GITNUXSOFTWARE ADVICE
Consumer RetailTop 10 Best Loss Prevention Software of 2026
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
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Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Riskified
Adaptive risk decisioning for real-time transaction approval, review, or decline
Built for ecommerce merchants needing automated chargeback reduction and dispute-ready workflows.
Shyft Analytics
Shrink risk scoring that prioritizes investigations by anomaly strength and location
Built for retail loss prevention teams needing analytics-driven shrink detection and investigations.
Verkada
AI video search across sites with event context from access and alarms
Built for mid-market retailers using Verkada hardware for fast video-driven loss investigations.
Comparison Table
This comparison table evaluates loss prevention software options including Riskified, Shyft Analytics, Verkada, 3M Cogent, and SenNet alongside other platforms used for fraud detection, chargeback reduction, and operational risk monitoring. It summarizes core capabilities, deployment patterns, and integration considerations so you can map each tool to your use case and compare vendors with the same criteria.
| # | Tool | Category | Overall | Features | Ease of Use | Value |
|---|---|---|---|---|---|---|
| 1 | Riskified Uses AI to detect and stop fraudulent orders and account abuse across ecommerce to reduce chargebacks and losses. | fraud intelligence | 9.2/10 | 9.4/10 | 8.3/10 | 8.1/10 |
| 2 | Shyft Analytics Provides retail loss prevention analytics that fuse point-of-sale, inventory, and operational signals to prioritize shrink investigations. | retail analytics | 7.6/10 | 8.2/10 | 7.1/10 | 7.8/10 |
| 3 | Verkada Centralizes video surveillance and access control so teams can investigate incidents and reduce theft with searchable footage and alerts. | video surveillance | 8.4/10 | 9.0/10 | 8.2/10 | 7.6/10 |
| 4 | 3M Cogent Delivers retail intelligence for loss prevention using analytics and video-based detection to reduce shrink in stores. | retail detection | 7.2/10 | 7.6/10 | 6.9/10 | 7.1/10 |
| 5 | SenNet Consolidates surveillance and operational data to support loss prevention workflows, evidence collection, and case management. | case management | 7.3/10 | 7.6/10 | 7.1/10 | 7.0/10 |
| 6 | Caper Systems Helps retailers and brands prevent inventory loss by using autonomous computer vision to detect suspicious behavior and theft. | computer vision | 7.6/10 | 8.2/10 | 7.1/10 | 6.8/10 |
| 7 | VISTA Supports loss prevention teams with inventory analysis, exception reporting, and investigative workflows across retail environments. | shrink analytics | 7.4/10 | 7.6/10 | 7.1/10 | 7.5/10 |
| 8 | Aera Technology Uses enterprise loss prevention analytics and risk scoring to prioritize investigations for theft and operational shrink. | risk scoring | 7.4/10 | 7.2/10 | 7.6/10 | 7.3/10 |
| 9 | Agent Video Intelligence Applies AI to video streams to detect and alert on loss prevention events so teams can respond faster. | video analytics | 7.3/10 | 7.6/10 | 7.0/10 | 7.8/10 |
| 10 | Openpath Manages mobile access control and door permissions to reduce unauthorized entry that can lead to internal loss events. | access control | 7.1/10 | 7.2/10 | 8.0/10 | 6.6/10 |
Uses AI to detect and stop fraudulent orders and account abuse across ecommerce to reduce chargebacks and losses.
Provides retail loss prevention analytics that fuse point-of-sale, inventory, and operational signals to prioritize shrink investigations.
Centralizes video surveillance and access control so teams can investigate incidents and reduce theft with searchable footage and alerts.
Delivers retail intelligence for loss prevention using analytics and video-based detection to reduce shrink in stores.
Consolidates surveillance and operational data to support loss prevention workflows, evidence collection, and case management.
Helps retailers and brands prevent inventory loss by using autonomous computer vision to detect suspicious behavior and theft.
Supports loss prevention teams with inventory analysis, exception reporting, and investigative workflows across retail environments.
Uses enterprise loss prevention analytics and risk scoring to prioritize investigations for theft and operational shrink.
Applies AI to video streams to detect and alert on loss prevention events so teams can respond faster.
Manages mobile access control and door permissions to reduce unauthorized entry that can lead to internal loss events.
