Insurers focus on claims once they’re filed, but many are lost before that, at First Notice of Loss (FNOL). Here’s why automating FNOL is the fastest way to fix insurance’s non-claiming problem.
Drafting business requirements is one of the most time-consuming yet critical parts of any technology project. It’s where ideas turn into structure, where “what we want” becomes “what we need to build.” But anyone who’s been through the process knows: it can be messy, repetitive, and full of back-and-forths.
This is where Artificial Intelligence (AI) is starting to show enormous potential — and where, at Briisk, we’re exploring how to make these capabilities possible for our partners. The goal? To make drafting business requirements smarter, faster, and better.
In insurance, precision is everything. The business requirement document sits at the heart of how products, platforms, and integrations come to life. It defines workflows, data flows, compliance checks, customer journeys — essentially, the DNA of a digital insurance process.
But writing requirements manually is labour-intensive and often involves multiple iterations between business analysts, product owners, and developers. Misinterpretations can lead to costly rework later in the build phase.
That’s why AI-assisted requirement drafting could become a game-changer: helping teams get to clarity faster, with fewer gaps, and more consistency.
While AI won’t replace human expertise, it can assist in several powerful ways:
✅ Automating the first draft: AI could analyse existing project documentation, emails, or meeting notes to produce a structured first draft of requirements — saving hours of manual writing.
✅ Ensuring consistency: By comparing against past projects, AI could highlight missing sections, duplicated logic, or inconsistent terminology.
✅ Validating completeness: Intelligent models might flag unclear requirements or dependencies that haven’t been fully defined.
✅ Bridging business and tech: AI could help translate between business language and developer language, improving communication across teams.
The result? A cleaner, more complete foundation for build teams to work from — and ultimately, a faster path to market.
At Briisk, we’re not just looking at how AI can assist once the system is already built — we’re exploring how it could strengthen the Build phase of our Build–Operate–Transfer model.
Through the Briisk Instant Transaction Platform (BITP), we’ve already standardised much of the process of digitising insurance journeys. Now, we’re investigating how AI could further streamline the early planning and documentation stages of these projects.
Imagine a future where:
✅ BITP-integrated tools assist in generating draft requirement documents based on pre-configured templates,
✅ AI models identify potential compliance or data integrity gaps before development even begins,
✅ And business and technical teams collaborate more seamlessly with AI-supported language bridging.
These are the kinds of possibilities we’re working to make real — carefully, ethically, and always with human oversight.
It’s important to remember: AI can make requirement drafting faster, but not automatically better without human expertise. The best results come from a collaboration between the two — AI providing structure, humans providing strategy.
At Briisk, our approach is about empowering people, not replacing them. By using AI as an enabler within BITP and our Build–Operate–Transfer framework, we aim to create a future where insurance partners can focus less on the admin and more on the innovation that drives their business forward.
Drafting business requirements may never be fully effortless — but with the help of AI, it could soon be much more efficient, accurate, and insightful.
At Briisk, we’re actively exploring how these AI capabilities could fit into the foundation of our digital transformation model, paving the way for smarter builds, smoother operations, and faster innovation.Stay tuned for our next post: “From code to capability: how AI could support development and coding.”
Insurers focus on claims once they’re filed, but many are lost before that, at First Notice of Loss (FNOL). Here’s why automating FNOL is the fastest way to fix insurance’s non-claiming problem.
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Drafting business requirements is one of the most time-consuming yet critical parts of any technology project. It’s where ideas turn into structure, where “what we want” becomes “what we need to build.” But anyone who’s been through the process knows: it can be messy, repetitive, and full of back-and-forths. This is where Artificial Intelligence (AI) […]
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