Fraud Technology Consultant
Most RequestedOwns detection design and delivery across whichever platform or in-house engine you run.
- Detection design
- Configuration
- Delivery
Financial Crime Technology
Fraud Talent Who Understand the Cost of Every Rule
Hire fraud technologists across vendor platforms and in-house decisioning — policy rules, real-time performance, models and signals, channel integration and case operations. Every change moves losses, customer friction and queue volume at once, and we screen for people who think in all three.
For banks, card issuers, payments firms and fintechs. Contract, contract-to-hire and dedicated pods.
What a Fraud Brief Usually Looks Like
Live demand- Roles
- Fraud technology consultant, policy and rules specialist, decisioning engineer, model analyst, channel integration developer
- Common estates
- Vendor fraud platforms, in-house rules and decisioning engines, or a hybrid with a vendor scoring service
- Typical trigger
- A rising loss line, a new payment rail, a scams and mule programme, or decisioning that cannot keep up at peak
- Engagement
- Contract · Contract-to-hire · Dedicated team · Project pod
- Working models
- Onsite, hybrid, offshore, or blended with your existing squad
Send us a JD or a rough outline —start a requirement.
Coverage
- Cards
- Payments
- Digital banking
- Account takeover
- Scams & mules
- Application fraud
Why This Role Is Hard to Fill
Fraud Detection Is Three Numbers Moving Together
Fraud caught, customers wrongly blocked, and cases the operation has to work. Improve one and you almost certainly worsen another. The engineers worth hiring talk about all three without being prompted, and can tell you what a specific change did to each.
It also happens inside a payment. Detection sits in the live path, so design is bounded by a latency budget and a throughput ceiling that batch financial crime work never has to respect. Add channel-specific behaviour — card, instant payments, digital session, onboarding — and the number of people who genuinely cover a given brief narrows fast.
All Financial Crime Technology Talent- AML Experience Offered as Fraud ExperienceBoth are financial crime, but batch detection with a review window is not real-time decisioning. The disciplines do not transfer cleanly.
- No Loss or Friction NumbersCandidates who cannot describe the impact of their own rule changes were probably not the ones making the decisions.
- Latency Treated as Someone Else’s ProblemRules that enrich from several external calls look fine in test and fail at peak volume in production.
- Channel-Specific GapsCard, wire, instant payments and digital session fraud behave differently. Experience in one is not experience in all.
- Never Been on the RotaFraud runs around the clock. Engineers who have handled a live incident and a rule rollback design with a safety net.
Roles We Staff
The Fraud Roles Banks Ask Us For
Mix and match into a squad, or add one specialist to a team you already have.
Fraud Policy & Strategy Specialist
Runs the rule set as a portfolio — what to add, what to retire, and what each choice costs.
- Rule portfolio
- Loss analysis
- Trade-offs
Real-Time Decisioning Engineer
Keeps detection inside its latency budget — enrichment design, caching, throughput, failure behaviour.
- Latency
- Throughput
- Failover
Fraud Model & Analytics Analyst
Score thresholds, model monitoring, champion-challenger testing and drift detection.
- Thresholds
- Monitoring
- Champion / challenger
Channel Integration Developer
Wires in card, payment, digital and onboarding channels with the signals each one needs.
- Payment rails
- Digital sessions
- Device data
Scams & Mule Detection Specialist
Inbound and outbound scam patterns, mule account behaviour, and detection that respects customer harm.
- Scam typologies
- Mule networks
- Intervention design
Fraud Case & Operations Developer
Queues, routing, investigator screens and the MI fraud leadership runs the function on.
- Queues
- Routing
- Operational MI
Performance QA & Release Automation
Load and regression testing against realistic traffic, plus rollback rehearsal for rule releases.
- Load testing
- Regression
- Rollback drills
What We Screen For
The Capability Grid Behind Every Shortlist
Requirements get mapped against this grid before we send anyone, so you can see depth by area instead of reading it out of a CV.
