Forensic Data Analytics

Quickly identify patterns and anomalies


Forensic Data Analytics

Anti-fraud and Financial Crime - Data Mining, Trend Analysis and Outlier Detection
IT and Systems Controls Assessment - Risk-based Transaction Monitoring


Our forensic investigators are also data scientists experienced in database programming and data mining. We tailor technology to the nuances of your case, to review and analyse structured and unstructured data on large, complex and high-profile investigations.


Finding compliance risks

Our data analytics team is well versed in gathering, analysing and culling voluminous transactional data from complex IT systems. We prioritise for further review the findings that present the highest compliance risks.

This non-linear risk-based approach increases review effectiveness and optimises resource allocation. Issues identified from parallel workstreams such as internal controls review and risk assessments are incorporated iteratively to increase the precision and accuracy of the analytics.

We use visualisation tools to communicate key findings to help our clients quickly identify patterns and anomalies that require special review and additional interrogation.

Anti-fraud and financial crime

Facing an unexpected investigation, it can be a daunting task for global organisations and counsel to quickly identify key sources of data for review and analysis. Our technical investigation team has conducted numerous IT interviews and is familiar with enterprise resource planning systems.

We help you confidently narrow the investigative focus by identifying the core repositories of relevant data.

Our team follows established forensic protocols to extract and preserve data from IT systems while minimising interruption to business critical operations.

Data mining, trend analysis and outlier detection

An effective and thorough investigation requires a comprehensive side-by-side review of all critical information. However, electronic evidence is often stored in disparate data sources, complicating efforts to recognise hidden relationships and reconcile transaction flow between systems.

Our data analytics team helps you overcome these challenges by mapping and linking data relationships to establish a centralised information repository, so that investigators can holistically review information and perform comparative analyses to look for patterns and outliers.

IT and systems controls assessment

A typical investigation includes conducting interviews, performing financial walkthroughs and reviewing internal controls, policies and procedures. Part of this effort requires evaluating if the enacted policies and procedures are correctly reflected and coded in the corporation’s IT systems.

Our data analytics team blends technological expertise with experience in compliance and fraud investigation, allowing them to effectively examine and assess IT system control and protocols. We inspect end-to-end data flows and system processes to test compliance effectiveness and identify gaps for remediation.

Risk-based transaction monitoring

Our data analysts and technologists use statistical algorithms and machine-learning techniques to model, forecast and quantify risk. Using historical data, we look for patterns that indicate fraud and help corporations with early detection, prevention and remediation of reputational risk. We leverage rule-based algorithms to quickly cull down large amounts of information and flag high risk transactions for review and testing.


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Our thinking

In Focus series

In Focus

Fighting doping in ice hockey

Join Jonathan Brown, Partner, and Alecia Futerman, Associate Director, from Control Risks' forensics team for a discussion with Ashley Ehlert, the Legal Director for the International Ice Hockey Federation.
The digital transformation of the sescurity function


The digital transformation of the security function

As part of their drive to introduce technology into security risk management, many corporate security teams are assessing internal and external technology options to help them improve their ability to collect data, process information and generate and disseminate intelligence to support faster and more accurate decision-making.