Compliance programs are a central part of an organisation's risk management strategy and underpin the overall development of an ethical and value driven culture. They seek to provide a framework to support the mitigation of identified business risks such as fraudulent activity, bribery and corruption, money laundering and conflicts of interest.

Building a robust compliance program and embedding a strong compliance culture within an organisation has never been more important. Emerging market trends, regulatory developments and the demand for greater transparency all impact the effectiveness of a compliance program. Organisations need to be able to adapt quickly to these new risks, requirements, and developments to achieve a culture of compliance and continuous improvement.

Organisations who can do this successfully are better placed to navigate emerging challenges, addressing increased regulatory scrutiny and society's need for higher standards of corporate ethics. To achieve this, many organisations are investing in Data Analytics to underpin their compliance program infrastructure, harnessing the ability to identify, investigate and prevent wrong doing in a timely manner and ensuring that they can handle these rising demands effectively.

In this article we look at how Data Analytics can be successfully used to support these objectives, with particular reference to anti-money laundering (AML) and anti-bribery and corruption (ABC) risks.

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