Take conversion friction out of payment screening
Decision Deck helps payment teams screen transactions without turning fraud control into conversion drag. Approve trusted payments faster. Step up only when it can save the transaction. Block real fraud. Keep fraud, chargeback and compliance thresholds under control.
Higher approval rates · fewer false declines · lower fraud loss · stronger chargeback control.
Don’t block good payments with blunt scores
A payment can look risky for the wrong reason. A new device, unusual location, larger order or first-time purchase may be fraud. It may also be a good customer doing something new.
Decision Deck separates real payment risk from unusual but acceptable behaviour.
Components used
- Predictive models
Estimate fraud probability, chargeback risk, payment failure risk and likely customer legitimacy.
- Behavioural Dynamics ↗
Reads transaction sequence, session behaviour, velocity, device pattern, payment history and customer movement.
- Noise Resilience ↗
Stops weak or isolated signals from becoming an automatic decline.
- Risk Stratification ↗
Separates trusted payments, uncertain payments, high-risk payments and urgent blocks.
- Policy Dynamics ↗
Controls what can be approved, stepped up, held, declined or reviewed.
Step-up is used only when it can save the sale
Extra authentication can stop fraud. It can also kill conversion. The point is to know when step-up improves the outcome and when it only adds friction.
Decision Deck decides whether the payment can proceed, needs step-up or needs to stop.
Components used
- Predictive models
Estimate fraud risk, step-up success likelihood and abandonment risk.
- Recommendations Block ↗
Selects the best action: approve, step up, hold, route to review, decline or monitor.
- Policy Dynamics ↗
Sets step-up rules by transaction value, customer state, merchant, geography, payment method and risk tolerance.
- Behavioural Dynamics ↗
Reads whether the session looks like genuine customer friction or risk-bearing behaviour.
- Monitoring
Tracks where step-up improves approval and where it creates avoidable drop-off.
Merchant and basket context change the decision
The same payment risk score does not mean the same thing everywhere. A high-value electronics basket, a digital goods purchase, a repeat grocery order and a trusted merchant transaction have different risk and margin consequences.
Decision Deck screens the payment in the context of the merchant, basket, customer and channel.
Components used
- Matching Block ↗
Connects the customer, card, device, merchant, basket, account, address and previous transaction history.
- Risk Stratification ↗
Separates low-risk merchants, watchlist merchants, high-risk categories and high-consequence baskets.
- Predictive models
Estimate fraud and dispute risk using merchant, basket and customer context together.
- Policy Dynamics ↗
Applies rules by merchant category, product type, payment method, channel and risk appetite.
- Evidence Vault ↗
Records which context changed the decision.
Make scheme and chargeback headroom a live control
Payment teams need conversion, but they also live inside fraud and chargeback thresholds. If controls are too tight, revenue is lost. If controls are too loose, scheme exposure, reserves and monitoring pressure rise.
Decision Deck adjusts screening logic based on real headroom, not static fear.
Components used
- Forecasting
Predicts fraud, dispute and chargeback movement over the next 30, 60 and 90 days.
- Risk Stratification ↗
Separates merchants with usable headroom from merchants approaching limits.
- Policy Dynamics ↗
Defines when screening can loosen, when it must tighten and when risk tolerance is exhausted.
- Simulation
Tests the impact of changing thresholds on conversion, fraud and chargeback exposure.
- Monitoring
Shows whether the change improved conversion without breaching risk appetite.
Review teams get the payments that need judgement
Manual review is costly and in payments it is often too slow. Review needs to be limited to cases where judgement can change the outcome.
Decision Deck routes only the payments that need human attention.
Components used
- Case Triage ↗
Prioritises payments by value, risk, uncertainty, customer consequence and time sensitivity.
- Exception Handling ↗
Captures cases outside the safe automated path.
- Recommendations Block ↗
Suggests the reviewer action: approve, step up, hold, decline, request evidence or escalate.
- Policy Dynamics ↗
Defines when review is mandatory and when override is allowed.
- Evidence Vault ↗
Gives the reviewer the risk drivers, policy context and decision history.
Screening changes become measurable before they go live
A fraud rule can change approval rates overnight. A threshold change can lift conversion, increase chargebacks or flood review teams.
Decision Deck tests screening changes before they hit live payments.
Components used
- Simulation
Tests new rules, thresholds, step-up strategies and merchant controls against historical and live payment populations.
- Predictive models
Estimate impact on approval, fraud, chargebacks, review volume and customer drop-off.
- Policy Dynamics ↗
Versions payment screening rules and supports controlled rollout or rollback.
- Monitoring
Tracks the effect after deployment.
- Evidence Vault ↗
Links every payment decision to the active policy, model and rule version.
Let more good payments through
Decision Deck helps payment teams approve more genuine transactions, reduce false declines and control fraud and chargeback exposure.
Use it to screen payments with better context, better routing and stronger decision evidence.