KPMG's Forensic Data Analytics team focuses on the identification, preservation and analysis of data, which is structured and used to provide insight into risks, or to support a legal proceeding or investigation. It involves the use of technology and analytical techniques to understand patterns, trends, and anomalies within data for complex problem solving and decision-making.
Our Forensic Data Analytics specialists can assist with digital evidence analysis, fraud and misconduct detection, financial crime analytics and compliance with regulation.
We support clients in responding to litigation or regulatory enquiries, locating the right information to avoid over reporting or under reporting, and facilitating the data management process.
Unlock hidden patterns. Expose the invisible. Uncover the truth.
Learn more about how we use data analytics to prevent, detect and remediate fraud, financial crime, non-compliance and other irregularities.
KPMG's Forensic Data Analytics services
Investigations & integrity analytics
- Fraud and misconduct analytics: Implement data driven analytical controls to assist in the early detection of possible fraud and misconduct, bribery & corruption, and providing data analytics support in investigations.
- Sport integrity analytics: Advanced data analytics and visualisation techniques to perform annual salary cap reviews to monitor and detect potential non-compliance by sporting clubs. Assess and recover potential royalty underpayments from various agreements with third-parties, including examination of contract interpretations, payment calculations, discrepancy identifications and recovery methodologies.
- Forensic Foresight: Forensic Foresight is a solution aimed at helping clients undertake continuous compliance monitoring of key risk areas such as employee misconduct, bribery & corruption and trade manipulation.
Financial crime analytics
- Transaction Monitoring: Employing a data analytics driven review, we help financial institutions and other regulated entities assess performance of current transaction monitoring (TM) scenarios by analysing historical alert data and performing alert correlation analysis to identify areas for optimization.
- Customer Risk Assessments: Customer risk assessments help financial institutions use their resources more efficiently. Poorly designed CRAs might fail to identify high-risk customers, leading to wasted effort in unnecessary investigations and follow-ups.
Analytics for law firms
- Scheme administration: The administration of class action settlements requires careful consideration of the legal instructions and analysis of data to ensure fair and equitable distribution of payments to group members. We work with law firms to identify group members, verify identities via data matching, enrich group member lists to maximise participation rates, establish communication channels (including online portals), calculate payment amounts and conduct ad hoc analytics to support the case.
- Class action analytics: Modelling of various case outcomes in support of legal cases, including the identification of group members and potential loss quantification based on share registry data.
Remediation analytics
- Customer Remediation analytics: Address complex remediation matters with regulatory scrutiny, including identification of the impacted customer cohort, calculation of the quantum of impact over time and identification who to pay and how to pay.
- KPMG ThinkPay and other payroll analytics: Data driven approach to identification and correction of irregularities in employment obligations, including wages, long service leave, termination payments and other entitlements. Working with employment specialists in KPMG, our services include AI-enabled timesheet transcription, wage theft vulnerability reviews, payroll process optimisation, remediation calculations, data driven employee contacts, remediation portals and ongoing monitoring support.
Why choose KPMG?
Analysing large data sets can reveal valuable trends, but without expert interpretation, organisations might miss insights into business risks.
A seasoned data analytics team with experience in investigations, financial crime analysis, customer remediation, and dispute quantification can identify key data points and offer deeper insights.
