Blog

Tom’s Thoughts – Ethics and Machine Learning

2023-01-13T14:03:12+00:00January 13th, 2023|Blog|

Ethics

Ethics is not a new phenomenon to the human race. Philsophers have struggled for centuries to try and form a framework where “good” and “bad” are defined ideas, fixed and abstracted from the personal opinions of the reader and the mores of the society. Most ethicists now consider those attempts at […]

The Art of the Possible – Tom Murphy

2023-01-06T12:22:17+00:00January 6th, 2023|Blog|

The art of the possible…

As automation ramps up and aggregators grow, consumers are looking for quick insurance covers. Automated risk selection is required, but traditional computer programming is not up to the task.

For years the insurance industry has tried to describe what a good risk looks like. We make our best attempt at it […]

AI in action

2022-08-31T09:43:16+00:00August 30th, 2022|Blog|

AI in action: MLPrograms analyses risks for the insurance industry

Developments in AI are moving fast and the potential is huge. But how exactly is AI applied in practice? Start-up MLPrograms uses modern Machine Learning methods to estimate the risks of insurance more efficiently and accurately.

The assessment of risks by […]

Tom’s Thoughts – Data Science run down for August

2022-08-04T09:35:51+00:00August 1st, 2022|Blog|

The latest news about AI/ML within in the insurance industry from our CTO Tom Murphy

Damaged Goods?

Automotive News Europe has a good piece on the general application of AI in the General Insurance value chain. One word of warning from MLPrograms though, there are serious questions over the accuracy of damage […]

Substance over Style

2021-10-01T08:30:21+00:00September 30th, 2021|Blog|

Machine learning has been around for a while and is widely used from YouTube hobbyists to the Silicon Valley tech giants. However, the adoption of applied AI in the insurance community is still very much in its infancy. In this article, MLP’s head of product James Parry looks at how the industry can make use of machine learning tools and, more importantly, how to pick the right tools for the job.