What are Microservices in Insurance?

Microservices are a way of building software as a set of small, separate services, each responsible for one job and communicating through APIs. In an insurance system, rating, documents, billing and claims might each run as their own service instead of as one large application.

This guide is for insurance operations, IT and product teams. It explains microservices in insurance terms, how they compare with monolithic systems, how they relate to APIs and events, what they cost to run and what a buyer of a policy administration system needs to know about them.

What microservices are, in plain terms

The term was set out by James Lewis and Martin Fowler in a 2014 article describing microservices as an approach to developing a single application as a suite of small services, each running in its own process and communicating through lightweight mechanisms. Each service can be built, changed and deployed on its own.

An insurance comparison helps. Think of a traditional insurer where one department handled everything: quoting, issuing documents, collecting premium and paying claims, all sharing one set of files. A microservices system is closer to an insurer organised into specialist teams. The pricing team prices, the documents team produces documents and the claims team handles claims. Each team has its own records and its own way of working, and they communicate through agreed forms. A change in how the documents team works does not require the pricing team to change.

Each microservice owns one business capability and, usually, its own data. A rating service holds rating tables and returns premiums. A document service holds templates and produces documents. Other services ask them for what they need through their APIs.

Monolithic versus microservices architecture, with an insurance example

A monolithic system is built and deployed as a single unit. Lewis and Fowler describe a monolith as an application built as a single unit in which change cycles are tied together, so a change to one small part means rebuilding and redeploying the whole application. Most legacy policy administration systems are monoliths: rating, policy records, documents, billing and claims are parts of one program sharing one database.

Take an MGA that needs to change the wording on one product's schedule. In a monolith, that change sits in the same code base as everything else, so it goes through the full release cycle and the full regression test, and the whole system is redeployed. If the release goes wrong, quoting, billing and claims can all be affected at once.

In a microservices system, the same MGA's platform might run rating, documents, billing and claims as separate services. The schedule change touches only the document service. That service is tested and released on its own, and the rating, billing and claims services carry on unchanged. If the release fails, documents are affected and the rest of the system keeps working.

Monoliths have real strengths. They are simpler to build, test and run, data is in one place and transactions that touch several functions, such as binding a policy, raising the invoice and issuing documents in one step, are straightforward. Many successful systems are monoliths, and some are designed as modular monoliths, with clear internal boundaries but a single deployment.

What microservices change for insurers

Independent updates are the first change. Because each service can be released separately, a vendor or in-house team can update one capability without touching the others. In insurance terms, a change to claims workflow does not have to wait for the next full release of the policy system.

Scaling busy services is the second. Load in insurance is uneven. A price comparison site can send thousands of quote requests an hour while policy issuance and claims see a fraction of that. Microservices let the rating service scale up to meet quote volumes without scaling every other part of the system, which matters when hosting is paid by usage.

Replacing one component without replacing everything is the third. If an insurer wants to swap its document production tool or add a specialist fraud scoring service, the change is confined to one service and its connections. In a monolith, replacing a component can mean changing the core system itself.

Microservices, APIs and event-driven architecture: how they fit together

Microservices talk to each other in two main ways. The first is through APIs: one service sends a request and waits for a response. When a broker asks for a quote, the quote service calls the rating service's API, receives a premium and returns it to the broker.

The second is through events. An event is a record that something has happened: a policy was bound, a payment failed or a claim was registered. In an event-driven architecture, a service announces the event and any service interested in it reacts. When a policy is bound, the billing service creates the instalment plan, the document service produces the schedule and the reporting service adds the policy to the next bordereau, all without the policy service having to call each of them in turn.

Events are also how external systems can be kept up to date. A CRM or a capacity provider's reporting system can subscribe to policy and claims events and receive updates as they happen, which removes the need for nightly files or repeated requests.

The two are complementary. APIs suit requests that need an immediate answer, such as a quote. Events suit actions that several services need to know about, such as a bind.

Trade-offs: complexity, monitoring and the need for strong engineering

Microservices move complexity from inside the application to the connections between services. A single transaction, such as binding a policy, may now involve several services, each of which can fail independently. The system has to cope with a service being slow or unavailable, and the team has to decide what happens to a bind if the document service is down.

Monitoring becomes harder. In a monolith, an error appears in one log. In a microservices system, tracing a failed bind can mean following a request through several services, so teams need tooling that tracks each request across them.

Data consistency needs care. When each service owns its data, keeping the policy, billing and claims records consistent requires deliberate design, and reporting may need a separate data store that brings them together.

All of this needs strong engineering and operations capability. For a software vendor that runs the platform as software as a service, those costs sit with the vendor. For an insurer building or running a microservices system in house, they sit with the insurer's IT team.

Microservices versus configurable platforms: what a buyer actually needs to know

Microservices describe how software is built. They do not decide how quickly a business user can launch or change a product. An insurer can buy a microservices-based system and still find that every new product needs a developer, and it can buy a modular system with a strong configuration layer and launch products without writing code.

For an insurer, MGA or broker choosing a policy administration system, the more useful questions are about outcomes. Can product, rating and rules changes be made by the business through configuration, without a development queue? Can the vendor release updates without disrupting the insurer's products? Can the platform scale for quote volumes from aggregators and partners? Can a component be swapped or a third-party service added through APIs? Does the platform publish events other systems can subscribe to?

If the answers are yes, the internal architecture is mainly the vendor's concern. Our article on low-code and no-code in insurance covers the configuration side, and our glossary entry on digital transformation in insurance sets out where architecture decisions sit in a wider programme.

How this applies to policy administration

For brokers, MGAs and insurers launching products, the practical benefits associated with microservices are independent releases, scaling under quote load and adding components through APIs. A policy administration platform can deliver those through a modular design, an API layer and event notifications, whatever its internal structure.

Genasys describes its platform on its product page as a modular, cloud-based SaaS platform running on Microsoft Azure, and on its connectivity page as API-first, with over 450 documented API endpoints and event notifications that let external systems receive real-time updates when defined business events occur.