A familiar voice, message, account, or request can bypass ordinary caution when verification is informal.
Fraud-Prevention Workflows
Put Verification and Escalation Between a Suspicious Request and a Loss
Design repeatable checks around the moments where urgency, identity, payment, and account access can be abused.
Why this matters
Security fails at the handoff between people, systems, identity, and high-impact decisions.
One tool cannot solve impersonation, compromised access, payment changes, recovery, or vendor risk. The workflow needs layered controls people can actually follow.
Accounts, devices, vendors, integrations, and former staff retain permissions without clear review.
Backups, escalation, evidence, customer communication, and decision authority fail when the first real incident arrives.
How the solution works
Map the highest-risk workflow, then layer prevention, verification, and recovery.
Client-owned assetsHuman approval gatesInspectable handoffNo outcome guarantees
Identify assets, actors, access, approvals, failure modes, and realistic impact.
Apply practical controls to identity, devices, data, payments, vendors, and change requests.
Document escalation and recovery, train the team, and test the controls under realistic pressure.
Fit & boundaries
Know what the engagement does—and does not—include
Clear ownership and exclusions protect the result before work begins.
Good fit when
- Payment or account changes rely on email, voice, or one person's judgment.
- Refund, promo, marketplace, or support abuse lacks consistent review rules.
- The team needs an implementable playbook rather than a generic risk report.
Launch boundaries
- No claim to prevent all fraud or replace banks, insurers, legal counsel, or law enforcement.
- No discriminatory profiling or decisions based on protected traits.
- No collection of identity or behavioral data without a defined need, retention rule, and access owner.
What Custom AI Works does
A working system, not a vague promise
Fraud-risk mapping and practical controls for payments, refunds, account changes, vendor updates, marketplace activity, and customer-service workflows.
Risk mapping
Identify valuable actions, likely abuse paths, existing signals, and accountable owners.
Preventive controls
Add role separation, thresholds, known-channel verification, and safe defaults.
Escalation
Define holds, evidence collection, customer communication, and decision authority.
Learning loop
Review aggregate incidents and exceptions to improve controls without sensitive profiling.
Packages
Start at the level your operation needs
No public dollar claims: scope, access, third-party costs, and owner responsibilities are confirmed first.
Starter
Scope and pricing are confirmed after discovery. No media spend or third-party fees are hidden in the quote.
- Current-state audit
- Prioritized action plan
- One bounded implementation
- Owner handoff and next steps
Growth
Scope and pricing are confirmed after discovery. No media spend or third-party fees are hidden in the quote.
- Everything in Starter
- Managed execution cadence
- Reporting and decision log
- Monthly optimization review
Custom
Scope and pricing are confirmed after discovery. No media spend or third-party fees are hidden in the quote.
- Cross-platform scope
- Custom integrations or workflows
- Governance and approval design
- Phased rollout and runbooks
Delivery
A four-step path with approval gates
Map high-value actions and abuse cases
A named owner approves the output before the next material step.
Choose proportionate controls and thresholds
A named owner approves the output before the next material step.
Implement and test escalation
A named owner approves the output before the next material step.
Review aggregate outcomes and exceptions
A named owner approves the output before the next material step.
Evidence
Artifacts you can inspect before case-study claims
Proof before promises
Until a privacy-safe client aggregate qualifies, this service is demonstrated with a sanitized audit, a sample operating checklist, a synthetic-data reporting view, and the working process used to deliver the engagement.
Primary guidance: NIST AI Risk Management Framework
Client results may be published only as anonymous aggregates from at least five authorized clients or campaigns, with the sample, period, metric definition, and verification date disclosed. Public examples remain clearly labeled as external.
FAQ
Questions, answered
Can you prevent all fraud?
No. The goal is to reduce avoidable exposure, improve detection and escalation, limit loss, and make decisions more consistent.
Is this a fraud-scoring product?
Not by default. We begin with workflow and control design. Any automated scoring requires separate data, bias, privacy, explainability, and error review.
What processes do you cover?
Common scopes include vendor bank changes, refunds, chargeback evidence, account recovery, payroll changes, high-risk orders, and marketplace exceptions.
How is customer data handled?
We minimize collection, define access and retention, and prefer aggregate operational reporting over personal profiling.
Related
Build the rest of your Build & Secure system
Make the next decision
Where can trust fail in a high-impact workflow?
Describe the people, systems, approvals, and failure scenario. We’ll identify the right assessment or verification starting point without pretending one control solves everything.
- Which people, accounts, devices, data, or approvals are exposed?
- What impersonation, access, payment, or recovery failure matters most?
- Which verification, logging, escalation, and recovery controls must work together?