We offer data science, machine learning, software development and both management and actuarial consulting services to the financial services industry.
We use survival analysis and anomaly detection techniques to understand churn and fraud in your customer base.
We augment your data with intelligently sourced public datasets to gain you an edge on the competition.
We help you meet regulatory compliance and design profitable products that have better market fit & reduced risk.
We use advanced Bayesian inference and agile prototyping to test new ideas and guide new business plans.
We use a wide variety of machine learning techniques to understand, automate and improve business operations.
We help to create expert in-house capability and embed a culture of scientific data discovery and communication.
By embedding a combination of graph databases, machine learning and data visualization within Claims Investigation Units we developed a solution that prioritised claims for investigation, improved fraud detection rates.Read More
Advanced project to help model customer and broker behaviours, and help predict and improve policy persistency. We created a set of bespoke time-to-event models using traditional and Bayesian inferential methods to understand key drivers.Read More
Using open-source and freely available data science tools, we took a historical book of catastrophe-exposed commercial property insurance and assessed the segments of the market in terms of risk and profitability. In close collaboration with both the underwriting and actuarial teams, we help them set future strategic goals for that line of business.Read More
We combine domain knowledge with specialist technical skills to deliver high-impact statistical insights, predictive models and data-driven business advice.
Formerly the Head of Data & Analytics at Barnett Waddingham Michael has worked in actuarial and IT roles. He brings a business-first approach to the use of machine learning and is as well advises businesses on how to efficiently establish data science functions.
Mick is a physicist with a MSc in high performance computing and a PhD in quantitative finance. He uses techniques such as time series analysis and Bayesian methods to help insurance companies with problems that traditional actuarial approaches struggle with.
Gerard has many years’ experience building and managing technology platforms for international companies in reinsurance and insurance. He combines a passion for technology with international business experience and a pragmatic approach to getting results.
Peter's PhD is in photophysics and has Masters in both Data Mining and Distributed Computing. Peter is experienced in data engineering, warehousing & mining. He has developed anti-fraud solutions for insurance companies using machine learning tools.