Riskified
fraud intelligenceUses AI to detect and stop fraudulent orders and account abuse across ecommerce to reduce chargebacks and losses.
Adaptive risk decisioning for real-time transaction approval, review, or decline
Riskified stands out for using automated risk decisions to prevent chargebacks while maintaining conversion rates. It provides adaptive fraud and abuse detection that flags suspicious transactions and routes actions through configurable workflows. Its loss prevention approach combines device, behavioral, and merchant signals to reduce disputes tied to account takeover and policy abuse. For merchants, the platform supports dispute and evidence workflows that aim to improve win rates after a suspicious purchase is identified.
Pros
- Automated transaction decisioning reduces chargebacks without heavy manual review
- Adaptive signals like device and behavior improve detection over time
- Dispute support helps teams increase evidence quality and win rate
Cons
- Advanced configuration often requires specialist onboarding and ongoing tuning
- Costs can rise quickly for high-volume merchants with strict review thresholds
- Less suitable for teams wanting fully self-built rules without vendor models
Best For
Ecommerce merchants needing automated chargeback reduction and dispute-ready workflows
Shyft Analytics
retail analyticsProvides retail loss prevention analytics that fuse point-of-sale, inventory, and operational signals to prioritize shrink investigations.
Shrink risk scoring that prioritizes investigations by anomaly strength and location
Shyft Analytics stands out for using retail loss prevention analytics to surface actionable shrink risks from transaction and operational signals. Core capabilities focus on identifying anomalies, monitoring high-risk locations and behaviors, and supporting investigation workflows with prioritized alerts. The system is designed to help teams reduce internal and external shrink by combining detection rules with review-ready reporting. It also supports audit trails so investigators can trace why alerts were triggered and what outcomes were recorded.
Pros
- Prioritized shrink alerts based on transaction and operational anomalies
- Investigation support with review-ready reporting for root-cause analysis
- Audit trails connect investigations to the signals that triggered alerts
- Monitoring supports targeting high-risk locations and behaviors
Cons
- Alert tuning and rule setup can require analyst effort
- Reporting depth depends on the quality of connected data sources
- Workflow configuration can feel complex for small teams
- Limited transparency into how every detection rule is derived
Best For
Retail loss prevention teams needing analytics-driven shrink detection and investigations
Verkada
video surveillanceCentralizes video surveillance and access control so teams can investigate incidents and reduce theft with searchable footage and alerts.
AI video search across sites with event context from access and alarms
Verkada stands out with a unified physical security platform that links camera, access, and alarm signals for loss prevention investigations. It provides AI-assisted video search across supported Verkada cameras plus configurable alerts for events like people loitering and unauthorized access. Investigators can build timelines from footage and export evidence for internal review or law enforcement handoff. The platform also supports location-based analytics and role-based access for guard teams and managers.
Pros
- AI-assisted video search accelerates investigations across multiple sites
- Unified access and camera context reduces missed incident details
- Role-based permissions support secure evidence handling for teams
- Centralized alerting helps standardize response for loss events
Cons
- Best capabilities depend on using Verkada hardware at sites
- Advanced investigation workflows can feel complex for small teams
- Per-user and enterprise requirements raise total cost for deployments
- Deep customization of detection logic may be limited versus DIY stacks
Best For
Mid-market retailers using Verkada hardware for fast video-driven loss investigations
3M Cogent
retail detectionDelivers retail intelligence for loss prevention using analytics and video-based detection to reduce shrink in stores.
Investigation workflow management that ties documented cases to measurable shrink prevention outcomes
3M Cogent focuses on loss prevention through analytics-driven operational workflows tied to retail execution. Its core capabilities include case management, investigative documentation, and performance reporting to support shrink reduction programs. The system also supports field and back-office teams with standardized processes for documenting incidents and outcomes. It is best suited to organizations that want centralized visibility into loss risk signals and documented investigations rather than ad hoc spreadsheets.
Pros
- Strong incident case management with structured investigation records
- Analytics and reporting for tracking loss prevention outcomes over time
- Standardized workflows help reduce inconsistency across store teams
Cons
- Setup and configuration can require meaningful implementation effort
- User experience depends on role design and permissions configuration
- Reporting depth may require training to interpret effectively
Best For
Retail loss prevention teams standardizing investigations and reporting across locations
SenNet
case managementConsolidates surveillance and operational data to support loss prevention workflows, evidence collection, and case management.
