Reference
Insurance Technology Glossary
Plain-English definitions of the terms that come up when carriers, MGAs, brokers, and engineers work on the same project. Written for mixed business-and-technical teams; free to reference and link.
Market roles & distribution
- Carrier
- The insurance company that underwrites and issues policies, holds the risk, and pays claims. Carriers run the core systems — policy administration, claims, billing — that most insurance technology work revolves around.
- MGA (Managing General Agent)
- A specialized intermediary with delegated authority from a carrier to underwrite, bind, and sometimes handle claims for specific programs. MGAs typically need lighter, faster technology than carriers because they operate on delegated authority with lean teams.
- Broker
- A licensed intermediary who represents the insurance buyer, shopping risks to multiple carriers or wholesalers. Broker workflows center on submissions, quoting, and placement.
- Wholesaler
- A broker's broker — an intermediary that places hard-to-write risks with specialty or surplus-lines markets. Wholesalers often re-key the same submission into many carrier systems, which is why data re-entry elimination is a common modernization project. Case study: 90% less re-entry
- Producer
- Any licensed individual or firm that sells insurance — agents and brokers collectively. Producer management systems track licensing, appointments, hierarchies, and commissions.
- Commercial lines
- Insurance sold to businesses (general liability, commercial property, workers' comp) as opposed to personal lines (auto, home). Commercial-lines workflows are more bespoke, which drives heavier submission and underwriting tooling.
- Surplus lines (E&S)
- Excess & surplus insurance for risks standard carriers decline, written by non-admitted insurers with more rate/form freedom. E&S growth is a major driver of MGA and wholesaler technology demand.
Underwriting & submissions
- Submission
- The package of applicant information a broker sends to an underwriter to request a quote — applications, loss runs, statements of value. Submission quality and completeness determine underwriting speed. Underwriting Accelerator
- Submission intake
- The process (increasingly automated) of receiving, extracting, normalizing, and triaging submissions from email and portals into structured data an underwriting workbench can use.
- Underwriting workbench
- A single workspace where underwriters see triaged submissions, risk data, prior history, and third-party enrichment, and record decisions — replacing spreadsheet-and-inbox underwriting.
- Risk appetite
- The classes, sizes, and geographies of risk a carrier or MGA wants to write. Appetite rules encoded in software let submissions be auto-declined or prioritized before an underwriter touches them.
- Loss run
- A report of an insured's historical claims, used in underwriting. Parsing loss runs from PDFs into structured data is one of the most common insurance document-AI use cases.
- Rater
- A tool (often spreadsheet-based, increasingly a service) that calculates premium from risk characteristics and rating algorithms. Replacing fragile spreadsheet raters with governed rating services is a frequent modernization step.
Claims
- FNOL (First Notice of Loss)
- The initial report that a loss occurred — the front door of the claims process. FNOL automation (structured intake, instant acknowledgment, smart routing) is where claims modernization usually starts. Claims Accelerator
- Claims triage / routing
- Deciding where each new claim goes: straight-through processing for simple claims, senior adjusters for complex ones, SIU referral for suspicious ones. Good routing shortens cycle time and reduces leakage.
- Claims leakage
- Money paid out beyond what a claim should have cost — from missed subrogation, over-payment, fraud, or process failure. Leakage reduction is a primary ROI measure for claims technology.
- Cycle time
- Elapsed time from FNOL to claim resolution. A core claims KPI: automation of intake, routing, and vendor coordination is aimed squarely at cutting it.
- Subrogation
- Recovering claim costs from the third party actually at fault. Missed subrogation opportunities are a classic source of leakage that analytics can surface.
- SIU (Special Investigations Unit)
- The team that investigates suspected fraud. Fraud-signal models flag claims for SIU review rather than deciding outcomes automatically.
Systems & integration
- AMS (Agency Management System)
- The system of record for agencies and brokers — clients, policies, carriers, commissions. Applied Epic is a widely used example; AMS integration is central to broker-side automation.
- Legacy modernization
- Incrementally replacing or wrapping aging core systems (mainframes, old .NET, spreadsheet processes) with maintainable, integrable software — usually via APIs and strangler patterns rather than risky big-bang rewrites. Modernization capabilities
- Straight-through processing (STP)
- Handling a transaction end-to-end with no human touch — a bound policy or paid claim that never hits a work queue. STP rate is a headline automation metric.
- ACORD forms
- Standardized insurance data forms (applications, certificates) maintained by ACORD. Extracting structured data from ACORD forms is a staple of submission-intake automation.
- TMS (Transportation Management System)
- Logistics software for planning and executing freight movement. Adjacent to insurance in commercial fleets and cargo; an example of the logistics systems Advancio has scaled engineering teams for. TMS case study
Delivery & compliance
- Staff augmentation
- An engagement model where external engineers join your team under your direction, adding capacity without hiring. Contrast with a managed team, where the vendor owns delivery. Engagement models
- Nearshore
- Locating engineering teams in nearby time zones (e.g., Mexico for US clients) so working hours overlap — real-time collaboration without onshore cost structures.
- SOC 2 Type II
- An independent audit attesting that a service organization's security controls operated effectively over a period of months — table stakes for vendors handling insurance data.
- RBAC (Role-Based Access Control)
- Granting system permissions by role rather than per person — the baseline access-control model auditors expect in insurance systems.
- Explainable AI
- AI/ML models whose decisions can be understood and justified to underwriters, adjusters, and regulators — a practical requirement in a regulated industry, favoring transparent models and clear feature attribution over black boxes. Data & AI capabilities
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