Built for home and commercial service pros, Jobber's platform streamlines and automates operations so businesses can work more efficiently, increase profitability, and scale with confidence. More than 100,000 businesses and 400,000 service pros across more than 50 industries, including landscaping, plumbing, cleaning, and contracting, rely on Jobber every day to quote jobs, schedule crews, track jobs, collect payments, and more. As Jobber expanded its fintech offerings, the surface area for fraud and financial risk grew alongside it.
Below is an interview with Barnard Steyn, Head of Risk and Fintech Operations at Jobber, detailing their experience with Sardine.
1. Before Sardine, what did Jobber's fraud and risk operations look like? (team, tooling, workflows)
Before Sardine, Jobber's fraud and risk operations relied on a legacy vendor that provided baseline coverage across core risk areas like account takeover and transaction fraud.
The setup served us well in our earlier stages, but as the business grew, we started to feel limitations in flexibility, signal depth, and the ability to adapt quickly.
Our workflows leaned more manual than we wanted, and the team was spending meaningful time on tasks that were better suited to automation.
2. What were the main fraud or financial risk challenges you were facing as Jobber scaled?
As Jobber scaled, the central challenge was maintaining accurate risk decisions without adding friction for legitimate customers. Growth brought higher volumes and more sophisticated activity, which required a more adaptable approach to decisioning and review.
We also needed a way to make consistent, repeatable decisions across a broader set of scenarios as both the product and the risk surface continued to evolve.
3. What gaps did you see in your previous stack?
The main gap was fragmentation. Signals, decisions, and workflows weren't unified in a way that allowed the team to operate efficiently, which slowed investigations and made it harder to spot patterns across cases.
We also wanted more flexibility on the rule and iteration side so the team could respond to new patterns faster.
4. In contrast, what does your fraud team and risk stack look like today? What has changed the most?
Today, our risk operations are centerd on a unified case management workflow, with Sardine providing the signal layer that informs decisions across various lifecycles of our customers.
The biggest change is the shift to a more proactive, scalable posture: analysts have richer context behind each decision, and the team can iterate on rules and controls much faster than before.
Overall, the operation feels more cohesive and better positioned to keep pace as Jobber continues to grow.
5. When choosing a provider, what criteria mattered most in that process?
The most important criteria were coverage, flexibility, and alignment with Jobber's future roadmap. Jobber is constantly innovating on the product side and expanding into new areas within our fintech arm, so we needed a vendor that could move quickly and adapt alongside us.
Beyond roadmap fit, we needed a partner that could deliver real-time decisioning, strong signal coverage, and meaningful automation across our workflows. Ease of integration, explainability for analysts, speed of iteration, and the ability to consolidate vendors over time were equally important.
Taken together, these criteria pointed us toward a partner that could serve as a long-term foundation rather than a point solution, which was central to the decision.
6. What has the experience of working with Sardine been like, and what problems has it helped Jobber solve?
Working with Sardine has been a strong partnership from the start. The team is responsive, collaborative, and genuinely invested in helping us get the most out of the platform, whether that's translating new rule ideas into production, helping us interpret signals, or supporting us as our use cases evolve.
On the problem-solving side, Sardine has helped Jobber close several meaningful gaps. We now have richer device and behavioural signals informing our decisions, faster iteration on rules in response to new fraud patterns, and the flexibility to adapt as our product and risk surface continue to grow.
7. How do you see the partnership with Sardine evolving as Jobber's business grows?
As Jobber continues to grow and expand its fintech offerings, we see the partnership with Sardine evolving alongside us.
The platform's flexibility means we can layer in new use cases as they emerge, whether that's deeper automation, expanded coverage across new product areas, or leveraging more of the platform's capabilities as our risk surface broadens.
8. What metrics or outcomes matter most for measuring success with Sardine?
The most important success metrics are fraud loss reduction, manual review rate, time to decision, analyst productivity, false positive rate, and account takeover prevention.
9. Has Sardine changed your team's day-to-day workflow in a meaningful way? Any anecdotes you can share?
One of the standout aspects of Sardine has been the depth of signal coverage and the quality of the analytics layer on top of it. The platform surfaces granular device and session attributes that go well beyond what we had access to previously. These markers are incredibly useful for distinguishing legitimate users from bad actors, identifying emulators or spoofing attempts, and linking related sessions across accounts.
The analytics dashboard is equally strong and removes the need to create and maintain one made internally. It gives the team a robust, real-time view into rule performance and signal trends, making it much easier to spot emerging patterns and validate the impact of rule changes.
Together, the richness of the underlying signals and the visibility provided by the dashboard have meaningfully raised the ceiling on what our team can detect and act on.
10. If you were recommending Sardine to another Head of Fraud or Risk, how would you describe the value?
I would describe Sardine as a flexible risk decisioning platform that helps a growing fintech bring together fraud and behavioural signals.
The value isn't just another fraud score, it's better signal coverage, more consistent decisions, fewer disconnected workflows, and a platform that can scale alongside new products and emerging risk types.
That combination of breadth, flexibility, and automation is what makes it a true platform rather than a point tool.