Artificial Intelligence covers several different concepts, as defined in the diagram below. Machine Learning and Deep Learning are subsets that falls under the umbrella of AI and is the area we are going to focus on today.
Research by Domo, as reported by Forbes, revealed that more data on people has been collected in the last two years than in all human history – that’s thanks to 2.5 quintillion bytes of data being created every single day!
This proliferation includes raw and unstructured data across fluctuating and sometimes volatile markets, and regulatory and evolving threat landscapes. It makes ‘human’ risk assessment more difficult and time-consuming.
This is where ML can lend a much-needed hand.
Using ML with a combination of proprietary and third-party data, risk selection can be defined across different touchpoints at speed.
In some specific examples, these can cover anything from property proximity to a fire hydrant to the declining credit score of a company.
The marriage of ML capability with human instinct and experience puts the broker in a better position to make a more informed decision for their clients that is tailored to a specific risk.
Additionally, ML helps underwriters to keep up with the vast amounts of data. This gives them increased bandwidth and makes them more accessible to our partners. This leads to more time for strategic relationships.
It’s not just the underwriting process that can be enhanced by ML; it can help assist in the management of claims and in doing so, speed up the claims process, keeping clients happy!
This is because ML can shoulder the burden of traditionally time-intensive tasks such as image recognition, claim triage, validation and categorisation, and updates for clients on the progress of their existing claims.
Here at Brit, we’ve collaborated with the Geospatial Insurance Consortium to use aerial drone technology to capture location images. Combining this with ML helps make sense of the image data captured, meaning we can be "on the scene" to assess damage post a loss event without our loss-adjustors physically travelling there.
This means we can treat your clients' claims with the speed and consistency they deserve.
These are interesting times. In many ways, the future is here today, and many of us are already embracing the technology that will allow us to execute our roles more effectively and keep our clients happy. The examples we have discussed here are just the beginning. While our focus has been applying ML to enhance existing underwriting and claims services, we are aware that there are opportunities in the future for AI and ML to support the development of new products and services. Together insurers and brokers need to face the future and thrive.
Joy Ferneyhough, CXO here at Brit, summed up why everyone should be excited about the opportunities to be part of the evolution of our industry, stating “we're focused on providing the best experience for our brokers and our AI and ML strategies further enable this.” We’re at the start of using AI and ML to create the best user experience in several different areas, including;