Appriss Intelligence

The only platform that sees the full picture of returns and shrink — and acts on it.

Built for retail loss leaders who can’t afford blind spots.

20+ years of retail transaction history — pattern recognition that only comes with time

Consumer identities stitched across cards, emails, addresses — in-store, online, and customer service

Cross-retailer consortium — a risk signal at one retailer follows the consumer to the next

Cases linked automatically across store locations — no manual hunting for connections

Systems in this layer

Consumer Identity Resolution

Consortium Model

Data Normalization

Case Linking

Address, Email, ID Validation

Core Model: Engage

In-Store Return Authorization

Scores every return transaction in real time and issues an Approve, Warn, or Decline decision at the POS — in under one second.

Protects margins and good customers automatically.

Core Model: Engage

Online Return & Claim Authorization

Return authorization for digital — online returns, online claims, and BORIS. Same real-time decisioning at every digital touchpoint.

Consistent protection in-store and online.

Core Model: Secure

Exception Detection

Builds peer-group baselines for every store and cashier, then flags statistical outliers automatically. No rules required.

Identifies areas of disproportionate loss.

Engage

Wardrobing Detection

Identifies buy-use-return patterns automatically — trained on behavioral fingerprints specific to this abuse type.

Catches one of the fastest-growing abuse types.

Engage

Tender Laundering Detection

Identifies manipulation of payment methods at return — cash purchases returned for store credit or gift cards to extract value. Flags it at scale.

Catches payment manipulation before value is extracted.

Engage

Discount Fraud Detection

Flags illegitimate discount and promo code patterns at return: coupon abuse, employee discount misuse, and fraudulent promo activity.

Protects margins for undetected discount fraud.

Engage

Incentive Optimization

Individual offer selection at return — selects the right incentive (exchange, store credit, or partial refund) to retain the customer and recover value.

Turns the return into a repeat purchase opportunity.

Built to be trusted

AI Governance & Data Principles

Enterprise procurement and compliance teams ask hard questions about AI. Here are ours — answered.

Human-in-the-Loop

All consequential outputs — return decisions, investigation narratives — support human review workflows. Retailers retain full control of final decision.

Fully Auditable

Every return authorization decision is fully auditable. Retailers can access factors that drove any decision for compliance, customer service, or legal review.

Data Security

All proprietary ML models are trained on Appriss' own historical data. No customer PII is used in model training. Cross-retailer signals are anonymized for consortium aggregation.

Demand-Triggered Retraining

Models are retrained on demand — triggered by performance, not fixed schedules — ensuring every model stays current with evolving risk patterns.

Formal Risk Classification

All production AI systems are formally risk-classified by our legal team, reflecting decision-making authority and potential customer impact.

All Proprietary

With the exception of address validation, every AI systems is built and maintained internally by Appriss' Data Science and Engineering teams.

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full picture of loss?

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The only platform that sees the full picture of returns and shrink — and acts on it.