Analytics is the discovery, interpretation, and communication of meaningful patterns in data. While analytics has been widely used in sales and marketing, it has not been extensively used in fraud discovery and internal audit.
At the same time Analytics is often misused. Calculations in spreadsheet are also considered “Analytics”. We need to differentiate between Analytics and Analysis.
Analytics involves extensive use of mathematics and statistics. Oft repeated phrase “Data is the new oil” is actually true. The insights from data provide actionable intelligence in context of fraud and suspicious transactions.
Huge amount of data available within the organization
Multiple sources of data within and outside organization
Data available in social media
Data available with government and other third party sites
Data is often unstructured to be used effectively
How can we help
Extensive audit and assurance reviews of ERP and other packages
Link various datasources for meaningful interpretation
Read unstructured data
Use Machine Learning to interpret large volumes of data
Analyze huge volumes of data for fraud discovery and internal audit
Develop scripts for data analytics using various tools like ACL, Idea
Develop scripts using open source technology such as Python, R etc.
Use advanced analytics for:
- Fraud Discovery
- Anomalies and suspicious transactions
- Spend analytics
- Logistics fraud
- Predict customer default
- Perform internal audit
- Process efficiencies
- Automate internal audit