Anomaly detection and risk analytics
Identify unusual patterns, detect outliers, rank cases for review, and support fraud or operational risk workflows.
MLS Analytics helps organisations turn complex data into practical insight through machine learning, statistical modelling, anomaly detection, forecasting, and decision support.
Founded by a consultant with a joint PhD in Mathematical Statistics from Stellenbosch University and Bioscience Engineering: Mathematical Modelling from Ghent University.
That combination brings together rigorous statistical thinking, mathematical modelling, and modern machine learning, with a focus on solving applied business problems clearly and professionally.
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Built for organisations that need rigorous quantitative thinking, not just dashboards.
Identify unusual patterns, detect outliers, rank cases for review, and support fraud or operational risk workflows.
Develop classification, regression, and forecasting models aligned with operational goals and business constraints.
Design sound analyses, compare alternatives, quantify uncertainty, and improve decision quality with robust inference.
Build bespoke models and analytic pipelines for domain-specific problems where off-the-shelf solutions fall short.
Translate complex model outputs into prioritisation, monitoring, and decision systems stakeholders can actually use.
Review existing modelling pipelines, evaluate methodology, and strengthen analytic strategy for teams and organisations.
MLS Analytics is designed for clients who want the depth of an advanced quantitative specialist with the clarity and responsiveness of an independent consultant.
The focus is on building solutions that are technically sound, well explained, and useful in practice, especially when data are messy, noisy, high-dimensional, or operationally complex.
Insurance, finance, healthcare analytics, industrial modelling, operational analytics, forecasting, and technically demanding decision problems.
Use these cards now as examples, then replace them later with your real case studies, dashboards, or project screenshots.
A demonstration project showing how machine learning and statistical scoring can be combined to prioritise unusual cases for review.
Show how statistical forecasting and machine learning can help plan inventory, staffing, budgeting, or risk reserves.
Illustrate how a scoring model or optimisation routine can improve prioritisation, triage, or resource allocation.
Whether the need is a one-off modelling project, an advisory review, or a longer analytics engagement, MLS Analytics is built to deliver focused expertise without unnecessary complexity.
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Cape Town, South Africa
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