I have worked in the insurance industry for over 20 years, specialising in personal property and high net worth insurance. I worked at AIG from 2000 to 2016 and during my time there I experienced working in many markets through global and EMEA managerial roles, managing teams of pricing actuaries and portfolio analysts.
These roles straddled mature and emerging markets, on multiple systems that came with varying degrees of usable, clean data. During these roles my focus was always on providing consistency in reporting and analytics and finding the highest quality and most useful data for the business. Ultimately, the aim was to drive differentiation in the insurance pricing and product, thereby achieving profitable growth.
I am enthusiastic about data, the insights you can find and the stories it can tell. I am passionate about driving a data first mindset through all areas of the business to maximise insight and future proof scalability.
These lessons have been carried forward to my current role at Azur, a fast paced insurtech environment which works, thinks and acts in an agile way. Our aim is to have one version of the truth with all the data in one real-time system.
It has been partnering with a data science company to implement an underwriting tool centred on enriched data, allowing real-time pricing and risk management.
Data is collected at the time of quote and fed into three algorithms which provide two scores; the likelihood to convert and the propensity to claim. This has obvious benefits as it both retains the human understanding offered by the underwriter and allows them to make better decisions at the risk selection stage, as the algorithm helps to remove cognitive bias. In essence, it is augmented underwriting using explainable AI, which will result in tilting the portfolio to better performing risks and improved loss ratio.
I am passionate about women in business and two very inspirational female leaders within the insurance industry are Inga Beale, the former CEO of Lloyd’s of London, and Sian Fisher, CEO of the Chartered Insurance Institute (CII). In a very male dominated industry, they epitomise female confidence and the potential to succeed.
2019 was a great success for Azur with the launch of a new product on our tech stack. Data is key and by engaging with multiple data enrichment partners, we have created short form underwriting and end to end processing, providing simplicity for customers and real-time analytics for capital providers without compromising the rating variables. Another big win for my year was the launch of augmented underwriting, made possible with the implementation of explainable AI.
I expect there to be continued focus on data ethics, not just within machine learning and algorithms but also in overall data use. There are many areas to consider and more frameworks will be created by companies outlining their data lineage, data control, transparency and conduct risk. This will help to mitigate the moral implications that can occur from homogeneity, moral bias, lack of diversity or unintended consequences in data use.
The speed of change is going to result in a wholesale upskilling of labour as people are replaced in less value-added tasks by machines. Far from being an apocalyptic event, and as has happened with all technological advances from the Industrial Revolution onwards, this will allow workers to perform further up the value chain and create more leisure and lifestyle opportunities. Data lies at the very heart of this positive societal change.
Digitisation is impossible without data, however, data is a continuous work-in-progress, requiring constant refining and updating. Staying on top of this in a fast-moving environment and trying to improve the hit rate for data enrichment, remains a constant challenge, especially with so many players coming from so many different angles.
There is a natural tension between keeping data at the heart of the journey and speed of delivery. There are often many levers to pull to launch a product efficiently and effectively and this could be at the detriment of putting the data first. Taking key stakeholders on the journey is the key to success.