In today’s fast moving digital landscape, the insurance industry is undergoing a significant transformation driven by the growing value of data. Insurers are harnessing the power of advanced analytics and big data on an unprecedented scale, they are uncovering hidden insights that are reshaping risk assessment, underwriting, and customer engagement. This surge in data-driven decision-making is enhancing operational efficiency and paving the way for more personalised and proactive insurance solutions. In this article, we will explore how the strategic use of data is revolutionising the insurance sector, creating new opportunities for growth, and delivering greater value to both insurers and policyholders.
The Insurance sector has always been a data rich industry but regulatory compliance, technology adoption, talent scarcity & big business bureaucracy represent serious challenges for incumbents seeking to invest in the power of data and analytics. In this context SMEs have been quick to take on the role of disruptive challengers (leveraging new data and analytics) or agile solution providers to larger incumbents. Our partners at Dufrain & 4most fall into the latter camp, helping to apply new technologies to deliver better data platforms and risk models for Insurance clients looking to innovate.
In this insights piece we explore 3 key developments in insurance data presenting opportunities for SMEs.
1. Hyper-Personalisation
Premiums aren’t just a function of underlying insured risk but also of competition & individual client preference. New sources of data such as IoT data for buildings, telematics and behavioural indicators can be used to assess an individual client’s underlying risk, cover needs and price sensitivity. Leveraging this data to price risk dynamically enables insurers to optimise conversion & profitability with far greater precision and improve client experience.
2. Emerging Risks Assessment
Unified Data
Many insurance businesses are data rich but insight poor. Deploying unified data to assess emerging risks opens up new insurance frontiers, often more quickly than traditional approaches where time (to see loss history) is a barrier to meeting market demand and growing insurance capacity. For example, when pricing motor insurance, electric vehicles (EVs) have limited historical records, particularly regarding battery degradation. Insurers can deploy predictive modelling in partnership with electric vehicle service providers and telematics to gain early access to data on failures, accidents and their cost.
Parametric Insurance
Another area emerging to help manage risk is parametric insurance. Unlike traditional indemnity insurance, parametric insurance offers predefined payouts triggered by specific criteria (i.e. parameters of an event, such as volume of rainfall) rather than reimbursing actual losses incurred.
Implementing this model requires robust inputs from data providers and / or sensors (e.g. measuring local water level). The proliferation of IoT devices and more sophisticated data management has allowed parametric insurance to become more precise and adaptable.
Parametric insurance has gained traction within natural catastrophe and agricultural sector.
By using binary payout triggers, parametric insurance accelerates claims resolution, reduces administrative costs, enables insurers to manage risk exposure and helps insure the otherwise uninsurable.
For example, leading specialty insurer Beazley partnered with Sola Technologies to introduce the innovative Tornado Crisis product, which uses a predefined severity index to act as a trigger for payments to be automatically generated. Sola’s premiums reflect only policyholder property risk, not claims history or personal details, with the aim of providing fairer pricing.
Geospatial Data
Many of the indices parametric insurance relies on use geospatial data and analytics in some way, however geospatial has a big role to play in traditional indemnity models too where actual losses/claims must be assessed.
Thanks to the build out of low-earth orbit (LEO) constellations, commercial sector growth and open data initiatives (e.g. NASA, ESA) geospatial data is now being much more widely applied in insurance.
Geospatial data unlocks value across a range of areas for insurers, including:
- Visualising the geographic distribution of risk
- Assessing damage more efficiently
- Identifying discrepancies in claims (i.e. fraud detection) e.g. by comparing pre- and post-event geospatial data
- Supporting capital requirement/reservation
- Identifying underserved insured areas and tailoring strategies
Where geospatial data is being applied, most commonly natural catastrophe insurance, the risk is usually out of the policyholders’ control, in other lines this may not be entirely the case…
3. Aligning Behaviour
Moral hazard is a fundamental challenge in insurance with warranties long used to align insurer & policyholder incentives, thereby reducing risk and preventing losses that might otherwise occur due to high risk behaviours or lack of best practice awareness.
The example most familiar to us as consumers involves telematics in motor insurance, offering pay-how-you-drive pricing and safe driving discounts.
Today, data-driven approaches have expanded into commercial lines too, notably within cybersecurity where maintaining specific certifications (e.g. Cyber Essentials) is often a pre-requisite for cover and compliance may be monitored on a near-live basis, for example by using outside-in external attack surface monitoring (EASM) tools.
Beyond merely incentivising better behaviour, insurers can mandate certain precautions or even bundle them with their policies…
Bundling Risk Management Tools
By procuring at scale and bundling with their policies insurers can overcome the affordability & awareness barriers that smaller businesses may encounter buying risk management tools independently. These bundles often include consultative services following an incident, aimed at increasing speed of rectification, improving outcome & reducing total loss e.g. an employment law hotline to call in advance of a contentious dismissal.
Conversely, producing policies that can be bundled and sold by the tool vendors themselves achieves a similar outcome and creates a new distribution channel for the insurer. Working with insurer AIG & broker Sutcliffe & Co, CyberSmart offers clients using their platform to achieve Cyber Essentials £100k of free cyber insurance & access to AIG’s breach response service following an incident.
Future Outlook
Data will continue to transform the insurance industry through the adoption of data & AI by both insurers and policyholder. The race to deploy these new tools at scale, harnessing new information sources, to refine underwriting, pricing models and claims is accelerating. This in turn drives improvements in capital efficiency and customer satisfaction by offering more tailored, clearly understood and responsive insurance. At Phoenix, we remain focused on backing the innovative founders & teams driving this data transformation.
