ESG Fraud Analytics
Your expert for questions
Christina Pellegrino
Director, Forensic Services at PwC Germany
Tel: +49 160 97254402
Email
We use data analysis to get to the bottom of ESG fraud
Data can provide invaluable insights into the background of ESG fraud and its causes. Using targeted analyses, which rely on both classic pattern recognition and complex AI-based algorithms, we support you in evaluating potential fraudulent behaviour as well as in conducting ESG Fraud Investigations. For each incident, we select the appropriate analysis procedures from our toolbox and customise them to the specific requirements, available data sources and the IT landscape. We combine internal company data with publicly available information to facilitate a comprehensive analysis.
Four steps for effective ESG fraud data analytics
Step 1: Examine the IT landscape and select internal data sources
All IT systems used within an organization can potentially be relevant for an ESG Fraud analysis. In the first step, we work with you to select the specific data sources that are to be used for the planned analysis. In particular, information from internal (ESG) risk management and scoring tools is ideally suited for this purpose as well as information obtained from systems related to accounting and business partner management (e.g., ERP systems, compliance risk management systems).
Step 2: Merge and harmonise internal and external data sources
Apart from the identified internal data sources, we also use publicly available information such as media reports and sanctions lists, as well as PwC ESG benchmarks and ESG fraud patterns as the basis for our analyses.
Our PwC data extraction and data processing tools allow for an efficient data acquisition and data processing, even of large and complex data volumes, which facilitates a successful data analysis process.
Step 3: Determine the type of data analyses
Depending on the needs and available datasets, we compile an analysis program from our extensive toolbox based on our experience in (ESG) fraud analyses. We then execute the selected analysis program using the previously harmonised database.
Step 4: Create reports and visualise results
We present the obtained analysis results, together with the harmonised data sets, in interactive dashboards. This allows transparent, direct, and detailed communication of KPIs and analysis results to all stakeholders.
We provide the following analysis to you
- Red-Flag Analysis
- Outlier Detection
- ESG KPI Benchmarks
- ESG Screening
- Anomaly Detection
- Interface Validation
Red-Flag Analysis
Using predefined criteria, we identify known ESG fraud patterns. The Red Flag Check provides a transparent overview of warning signals and deal breakers in the context of transactions.
Outlier Detection
By clustering selected transactions, we uncover outliers in ESG-relevant calculations, which are typically hard to detect with other analysis methods.
ESG KPI Benchmarks
Comparing ESG metrics with benchmarks from same-industry peer groups is another way of identifying discrepancies pointing to ESG fraud.
ESG Screening
Business partners committing ESG fraud can pose a high risk for your organization. By performing a targeted screening, we ensure that there are no known "ESG fraudsters" among your business partners.
Anomaly Detection
Anomaly detection algorithms can uncover previously unknown ESG fraud patterns. We select appropriate anomaly detection methods and apply them to the complete data set to perform a comprehensive analysis.
Interface Validation
To ensure a correct data exchange of the relevant ESG criteria, we validate the functional reliability of interfaces between accounting, risk management systems and ESG scoring tools.
“Data analyses ensure the reliability of ESG reporting.”
Related content
Follow us
Contact us
