We combine specialist technical expertise and rich industry experience to deliver a true data science consulting service to leaders in the insurance sector. We help our clients learn from data and capitalise upon new insights gained from advanced statistical analyses.
Expand your market and reach the right audience for your products. We discover and combine data sources from inside and outside your organisation, and use leading algorithmic tools & techniques to identify, learn and predict patterns of behaviour.
Meet regulatory compliance and design profitable products that have better market fit & reduced risk. We use Bayesian statistics and agile prototyping to create reliable scenario models that automatically become more accurate with more information.
Create great teams and embed a culture to discover and communicate insights that lead to real change throughout your organisation. We have experience bringing together managers, academics & developers to use data science effectively and sustainably.
We have been fortunate to work with several interesting and progressive organisations particularly in life insurance; which, fittingly, in the mid-1700's became one of the first industries to ever apply statistics to daily business. Click images to request a case study.
Greenfield project to provide insight into customers past, present & future. We fused high-dimensional demographics with internal data and used unsupervised clustering & survival modelling to categorise customers and evaluate credit risk.
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.
Exploratory project to find non-invasive insights into the communication patterns between the client, customers and brokers. We mined large textual datasets, using advanced natural language processing and lightweight interactive dashboarding.
We are a small but experienced team with expertise in data science, software development, financial systems and interface design. Our wide network of strategic alliances allows us to bring in complimentary capabilities to specific projects.
Jon has over ten years experience providing trusted advice and actionable insights to senior audiences in insurance, telco and retail in Europe & USA. Commercially minded, trained in physics and machine learning, he also volunteers within data-for-good social movements, and speaks at tech and industry events.
Michael trained as an actuary and has over twenty years experience designing, developing and managing bespoke IT solutions for a broad range of financial companies throughout Europe. He understands the complexities of IT-enabled change and brings a wealth of actuarial, financial and practical expertise.
Michael is highly experienced in probabilistic programming and financial modelling for derivatives analysis and volatility trading. His backgrounds in stochastic and high performance computing, theoretical physics and as organiser of technical user groups ensure a great scientific and academic strength within the team.
Jonathan is an experienced software developer and applied mathematician with a background in novel machine learning systems. He joins us as an associate on specific projects, where as published researcher, lecturer and university fellow, he brings an academic rigor to his approach.
Ken is a data scientist and innovator with experience in software development and machine learning. As an associate on specific projects he brings particular expertise in entrepreneurship and text mining, having previously founded and lead a successful startup in sentiment analysis.
We're growing quickly and always happy to hear from experienced statisticians and software developers looking for new challenges in the UK, Ireland and throughout Europe. Recruiters please contact via email only.
Applied AI Ltd is a limited company registered in England and Wales #08609649 152 City Road, London, EC1V 2NX, UK Applied AI Ltd © 2013 - 2016