View source for Definition:Real-time data

📡 '''Real-time data''' is information that is captured, transmitted, and made available for analysis or decision-making at the moment it is generated, with no meaningful lag between the event and its reflection in an insurer's systems. In the insurance industry, this encompasses everything from [[Definition:Telematics | telematics]] feeds streaming driving behavior, to [[Definition:Internet of Things (IoT) | IoT]] sensors reporting water leaks in commercial buildings, to live [[Definition:Catastrophe modeling | catastrophe model]] outputs tracking an approaching hurricane's impact on an insurer's [[Definition:Aggregate exposure | aggregate exposure]].

🔗 Operationally, real-time data flows through [[Definition:Application programming interface (API) | API]]-connected architectures that link [[Definition:Policyholder | policyholders]], [[Definition:Insurance broker | brokers]], [[Definition:Managing general agent (MGA) | MGAs]], [[Definition:Insurance carrier | carriers]], and [[Definition:Third-party administrator (TPA) | third-party administrators]] into a shared information layer. In [[Definition:Usage-based insurance (UBI) | usage-based insurance]], a driver's speed, braking patterns, and mileage stream directly into a [[Definition:Pricing model | pricing engine]] that adjusts [[Definition:Insurance premium | premiums]] dynamically. In [[Definition:Commercial property insurance | commercial property]], smart-building sensors can alert a carrier's [[Definition:Loss control | loss control]] team the instant environmental conditions exceed safe thresholds — potentially preventing a [[Definition:Claim | claim]] before damage occurs. [[Definition:Parametric insurance | Parametric insurance]] products depend entirely on real-time data feeds from third-party sources like weather stations or seismic monitors to trigger automatic [[Definition:Claims payment | payouts]].

📊 Harnessing real-time data fundamentally changes how risk is understood, priced, and managed. Rather than relying on historical [[Definition:Loss experience | loss experience]] compiled over months or years, [[Definition:Underwriter | underwriters]] and [[Definition:Actuary | actuaries]] gain a living picture of risk as it evolves. This granularity supports tighter [[Definition:Loss ratio (L/R) | loss ratios]], more responsive [[Definition:Reinsurance | reinsurance]] purchasing, and better customer engagement through proactive risk mitigation. However, it also raises significant questions around [[Definition:Data privacy | data privacy]], [[Definition:Regulatory compliance | regulatory compliance]], and the infrastructure investment required to ingest and act on continuous data streams at scale.

'''Related concepts'''
{{Div col|colwidth=20em}}
* [[Definition:Internet of Things (IoT)]]
* [[Definition:Telematics]]
* [[Definition:Usage-based insurance (UBI)]]
* [[Definition:Parametric insurance]]
* [[Definition:Catastrophe modeling]]
* [[Definition:Real-time]]
{{Div col end}}