Anomaly Detection Systems are built to identify and measure the root cause of error, abuse, fraud and waste. Anomaly detection also referred to as outlier or novelty detection, identifies events or observations that deviate significantly from the expected result, or a majority of the data, or do not conform to a well-defined notion of normal behaviour. These are often identified as behavioural events of error, waste, abuse, or fraud.
Industries that rely on third parties to deliver complex services to end-users, ranging from health services, education, wealth management, capital markets and taxation services to franchise operations.
This environment is susceptible to error, waste, abuse, and fraud as the service deliverer, or intermediary, behave in a way inconsistent with the organisation’s intention and expectations.
Download the PDF version for 7 guiding principles for anomaly detection systems.
When designing an anomaly detection system, some guiding principles, or strategic drivers, of the design and implementation are:
About RoZetta Technology
RoZetta Technology’s core belief is that fusing data science, technology, and data management is the path that amplifies human experience and knowledge. Anomaly Detection is one of the many SaaS and managed service offerings we deliver for organisations that deal with large volumes of data.
RoZetta’s clients have an understanding of the challenges they face. RoZetta brings proven capability, experience and a mindset to create products and systems that resolve these challenges in a way that optimises the value created.
The mix of good data, the right technology, the right design and the right team can solve complex problems.