Photo in a bustling open-plan corporate office with multiple busy workspaces in the soft-focused background. In the foreground, a team of data scientists and a senior partner collaborate around a large glass-topped table, actively analyzing complex data science and AI models, graphs, and dashboard metrics on multiple laptop screens and a large interactive wall display.

Data Strategy and Data Science

Establishing robust data strategy frameworks and applying predictive modelling to enhance analytical capabilities and drive commercial profitability.

Establishing robust enterprise data strategy and governance frameworks to ensure high-quality data pipelines for campaign execution, data science and actuarial modelling.

Applying predictive modelling to support customer segmentation, net present value (NPV) calculations, contact optimisation and persistency analysis, embedding these insights into, acturial rating, commercial targeting and product design.

Enhancing analytical capabilities to deliver measurable profitability improvements, including turning underperforming portfolios around from an internal rate of return (IRR) of -5% to +18% through strategic segmentation and tailored servicing models.

Delivering demonstrable ROI by using behavioural analytics at the digital point of sale to identify and filter fraudulent online applicants, reducing client claims loss ratios by 10%.

Improving visibility across the customer journey through single customer view (SCV) architectures, web analytics and omnichannel attribution models that underpin high-performance, data-driven marketing strategies.