Situation
The operating reality
The legacy claims system encoded process in code. Every regulatory change required a quarterly release, and audit findings on evidence handling were rising.
Case study · Insurance
A claims modernization that closed cases 31% faster — and audit-ready
Modernised the claims platform with a workflow engine, evidence vault, and adjuster experience that closed cases 31% faster while improving regulatory audit posture.
Anonymized delivery dashboard
Insurance outcome cockpit
Cycle time
−31%
Audit findings
−72%
Adjuster capacity
+24%
Before
Constraint
Build
Controlled cutover
After
Measured gain
- Client
- European insurer
- Industry
- Insurance
- Service
- Digital Transformation
- Engagement closed
- October 2024
Storyline
From constraint to measurable change.
Every engagement is framed around the business situation, the constraint that made it hard, and the decision that turned delivery into a controlled path to value.
Constraint
Why it was hard
The legacy claims system encoded process in code. Every regulatory change required a quarterly release, and audit findings on evidence handling were rising.
Decision
The path we chose
Moved process rules into a governed workflow engine and made evidence handling tamper-evident by design.
Build
Workflow as data
We replaced hard-coded claim flows with a workflow engine where business analysts could safely change routing, SLAs, and approvals without a code change. Every change was versioned and audit-logged.
Claims evidence was stored with append-only audit trails, cryptographic hashing, and customer-data-residency controls aligned with the regulator’s expectations.
Outcome
Measured impact
Median claim cycle time fell 31% across motor, home, and travel lines.
Regulatory audit findings dropped 72% year-over-year.
What changed after launch
New behavior
Regulatory changes could be modeled, versioned, and audited without waiting for a quarterly software release.
Outcome
The numbers that mattered.
- Cycle time
- −0%
- Audit findings
- −0%
- Adjuster capacity
- +0%
“The adjusters got speed, compliance got evidence, and neither group had to trade off against the other.”
Before and after
The transformation the client could see.
The work was not abstract modernization. It changed day-to-day behavior, ownership, and the evidence leaders used to make decisions.
Workflow modernization
Before
- Claims process encoded in code
- Quarterly release dependency
- Evidence audit findings rising
After
- Workflow changes versioned by analysts
- Append-only evidence vault
- 31% faster median cycle time
Architecture and delivery
A controlled path from discovery to launch.
The delivery plan made the system boundary explicit, then used rehearsals, gates, and telemetry to optimize safely before launch.
Delivery architecture
Insurance control loop
Discover
Workflow as data
We replaced hard-coded claim flows with a workflow engine where business analysts could safely change routing, SLAs, and approvals without a code change. Every change was versioned and audit-logged.
Launch
Evidence vault with tamper-evidence
Claims evidence was stored with append-only audit trails, cryptographic hashing, and customer-data-residency controls aligned with the regulator’s expectations.
Build
How we shaped the work.
Workflow as data
We replaced hard-coded claim flows with a workflow engine where business analysts could safely change routing, SLAs, and approvals without a code change. Every change was versioned and audit-logged.
Evidence vault with tamper-evidence
Claims evidence was stored with append-only audit trails, cryptographic hashing, and customer-data-residency controls aligned with the regulator’s expectations.
What changed after launch
What shipped, and what it changed.
- Median claim cycle time fell 31% across motor, home, and travel lines.
- Regulatory audit findings dropped 72% year-over-year.
- Adjuster effective capacity increased 24% without headcount change.
After launch
Regulatory changes could be modeled, versioned, and audited without waiting for a quarterly software release.
Stack
What we built it with.
.NET
TypeScript
PostgreSQL
Camunda
Azure
Azure AD
Datadog
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