SPT Wirtschaftsprüfung automates the analysis of heterogeneous client data

Customer Success Story with SPT Wirtschaftsprüfung

How dab helps SPT transform different data structures into reusable audit and analytics processes.

SPT Wirtschaftsprüfung works with data from different client environments in its audit engagements. Depending on the client, the data is provided in different structures, withdifferent field names and in different formats, primarily as CSV files and, in some cases, as TXT files. Until now, preparing this data for analysis in ACL Analytics involved a high degree of manual effort.

Together with dab, SPT developed an approach that combines client-specific data imports with a standardized materiality analysis. The project focused on consulting, process structuring, and the automation of recurring work steps.

About SPT

SPT Wirtschaftsprüfung & Steuerberatung is based in Dornbirn, Vorarlberg, Austria. It is one of the leading audit and tax advisory firms in Vorarlberg. Its clients are diverse, ranging from regionally active SMEs and sole proprietorships to global players and private foundations.

From manual data preparation to repeatable analytics workflows

At SPT, the central task was to make data from different clients usable for audit and materiality analyses. Clients generally provide their data (from SAP or other source systems) as files. These files must then be imported into ACL Analytics and prepared and structured so that the relevant analyses can access them reliably.

In practice, this step was particularly time-consuming. The files supplied did not follow a consistent structure. A field might be called “invoice number” for one client and “document number” for another. Comparable content might be labeled “document type” or “posting code”. Some fields were available in certain data sets but missing in others. It was therefore not possible to process every client’s data using a single, unchanged import schema.

At the same time, the audit analysis itself needed to remain as consistent as possible. For SPT, it was essential that key audit areas such as key-date analyses, cut-off testing, sampling, gap analyses, critical text searches, numerical reconciliations, and Benford analyses could be performed using transparent, repeatable logic.

Heterogeneous client data as a practical project requirement

The challenge was not limited to the technical import of the files. The key was to correctly interpret the business meaning of the data fields and transform them into a structure that would enable standardized analysis in the first place.

dab therefore established a clear separation between data import and analysis. The import logic is adapted for each client because the source data is supplied differently. The materiality analysis, by contrast, remains standardized and accesses the previously harmonized data set. This allows SPT to accommodate different data realities without having to rebuild the audit analysis from scratch for every client.

This approach reflects dab’s understanding of data work: data should not merely be technically available. It should be structured and prepared in a clear, comprehensible way so that different departments can use it reliably in their processes. The initial business and technical preparation creates standardized data structures that form the basis for automated analytics processes.

Consulting aligned with the audit requirements

dab’s role was to translate requirements from day-to-day audit practice into executable data and analytics logic. The team contributed both technical data expertise and experience from data-driven audit and analytics projects.

SPT defined the required analyses. Based on these requirements, dab developed the scripts and preparation steps needed to implement them in ACL Analytics. This resulted in a two-stage approach: first, client-specific import scripts transform different raw data sets into a consistent starting point. A standardized materiality script is then run to perform the audit analyses on the prepared data set.

“dab supported us not only with the technical implementation, but above all with their deep understanding of data structures and analytics processes. Their ability to translate our audit requirements into a practical and sustainable solution was particularly valuable. This enabled us to automate recurring data preparation and analysis steps and make our audit processes more efficient in the long term.”

– Mag. Clemens Huber, Authorized Signatory and Certified Public Accountant at SPT

Automation where it makes a difference in day-to-day auditing

A key objective of the project was to automate recurring steps. Manual data preparation was to be reduced and replaced by scripts that can be reused in subsequent audit cycles, provided the data structures remain comparable.

For SPT, this means shifting the effort away from recurring manual data preparation towards import and preparation logic that is defined properly once. If a client supplies data in a comparable structure in the following year, the existing import script can be reused. The analysis itself remains consistent through the standardized materiality script.

Results at a glance

Greater efficiency in audit preparation
Recurring steps involved in importing and preparing different client data sets were automated, noticeably reducing the effort required for data analysis.

Consistent analyses across different clients
Despite different data structures, audit and analytics procedures can be performed using a consistent methodology. This preserves the benefits of data-driven full population analyses without relying exclusively on traditional sampling procedures.

Sustainable, reusable audit processes
Once defined, import and analytics logic can be reused in future audit cycles and makes it easier to scale data-driven audits.