Big Data Working Group
Focus on Big Data – Afternoon Working Goup: 29 May 2015
According to the Association of Certified Fraud Examiners, almost 50% of fraud and corruption is detected by tip-offs or by accident, while only 14% is detected by internal audit. Why is this? With many high-risk transactions involving schemes designed to circumvent existing rules, traditional tests are typically not as effective for identifying those transactions. For bribery and corruption, new approaches to data analytics are needed that integrate statistical analysis, anomaly detection, data visualisation and text mining. This session will look at utilising sophisticated anti-bribery and corruption (ABC) analytics to enhance your risk assessment and monitoring processes, helping you to increase the overall efficiency and effectiveness of your anti-corruption programme and compliance initiatives.
- The latest ABC analytics tools at your disposal
- Analysing emails to detect anomalous relationships
- Leveraging text mining to identify potentially suspicious terms within transactions
in the financial accounting data
- Utilising visualisation tools to identify key risk areas on which to focus
- Monitoring tools and statistical techniques to identify data trends and potential
- Understanding the business challenges to improve ABC compliance
- Effective use of technology and ABC analytics improve your compliance programme
- ABC case studies
Today, a technology enabled strategy using data analytics should be the cornerstone of your compliance program. Companies need to proactively monitor an exponentially growing number of transactions to ensure compliance with policies. Monitoring enables a company to understand the effectiveness of its anti-corruption compliance program and where future efforts should focus to minimize risks. It can, however, be a challenge to determine what tools and techniques to use, what to test and measure, how to actually do it, how often to do it, and how to report the results in a way that stimulates action rather than fosters bureaucracy.
This interactive session will discuss:
- What a data-drive strategy will actually achieve.
- How to design and deliver a proactive, risk-based audit programme centred on automated data analytics processes in your organization.
- What detection programme strategies are better practices for your industry?
- How to manage the results – all of the red flags and potential false positive results
- How to cater for multiple languages in your data.
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