Data is the foundation of Insurtech. Policy details, coverage types, premium changes, individual transactions: none of it means anything if it isn't accurate. Carriers need clean data to make good decisions for their business and their customers. That's where NLS spends its time, and it's the kind of work our team has built its reputation on.
The Challenge
A recent NLS client managed a large on-premise data warehouse and wanted to move to the cloud. First, their data ingestion pipeline needed work. It had to become On-Demand compliant, without disrupting the business already running on top of it.
The Approach
Our data SMEs live inside Duck Creek every day, and it showed in how fast they got oriented in this client's environment. We partnered with the client's team to remediate their pipeline using:
- Duck Creek Clarity (Snowflake-based)
- Balancing and Controls
- The Duck Creek Extract Mapper tool for policy data
To stay On-Demand compliant across staging and warehouse, our team built a direct data hop, a bridge that mapped the new On-Demand database into the client's existing staging model. Their historical data stayed intact. No rebuild required, a solution that only comes from knowing exactly how Duck Creek's data architecture behaves under pressure.
We stayed out-of-the-box wherever feasible, and we made sure we understood the client's staging model inside and out, tracking how data moved both upstream and downstream, not just where it landed. That upstream-downstream instinct is second nature to our SMEs at this point, and it's what let us catch design gaps before they became production problems. One result of that work: an auditing tool that checks a policy's transaction premium from source to destination, so premium issues surface fast now, not months later. We also built a full test strategy, with defect standards, clear triage, and defined validation at every step, the same rigor we bring to every Duck Creek engagement, regardless of size.