SaaS solutions
Fraud Detection for SaaS
Most fraud detection initiatives stall on data quality, governance, or change management — not on the models themselves. Beryl Analytics solves the full stack for B2B software companies, from ingestion through to operator adoption.
Why saas teams choose Beryl Analytics for fraud detection
- Built for compounding value. Each fraud detection engagement leaves B2B software companies with infrastructure that accelerates the next one — shared feature stores, reusable pipelines, documented data contracts.
- Real handover. We pair your team into the build from day one. By go-live, they own the system. We're optional from then on.
- Practical AI. We've shipped LLM-augmented analytics where they help, and stayed with simpler models where they outperform. Hype is not a strategy.
- Audit-friendly. Every model decision is traceable. Compliance and risk teams stop blocking — they start enabling.
- Track record. 1,000+ models in production. Across heavy-industry, regulated, and consumer domains.
How we deliver fraud detection engagements
- 01
Discovery (week 1-2)
We meet your operators, map data sources, and pressure-test the business case. Half the value is sometimes in killing the wrong initiative and reframing the right one.
- 02
Pilot build (week 3-6)
One vertical slice end-to-end: ingest, model, dashboard, monitoring. Real data, real users, measurable result before we expand.
- 03
Productionise (week 7-12)
Hardening, governance, lineage, runbooks, observability. Pair-programmed with your team so they own it by handover.
- 04
Scale & evolve
Expansion into adjacent use cases, retraining cadence, model performance reviews, and a roadmap that compounds.
Frequently asked questions about Fraud Detection for SaaS
How long does a typical Fraud Detection engagement take for a saas business?
Most fraud detection projects for B2B software companies land a working production slice within 4-6 weeks, then harden and expand over the following 8-12 weeks. Larger saas programmes that touch multiple business units take 4-6 months end-to-end.
What data do you need to start a Fraud Detection project in saas?
Minimum viable inputs are 12-18 months of historical transactional or operational data, basic entity reference tables, and access to the systems that will consume the output. We can work with messy data — cleaning is part of the engagement.
Can Beryl Analytics integrate fraud detection with our existing B2B software companies systems?
Yes. We're tool-agnostic and have integrated with Snowflake, BigQuery, Databricks, Salesforce, SAP, Oracle, custom in-house platforms, and dozens of saas-specific systems. Insights surface inside the tools your operators already use.
How do you measure success on a Fraud Detection engagement?
Before we model anything, we agree the business decision the output will change and the dollar metric we're targeting — revenue lifted, cost avoided, or risk reduced. Fraud Detection engagements in saas typically return 4-12x within the first year.
Do you work with saas businesses outside major NZ and AU cities?
Yes. We deliver remotely across New Zealand and Australia and visit on-site for discovery, key workshops, and go-live. Distance is not a blocker — many of our highest-impact fraud detection engagements have been with regional B2B software companies.