By Alistair Moodie, Chief Product Officer, SAMP Risk
For London Market underwriters, specialist brokers and MGAs active in renewable energy, plant risk is increasingly difficult to capture through traditional annual surveys alone. Generation assets are becoming more distributed, technology is evolving quickly, and operational performance can change materially between renewal dates. Yet much of the data needed to understand that risk already exists on site.
The challenge is not simply data availability. It is translating operational signals into a form that can support risk selection, technical pricing, capacity deployment and portfolio management in a specialist market.
Most renewable energy sites already generate three separate streams of risk information: periodic inspections, real-time SCADA (Supervisory Control and Data Acquisition) feeds, and day-to-day management indicators. Each is typically owned by different teams, refreshed on different cadences and expressed in different language. An engineer’s “high-risk” component and a London Market underwriter’s “high-risk” placement are not always the same thing. As such, underwriting decisions can remain anchored to a point-in-time view from an annual site or desktop survey, that may already be out of date.
For a sector that depends on reliable output, lender confidence and sufficient insurance capacity, that disconnect is becoming more expensive.
Why actuaries need a live view of asset health
The relevant data streams to underwrite these risks based on ‘live’ data already exist. So the task is to combine them into a consistent risk measure that can be understood by asset operators, insurers and capital providers.
SAMP Risk developed the Plant Health Index to do this: a single score out of 100, refreshed continuously, built from technical risk (probability of failure multiplied by consequence of failure, by component) and a behavioural modifier that reflects how actively a site is managing those risks day to day.
For actuarial teams supporting specialist energy portfolios, the value of that single score lies in its traceability. Each movement can be linked back to a component, a finding or a recommended action. When a score moves from 78 to 74, the platform does not simply report deterioration; it explains the driver. In a connected London Market model, that explanation can feed directly into risk assessment and underwriting dialogue, rather than remaining an operational note outside the placement process.
Visibility changes behaviour
The most important effect is not the score itself, but the behavioural change that follows when risk is visible, measurable and connected to insurance outcomes. Where operational teams can see which actions affect their risk position, and where brokers, MGAs and capacity providers can see the same evidence, there is an obvious incentive to deal with any issues flagged earlier. In deployments to date, investigation detail on unplanned events improved by 61 percentage points within five months, half of all risk recommendations were closed early rather than deferred to renewal. The risk of a major outage fell by 14% within four months.
In one case, a risk that was invisible to SCADA and missed in routine maintenance review was flagged before it could develop into a significant unplanned outage. In another, the algorithms identified a problem that was undetected by the OEM’s condition monitoring system. Manual inspection confirmed the finding and the unit was replaced before failure – and an insurance claim.
A common risk language for engineering and underwriting
For London Market participants, the practical benefit is a shared language between engineering evidence, broking submissions, MGA underwriting appetite and capacity-provider judgement. A continuously updated score can support more informed discussions about terms, deductibles, risk improvements and premium adequacy. It also allows specialist underwriters to distinguish between assets that may look similar in an annual survey but are managed very differently in practice.
That distinction has balance-sheet consequences beyond the insurance premium itself. If lenders, brokers, MGAs and capacity providers have stronger evidence of how business interruption risk is being managed, reserve requirements and working capital constraints can be reconsidered. In some cases, reducing the reserve period required against business interruption risk has released millions in working capital on individual sites. The key point for the specialist energy insurance chain is that incentives are funded by demonstrated risk reduction, not by goodwill or retrospective negotiation at renewal.
Implications for actuarial pricing and specialist portfolio management
The experience across live energy sites in the United States and South Africa suggests that the raw material for better reliability and better-priced risk transfer is already present. The opportunity is to turn fragmented operational data into a structured measure that supports technical pricing, exposure management, claims prevention and portfolio steering for specialist renewable energy facilities.
Renewable energy underwriting cannot rely indefinitely on static snapshots when underlying exposure is changing continuously. As live risk data becomes more credible, auditable and connected to insurance outcomes, it can help move renewable energy insurance towards a more responsive specialist model: one where risk is not only priced at renewal, but actively measured, managed and improved throughout the policy period.