Investigation workflow that links incidents to evidence, actions, and final outcomes
SenNet focuses on loss prevention workflow automation by turning alerts into assignable investigations and documented outcomes. It supports incident capture, evidence collection, and case management so LP teams can standardize how shrink risks get reviewed. The system ties investigations to actions and reporting so managers can track repeat issues and process failures. It is best suited to teams that need consistent LP case handling rather than only static dashboards.
Pros
- Case management turns alerts into trackable loss prevention investigations
- Evidence gathering supports consistent documentation for investigations and reviews
- Workflow structure helps standardize LP processes across locations
Cons
- Setup and workflow tuning take time to match store-specific LP practices
- Reporting depth can feel limited versus enterprise LP suites with advanced analytics
- User training may be required to maintain consistent evidence and outcome tagging
Best For
Retail or multi-site LP teams standardizing investigations with workflow automation
Caper Systems
computer visionHelps retailers and brands prevent inventory loss by using autonomous computer vision to detect suspicious behavior and theft.
Loss investigation case management that links incident documentation to captured video evidence
Caper Systems stands out for loss prevention workflows that combine video evidence with structured case management for retail investigations. The platform supports incident creation, documentation, and investigator collaboration so teams can turn surveillance findings into auditable cases. It also provides tagging and search across captured events, helping LP teams locate patterns without manually reviewing long video timelines. Caper is most effective when your organization needs standardized case workflows tied to store operations and camera footage rather than standalone video-only review.
Pros
- Case workflows tie incidents to video evidence for investigation trails
- Structured documentation reduces inconsistency across investigators and regions
- Search and tagging speeds up locating relevant events across stores
Cons
- Setup and rollout take time due to workflow standardization requirements
- LP teams may need process training to use documentation correctly
- Value can drop for small teams that only need lightweight video review
Best For
Retail loss prevention teams standardizing video-backed incident investigations and reporting
VISTA
shrink analyticsSupports loss prevention teams with inventory analysis, exception reporting, and investigative workflows across retail environments.
Loss case management with evidence-backed incident tracking and investigation workflows
VISTA stands out by focusing loss prevention operations around actionable case management workflows. The system supports investigations, evidence handling, and incident tracking so teams can standardize how they document shrink and policy breaches. It also provides analytics that help managers spot recurring patterns across locations and time periods. Overall, VISTA is built for teams that want to connect field reporting to measurable prevention outcomes.
Pros
- Structured incident and case workflows for consistent loss investigations
- Evidence organization supports faster review and audit readiness
- Analytics highlight trends across locations and time for prevention planning
- Designed for LP teams managing recurring claims and policy exceptions
Cons
- Workflow setup can require admin effort to match local LP processes
- Reporting customization is limited compared with enterprise governance suites
- User permissions and field entry rules need careful configuration
- Integrations may be constrained for teams needing broad retail tech stack connectivity
Best For
Retail loss prevention teams needing case tracking and pattern analytics for investigations
Aera Technology
risk scoringUses enterprise loss prevention analytics and risk scoring to prioritize investigations for theft and operational shrink.
Device-enabled incident intake that creates investigator-ready cases with evidence capture
Aera Technology focuses on loss prevention for multifacility retail by combining device-based incident reporting with action-oriented workflows. The system supports case creation for shrink, safety, and compliance events, then routes tasks to investigators and managers with measurable statuses. It emphasizes audit-ready documentation through timestamps, ownership, and evidence attachments tied to each case. The platform is strongest when teams need standardized investigations across store locations rather than ad hoc reporting.
Pros
- Case management workflow for incidents across multiple locations
- Task routing with clear ownership and status tracking
- Evidence attachments keep investigations audit-ready
Cons
- Limited visibility into loss analytics compared with top specialist LP suites
- Workflow customization can feel heavy for small teams
- Integrations beyond core incident handling are not a standout
Best For
Retail loss prevention teams standardizing store investigations and case documentation
Agent Video Intelligence
video analyticsApplies AI to video streams to detect and alert on loss prevention events so teams can respond faster.
