Insurance
Most insurers know exactly what it is that is holding them back.
The overwhelming part is working out how to fix the problem without throwing everything else out with it. We've delivered a decade of insurance automation and decisioning across APAC - built for carriers, underwriting agencies, and brokers.
The landscape
The problems we keep walking into
Different clients, same structural issues. Each one gets harder to live with as the market accelerates - faster competitors, tighter regulation, softer markets, higher costs.
Pricing agility is locked inside policy admin
Most carriers and underwriting agencies run pricing through the same platform that handles the policy lifecycle, selected to manage that complexity, not for agility. A rating model or factor change takes months, and the product team can't experiment without IT spend and an unpalatable lead time.
Meanwhile MGAs enter with no legacy, price weekly, and take share. The carrier knows the problem; the platform vendor won't solve it.
Two underwriters, same proposal, different answers
Referral rates fluctuate by underwriter, swayed by bias, interpretation, time, and experience. Eligibility rules live in spreadsheets, PDFs, and the minds of tenured underwriters. When a regulator or broker asks "why" on a decision, the audit trail is often an email chain, or less.
The cost is quiet but real - adverse selection, broker churn, margin leak - and regulatory and binder pressures ask harder questions with every quote.
Brokers are the customer, and their experience influences their choices
As the intermediary market expands and specialises, the carrier that wins broker share is the one with the simplest, fastest, most transparent experience. Most carriers know this; few have shipped anything brokers would call a step change.
Brokers still re-key data into portals that weren't designed for them. Quotes take days, some never arrive. Referrals disappear into queues with no visibility, and the broker can't see why a decision was made, so can't explain it to their client. Every carrier has a project to fix this; most are still planning it, and still framing it from the insurer's angle, not the broker's.
Unstructured data is here to stay. Processes must evolve.
Whether it's underwriting, servicing, or claims, core processes still resemble what they looked like 30 years ago, including the data they rely on. What has changed is our ability to use AI to curate, organise, and contextualise the unstructured data that until now needed a swarm of humans, or went untouched. The trap most fall into: tuning AI alone to be correct and consistent, or deploying it only to automate gross inefficiency.
The problem isn't whether to automate. It's where to draw the line - automating the parts that don't need a human, so the parts that do get the attention they deserve. Most carriers are still debating the principle when they should be drawing the line.
What good looks like
A carrier or agency that has solved these
There are two ways to define success. Neither is better than the other, but the difference is strategic.
Operational transformation
An organisation that has approached digital transformation properly doesn't look transformed at all from the outside. Internally, the efficiencies surface materially - in the P&L, in handling times, conversion rates, and SLAs. There are equally important shifts in team culture, with people working on higher-value tasks.
Business-model transformation
Then there is the organisation that has looked at the opportunity through a much wider lens. It looks beyond operational processes to reconsider what it does, how it does it, and who it does it with, reimagining the operating model altogether. In some cases, abandoning parts of it.
Rate changes ship in days. Product experiments run weekly. Two underwriters reach the same decision on the same submission - in Sydney and in Brisbane, whether they're senior or a new starter. The audit trail builds itself. Regulator questions get answered with a query, not a three-week internal investigation.
Brokers self-serve the routine and get fast human judgement on the complex. Quote-bind-issue times drop. The carrier's name moves up the broker shortlist because the experience matches what brokers actually want.
Claims triage, eligibility, and data gathering run in seconds. Complex cases get the attention they deserve. Routine cases stop waiting in queues. The human is freed from work that doesn't need them.
How we've helped
Patterns anchored in real work
Patterns we've shipped across carriers, underwriting agencies, and broker platforms. All in production. Each one transfers across lines of business and across carriers.
Externalised rating engines
Pulling rating logic out of the policy admin platform gives product teams direct control without forcing a platform replacement. The platform keeps doing what it's good at - policy lifecycle, billing, document generation. The rating engine sits beside it, owned by product and pricing, with product and rating enhancements deployable in days in some cases.
