend on past trends extending into the future. With black swan events, past trends do not extend into the future. We propose two new metrics. The “Going Concern Survivability Index” ( GCSI) is the maximum percentage revenue loss that a business can endure as a going concern. The “One Month Resilience Index” (OMRI) is the effect on the net income from the loss of the revenue its most successful month. While OMRI is straightforward, calculating GCSI requires real options and process mining. The emerging technology of process mining and artificial intelligence are needed to capture the dynamic process by which management will juggle cash flows, sources of funds, and payment of liabilities as revenue falls. This paper is an instance of action design science research and we discuss the steps to put our artifact into practice.

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