Automated incident detection that converts video footage into searchable loss-prevention events
Agent Video Intelligence focuses on AI-driven video intelligence for loss prevention, using automated analysis to flag risk from recorded footage. It supports incident review workflows by turning video evidence into searchable, actionable events for investigations and store operations. Its core capabilities center on visual detection, alert generation, and evidence organization to speed up audit trails. It fits teams that want faster exception handling rather than manual scrubbing of long video timelines.
Pros
- AI-generated video events speed up investigation and exception review
- Searchable evidence reduces manual scrubbing across long recordings
- Supports loss-prevention workflows with investigation-ready incident context
- Helps standardize how teams capture and review visual evidence
Cons
- Setup and tuning can require time to match your store footage
- Advanced outcomes depend on camera coverage and footage quality
- Fewer out-of-the-box LP metrics than full PSIM suites
- Workflow customization may be limiting for complex enterprise processes
Best For
Retail loss prevention teams needing faster video incident triage and evidence review
Openpath
access controlManages mobile access control and door permissions to reduce unauthorized entry that can lead to internal loss events.
Role-based access schedules with detailed door audit logs for investigations
Openpath focuses on physical access and visitor control workflows that support Loss Prevention teams with role-based entry rules and audit trails. It centralizes permissioning for doors, users, and schedules through cloud-based management. The solution adds identity-linked access insights that help investigate incidents by connecting when a person had access to specific locations. It is strongest when loss prevention relies on access control processes rather than traditional case management or incident ticketing.
Pros
- Cloud-managed access rules with user and schedule based permissions
- Audit trails connect door access events to specific identities
- Fast deployment for small to mid-size sites needing controlled entry
Cons
- Loss Prevention features focus on access, not comprehensive case management
- Requires integration work for broader investigations across systems
- Hardware dependent setup can add ongoing operational complexity
Best For
Retail and multi-site teams using access control to reduce internal theft risk
Conclusion
After evaluating 10 consumer retail, Riskified stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Loss Prevention Software
This buyer's guide explains how to choose Loss Prevention Software that fits your store workflow, evidence needs, and incident outcomes. It covers ecommerce chargeback prevention with Riskified, retail shrink investigation analytics with Shyft Analytics, and physical security evidence workflows with Verkada and Openpath. You will also get concrete guidance on case management options like SenNet, 3M Cogent, Caper Systems, VISTA, and Aera Technology, plus AI video event triage with Agent Video Intelligence.
What Is Loss Prevention Software?
Loss Prevention Software helps teams detect loss risk, turn signals into investigations, and manage evidence and outcomes across stores, sites, or channels. It reduces chargebacks, shrink, and policy exceptions by routing incidents to responsible owners and capturing audit-ready documentation. Ecommerce teams typically use Riskified to make real-time approve, review, or decline decisions for suspicious transactions and chargeback reduction. Retail teams use tools like Shyft Analytics to score shrink risk and prioritize investigation work tied to investigation-ready reporting.
Key Features to Look For
Loss prevention tools should align detection signals with investigation workflows and evidence so teams can act fast and document outcomes consistently.
Real-time risk decisioning with configurable approval or review actions
Riskified excels at adaptive risk decisioning that routes each transaction to approval, review, or decline so chargeback exposure is reduced without blanket manual review. This decision workflow matters most for ecommerce teams that need immediate fraud and account abuse responses.
Shrink risk scoring that prioritizes investigations by anomaly strength and location
Shyft Analytics provides shrink risk scoring that ranks alerts by anomaly strength and location so investigators handle the highest-impact cases first. This prioritization supports faster root-cause work when you are targeting high-risk locations and behaviors.
AI video search that connects footage to event context from access and alarms
Verkada stands out with AI-assisted video search across sites and event context from alarms and access signals so investigators can build timelines quickly. This is valuable when video evidence alone is too slow to review across multiple locations.
Case management that links incidents to evidence, actions, and final outcomes
SenNet provides investigation workflow automation that links incidents to evidence, assigned actions, and recorded outcomes. Caper Systems also ties incident documentation to captured video evidence so investigations remain auditable across investigators and regions.
Investigation workflow management that standardizes documented shrink prevention outcomes
3M Cogent focuses on standardized investigation workflow management that ties documented cases to measurable shrink prevention outcomes. This matters for organizations that need consistency across store teams and performance tracking over time.