Detection & PolicyThe rule portfolio, not single rules
- Policy rule design
- Profiles & velocity checks
- Score thresholds
- Rule retirement
- Suppression & whitelisting
- Shadow mode & A/B
- Typology coverage
Real-Time PerformanceThe constraint that shapes the design
- Latency budgets
- Peak throughput
- Enrichment call design
- Caching
- Timeout & failover
- Capacity planning
- Load testing
Channels & RailsEach behaves differently
- Card present & not present
- Instant & faster payments
- Wires
- Direct debit & ACH
- Digital and mobile banking
- Application fraud
- Account takeover
- Authorised push payment scams
- Mule detection
Models & SignalsKeeping detection honest over time
- Model performance monitoring
- Drift detection
- Champion / challenger
- Device & behavioural signals
- Consortium & third-party scores
- Feature availability
- Backtesting
Data & IntegrationWhat detection can see
- Channel feeds
- Customer & account context
- Third-party enrichment
- APIs & services
- Case handoff
- Reporting extracts
- Data quality controls
Platforms & OperationsWhere vendor experience matters
- Vendor fraud platforms
- In-house decisioning engines
- Change control on live traffic
- Rollback
- Incident response
- Round-the-clock support models
- Monitoring & alerting
Vendor-specific briefs are staffed from the platform practices — see NICE Actimize IFM and SAS financial crime talent.
Engagement
Compare all modelsFour Ways to Bring Fraud People On
Dedicated Technology Teams
A standing pod, because fraud typologies change faster than a project cycle can absorb.
DetailsContract Staffing
Named specialists for a defined period — a new channel, a scams programme, a performance fix.
DetailsProject Team Staffing
A scoped outcome — a rail onboarded, a model refresh, a decisioning re-platform.
DetailsContract-to-Hire
Work together first, convert to permanent once the fit against your loss lines is proven.
DetailsHow We Get to a Shortlist
Screening, in the Order It Happens
Four steps, and you hear from us at each one.
- 1
Requirement Intake
Which channels and rails, real-time or batch, current pain in losses or false positives, and who signs off rules.
- 2
Specialist Screening
A financial-crime-experienced reviewer probes trade-offs made, latency problems solved, incidents handled.
- 3
Shortlist With Notes
Profiles arrive with channel coverage and real-time depth rated separately, plus notice period and rate.
- 4
Interview and Onboard
We coordinate panels, handle paperwork and stay involved through the first weeks on your estate.
Profile Shapes
What a Fraud Shortlist Tends to Contain
Representative profile structures for the three most common briefs.
Senior Fraud Technologist
Cards and payments · real-time
- Has shipped rule change into live fraud traffic
- Runs shadow mode before going live, as a habit
- Can state what a change did to losses, friction and queue volume
- Has been on the incident rota
Fraud Policy & Analytics Specialist
Loss-line facing · analytical background
- Owns the rule portfolio, including retirement
- Model monitoring and threshold work with measured outcomes
- Presents trade-offs to fraud leadership
- Has delivered a scams or mule detection programme
Real-Time Decisioning Engineer
High volume · performance-led
- Has fixed a decisioning latency or timeout problem in production
- Enrichment design, caching and failover behaviour
- Load testing against realistic traffic profiles
- Capacity planning for peak events
These are representative profile structures, not live availability. Current availability, notice periods and rates are shared against a specific requirement.
Before You Send a Brief
Questions We Get Asked
Will an AML specialist do for a fraud role?
Usually not, and we will say so rather than filling the seat. Real-time decisioning under a latency budget is a different discipline from batch monitoring. Where a crossover candidate genuinely works — often on the data or case management side — we flag exactly which part transfers.
We run an in-house decisioning engine rather than a vendor platform. Does that narrow the pool?
It changes it rather than shrinking it. In-house estates favour engineers with stronger software and performance backgrounds, while vendor estates favour configuration depth. We screen accordingly rather than treating all fraud experience as interchangeable.
Do you screen for specific channels?
Yes. Tell us which rails matter — cards, instant payments, wires, digital sessions, onboarding — and the shortlist is built around them rather than around generic fraud exposure.
Can you staff round-the-clock support as well as build?
Yes, and it is worth scoping separately. Support cover changes the shape of the team and the working pattern, so we would rather staff it explicitly than let a build team absorb a rota badly.
Do you cover the adjacent disciplines?
Yes — see AML, transaction monitoring, KYC and risk & compliance technology.
What do you need from us to start?
A JD if you have one. If not: channels and rails in scope, vendor platform or in-house, the current pain, whether the role is policy, engineering or analytics-led, seniority, engagement type and location expectations.
Request Talent
Tell Us Where the Losses Are Coming From
Send a JD or a two-line outline. We come back with the roles that fit, what the market looks like for them, and a shortlist against your requirement.
Send Your Requirement
Two minutes now, a shortlist conversation next.