We built this for Envest across their Club 4x4 and KT Insurance brands - externalised rating engines under a multi-brand insurance group, with the incumbent policy admin staying in place underneath.
Underwriting decisioning that holds together
For specialist lines and complex risks, we've replaced spreadsheet-driven underwriting decisioning with auditable platform-based rules. Eligibility, referral routing, pricing logic, and decision rationale all live in one place.
Solution Underwriting (now CFC) now benefits from a consolidated new business, MTA, and renewal workflow across product lines and binders.
Premium calculation and rules at carrier scale
For life carriers operating multi-channel distribution, the premium calculation engine and the underwriting rules engine are the two heaviest workloads. Both have to be fast, auditable, and able to absorb a constant stream of regulatory and product change.
Fidelity Life runs premium calculation, commission calculation, and reinsurer calculation on a no-code decisioning solution we designed and delivered for them. Integrity Life's advisor quote and underwriting lifecycle ran premium calculations and 60-year premium projections in sub-second time on a solution we delivered. A state government department runs an average of 10,000 premium calculations per day on a multi-provider rating solution we developed.
Claims and underwriting automation - drawing the line
The question in Life and Health is never whether to automate. It's where to draw the line. Triage, eligibility, data gathering, and routine determinations run in seconds, leaving the human time for cases that need judgement.
A global Life reinsurer we partnered with described this as the work that protects the moments that matter. The pattern transfers to any life or health carrier balancing customer experience against regulator scrutiny and team capacity.
Proven in European insurance
The conversational and immersive patterns we bring to ANZ are already in production with European insurers. CNP Vita, an Italian life insurer, lifted 40 percent of its service workload with a conversational agent at 97 percent answer accuracy. Generali Global Corporate & Commercial runs immersive XR risk engineering, with true-to-life industrial environments and an Apple Vision Pro risk-awareness experience.
Capabilities that apply
Where to start
Our decisioning and AI capabilities cover most of the work above. What matters most is understanding how and where to apply the capability.
Process and Decision Automation
The underwriting rules engines, pricing control, claims triage, and decision externalisation patterns above. Where most insurance engagements begin.
Artificial Intelligence
Broker portals, customer service across channels, claims first-notice-of-loss, accessibility-by-design. The experience layer on top of the decisioning underneath.
Related reading
Go deeper
Questions we get asked
What does decisioning look like in insurance?
Rating, underwriting rules, eligibility, and claims triage, externalised from core systems so product and operations teams own the logic and can change it in days. We have delivered a decade of this work across APAC, for carriers, underwriting agencies, and brokers.
Can you take rating out of our policy admin platform?
Yes. An externalised rating engine sits beside the policy admin platform, owned by product and pricing, while the platform keeps running the policy lifecycle, billing, and documents. We have built this for multiple insurers across ANZ, with the incumbent policy admin staying in place underneath.
Where does AI fit in insurance operations?
AI reads and organises the unstructured material that slows underwriting, servicing, and claims, and gets each case decision-ready; deterministic rules then make the call that has to hold up to a regulator. CNP Vita, an Italian life insurer, lifted 40 percent of its service workload with a conversational agent at 97 percent answer accuracy.
How do you handle rule and rate versioning?
Rules and rates are versioned at the logic, rate, or rating-factor level, so any quote or decision can be replayed against the version in force at the time. The right pattern depends on the architecture; we have several in production.
Do you work with brokers, underwriting agencies, and carriers?
All three, across the full customer and policy lifecycle: broker platforms, agency underwriting workbenches, and carrier-scale rating, premium and commission calculation, and claims automation. Fidelity Life, Integrity Life, Solution Underwriting (now CFC), and Envest are named examples.
Is this only for large insurers?
No. The same discipline scales down; the constraint is whether the workload has enough volume to justify it. Specialist lines and underwriting agencies are often the strongest fit.