Fraud-resolution and scam-prevention FAQ
Detection isn't the bottleneck anymore.
Resolution is, and that's where most fraud teams still spend their day.
These are the questions we get asked most by fraud, deposit ops and risk teams looking at automated alert resolution: what it can take off your plate, how it works with the systems you already run, what banks are seeing in practice, and how long it takes to get going.
If yours isn’t here, ask us.
1. What problem does Refine Intelligence solve?
Banks are very good at generating fraud alerts. The problem is resolving them efficiently and on scale. Refine automates the work that happens when an alert requires resolution: understanding what happened, engaging the customer using high-trust, automated outreach when needed, asking the right questions, determining their intent, and helping the bank make the right decision fast. The result is eliminating manual work, reducing unnecessary declines, and stopping more fraud and scams.
2. How is Refine different from the fraud solutions banks use today?
Traditional fraud platforms focus primarily on detection: identifying suspicious activity and generating alerts. Refine focuses on resolution. Its Agentic AI investigates alerts, invokes an automated customer outreach when needed, understands the context and customer intent, and analyzes the response using intent-aware AI trained on a proprietary data set of customers’ explanations to anomalies. Refine then recommends or automates the appropriate decision.
3. Is Refine a fraud detection tool or a fraud prevention tool?
4. What types of fraud does Refine handle?
Refine can resolve alerts across multiple payment types and fraud scenarios, including checks, ACH, wires, Zelle, and other digital payments. It is particularly powerful where understanding customer intent matters, such as in scams and business email compromise.
5. How does automated fraud alert resolution work?
When an alert is generated, Refine’s agentic AI analyzes the available data and determines what information is missing to resolve it. When customer input is needed, Refine launches a secure, branded digital conversation tailored to the specific transaction and risk. It combines the customer’s answers with the bank’s data to resolve the alert, typically without an analyst ever touching it.
6. Why is engaging customers important to stopping fraud?
Because the bank can see the transaction, but the customer knows not only if, but also why they’re making it. For Fraud Resolution to scale, understanding Intent at machine speed is crucial. Banks today use outreach as the last resort because it’s now a manual, ineffective process using phone calls; Refine has completely automated outreach and made it a high trust environment. Asking the right questions can uncover intent, context, and manipulation that transaction data alone cannot see.
7. Why do customers respond to Refine when they ignore normal bank calls?
Refine engages customers in a way they love and trust, using a branded, contextual inquiry in multiple channels simultaneously. Response rates are consistently over 80%, in an era where customer mistrust of communication is at an all time high.
8. How does Refine help against call spoofing and bank impersonation attacks?
In an impersonation scam, the criminal may be on the phone with the victim pretending to be the bank, often with the bank’s caller ID visible. During such an attack it is critical to automate payment verification. Refine succeeds in doing that by an automated outreach method that doesn’t use voice at all; it creates a separate, trusted digital interaction where the real bank can verify the transfer, ask customers scam-specific questions, and determine whether someone is coaching or manipulating them.
9. How does Refine tell a legitimate payment from a scam?
Refine doesn’t simply ask, “Did you make this payment?”, because scam victims often do make the payments. Instead, Refine investigates why the customer is making the payment: who they’re paying, how the interaction started, what they believe the payment is for, and whether there are signals of manipulation or deception. Refine then uses proprietary intent data to train AI so it can distinguish, in seconds, between an unusual but legitimate payment and a scam payment the customer authorized.
10. How much fraud alert triage can realistically be automated?
A substantial portion of alert-resolution work can be automated. Refine can handle initial investigation, customer outreach, information gathering, and resolution, allowing analysts to focus on the smaller number of cases that genuinely require human judgment. In production deployments, Refine has already achieved 88.6% automated alert resolution.
11. How does Refine fit into our current tech stack?
Refine sits downstream from the bank’s existing fraud detection systems. Banks don’t need to rip and replace their detection technology, and Refine developed a zero-integration method of pulling data from those systems. Existing systems continue generating alerts; Refine adds the automated investigation, customer engagement, intent intelligence, and resolution layer.
12. How long does it take to implement Refine?
Refine is designed for rapid deployment rather than a large core-system replacement. It’s measured in weeks, not long months. Implementation depends on the use case and integrations required, but banks can start with a focused alert type or payment rail and expand from there.
13. Can Refine be deployed quickly if we're under an active attack?
Yes. Refine can be deployed around a specific attack pattern or alert population without requiring the bank to redesign its entire fraud stack. That makes it useful when a bank is seeing a sudden spike in a particular fraud or scam typology and needs additional resolution capacity quickly.
14. What results can we expect?
Banks typically see three categories of impact: dramatically less manual investigation, much faster alert resolution, and better fraud/scam prevention. Refine has already achieved 88.6% automated alert resolution, with alert queues processed in seconds and most customer-assisted alerts resolving within an hour. This also gives fraud teams capacity to investigate more alerts without adding equivalent headcount.
15. Is Refine a fit for a bank or credit union our size?
Refine is designed to work across financial institutions of different sizes. For smaller institutions, it provides automation and capabilities that would otherwise require a much larger fraud team. For larger banks, it addresses the opposite problem: enormous alert volumes, operational costs, and the difficulty of scaling manual customer outreach. The common denominator isn’t bank size; it’s having too many alerts that still require too much human effort.