Account Takeover Defence
Risk-adaptive authentication, step-up verification on high-value actions, credential stuffing detection, and lifecycle controls over reset, recovery and delegation flows.
Practice 01
Loyalty Fraud Prevention & Identity Security
Purpose-built defence for loyalty ecosystems. Not a payment fraud engine pointed at a rewards database — a control architecture designed around how points are actually stolen, laundered and cashed out.
The Premise
Loyalty fraud is an infrastructure problem, not a support ticket
Generic fraud platforms are built around a card-present or card-not-present transaction: a discrete event, a merchant, an amount, a decision. Loyalty ecosystems do not look like that. Value accrues through program rules, sits as a balance for months, moves between accounts and partners, and converts to something liquid at a moment that may be far removed from the compromise.
That structure creates attack surface a payments model never sees — accrual logic abuse, pooling and transfer arbitrage, reconciliation delay exploitation, partner boundary inconsistency and administrative override. Each is legitimate system behaviour used against its economic intent.
The practice therefore works at the architectural level: identity as asset custody, behaviour as an integrity signal, transactions as integrity-sensitive operations, and administrative authority as a custodial responsibility that must be segmented and attributable.
Capabilities
What gets built
Controls are selected against the findings of the assessment, then implemented in the order that removes the most exposure for the least disruption to legitimate members.
Behavioural & Risk Analytics
Continuous baselines per account, device and operator. Deviation scoring that catches novel and low-frequency patterns that static rules never fire on.
Graph Correlation
Network-level analysis linking accounts, devices, IPs, payment instruments and redemption destinations to surface coordinated rings invisible at the single-account level.
Device & Session Intelligence
Device fingerprinting and session signals that establish persistent trust — and expose emulation, farm infrastructure and proxy rotation.
Velocity & Transaction Integrity
Dynamic limits calibrated to value and behavioural history, contextual verification on redemption, and automated throttling of suspicious flows before extraction completes.
Policy-Abuse Prevention
Rule validation across accrual, promotion, referral, pooling and returns logic — closing the arbitrage paths that operate entirely within nominal permissions.
Governance & Insider Risk
Privilege segmentation on least authority, dual authorisation for balance adjustment and manual issuance, and tamper-resistant audit trails over privileged action.
Real-Time Fraud Operations
Event-driven telemetry, live scoring, automated containment, investigation workflow and a feedback loop returning confirmed outcomes to the models.
Fraud-Resilient Architecture
Design-level work: trust boundaries, API contracts, reconciliation windows and failure modes specified so that a compromise in one component cannot cascade.
Coverage
Attack vector to control layer
Every vector maps onto the architectural layer that can actually interrupt it. Controls placed in the wrong layer generate alerts without preventing loss.
| Attack vector | Primary control layer | Severity |
|---|---|---|
| Credential stuffing & ATO | Identity assurance + device intelligence | Critical |
| Insider privilege misuse | Governance architecture + behavioural oversight | Critical |
| Synthetic account creation | Graph correlation + enrolment velocity | High |
| Redemption & returns abuse | Transaction integrity + rule validation | High |
| Gift card monetisation | Velocity controls + destination risk scoring | High |
| Promotional & referral farming | Policy-abuse prevention + graph clustering | High |
| Partner API exploitation | Integration hardening + rate governance | High |
How It Runs
From assessment to steady state
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01
Discovery & threat modelling
Map the ecosystem: identity flows, accrual and redemption paths, partner integrations, administrative surfaces and reconciliation boundaries. Model who would attack what, and how.
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02
Exposure quantification
Test the model against actual data. Establish where value is leaking today, at what rate, and which findings carry material financial or regulatory weight.
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03
Control design
Specify the control architecture across all five layers, including the security–usability tradeoffs. Friction is applied deliberately and narrowly, where risk justifies it.
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04
Implementation
Build and integrate, sequenced by risk reduction per unit of effort, with measurement in place from the start so the effect of each control is observable.
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05
Tuning & validation
Calibrate thresholds against false-positive cost, validate that legitimate member journeys are unaffected, and confirm containment works end to end.
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06
Operational handover
Runbooks, investigation workflow, executive reporting and the feedback loop that keeps detection current as attacker behaviour shifts.
Common Questions
Before you get in touch
Usually not. Payment fraud engines, WAFs and bot management do useful work — they simply
do not model loyalty-specific logic. The typical outcome is a layer that consumes signals
from what you already run and adds the loyalty-aware scoring, graph correlation and
governance controls that are missing.
The design constraint is that friction is a targeted defence mechanism, not a default
posture. Most controls are invisible — device signals, behavioural baselines, background
scoring. Verification is escalated only when risk context justifies it, typically on
high-value or anomalous actions rather than on every login.
Yes. A large share of the control surface sits around the platform rather than inside it —
identity, API boundaries, telemetry, administrative governance and redemption
validation. Where the platform is extensible, controls go deeper; where it is not, the
architecture compensates at the boundary.
Architecture documentation, access to the people who own identity, program rules and
fraud operations, and — where possible — anonymised or aggregated telemetry covering
authentication, accrual, redemption and administrative activity. Scope and data handling
are agreed before anything is shared.
Start with the assessment
Know your exposure before committing budget to controls. The findings register is yours either way.