Device-enabled incident intake with evidence attachments and audit-ready case ownership
Aera Technology emphasizes device-enabled incident intake that creates investigator-ready cases with evidence capture and audit-ready documentation via timestamps and ownership. Agent Video Intelligence complements this by converting video streams into searchable AI-detected events to speed up exception handling.
How to Choose the Right Loss Prevention Software
Pick the tool that matches your primary loss pathway, your evidence type, and your investigation workflow requirements.
Start with the loss type you need to prevent
If your primary loss is ecommerce fraud and chargebacks, Riskified is built for real-time transaction approval, review, or decline using adaptive signals from devices, behavior, and merchant context. If your primary loss is retail shrink, Shyft Analytics and VISTA prioritize investigations with shrink risk scoring and evidence-backed incident tracking tied to locations and time periods.
Choose the detection-to-action workflow you can operate
Riskified reduces manual review by routing transactions through configurable workflows, which fits teams that want automated decisioning at scale. For structured LP operations, SenNet and 3M Cogent turn alerts into standardized investigations with documented outcomes, which fits organizations that want consistent evidence handling across locations.
Match evidence handling to your investigation reality
If investigators need fast access to relevant footage, Verkada AI video search supports evidence discovery across sites and builds investigation timelines with event context from access and alarms. If your team relies on video evidence and needs auditable documentation, Caper Systems, Agent Video Intelligence, and SenNet connect incidents to captured or AI-detected video events for review-ready case work.
Validate that the tool supports audit-ready documentation and outcome tracking
Aera Technology ties cases to timestamps, ownership, and evidence attachments so documentation stays audit-ready from intake through resolution. SenNet, VISTA, and Shyft Analytics also support investigation trails and audit-ready reporting so managers can track repeat issues and process failures.
Assess rollout constraints and workflow complexity against your team size
If you need deep system tuning, Riskified can require specialist onboarding and ongoing configuration to keep thresholds aligned with your fraud patterns. If you need standardized LP case handling, 3M Cogent, SenNet, and Caper Systems can require workflow setup and role design work, which is usually harder for small teams without dedicated operations support.
Who Needs Loss Prevention Software?
Loss prevention software fits teams that must detect risky activity, run investigations, and document outcomes across stores, sites, or channels.
Ecommerce merchants reducing chargebacks tied to fraud and account abuse
Riskified is the best fit because it performs adaptive risk decisioning that routes suspicious transactions to approval, review, or decline and includes dispute support workflows for evidence-driven win-rate improvement. This is designed for teams that need automated transaction decisioning without relying on heavy manual review.
Retail loss prevention teams that need shrink analytics plus prioritized investigation alerts
Shyft Analytics is built for shrink risk scoring that prioritizes investigations by anomaly strength and location and includes audit trails connecting alerts to triggering signals. This fits teams that want analytics-driven targeting rather than ad hoc spreadsheets.
Mid-market retailers using Verkada hardware across multiple sites
Verkada fits teams that already deploy Verkada cameras and want AI video search plus event context from access and alarms for fast incident investigations. It also supports role-based permissions for secure evidence handling across guard teams and managers.
Multi-site LP teams standardizing investigations with evidence, actions, and repeat-issue tracking
SenNet provides investigation workflow automation that links incidents to evidence, assignable actions, and final outcomes with repeat issues tracked through consistent case handling. 3M Cogent also standardizes investigations by tying documented cases to measurable shrink prevention outcomes across locations.
Common Mistakes to Avoid
Buyers often choose tools that do not match their evidence sources or their ability to manage workflow tuning and case consistency.
Treating video tools as a substitute for standardized case outcomes
Agent Video Intelligence and Verkada can accelerate detection and searchable evidence, but loss outcomes still depend on investigation workflow discipline. Pairing video event discovery with case management like SenNet or Caper Systems prevents documentation gaps when investigators capture incidents and record final results.
Overlooking the operational effort required for alert tuning and workflow setup
Shyft Analytics can require analyst effort to tune alerts and set rules, and SenNet and 3M Cogent require workflow tuning to match store-specific LP practices. Riskified can also demand specialist onboarding and ongoing tuning when thresholds must adapt to changing fraud patterns.
Selecting a tool optimized for one loss pathway and expecting it to cover everything
Openpath is focused on mobile access and door permissions with audit trails, so it does not provide comprehensive loss case management across shrink investigations. If your program includes shrink claims and policy exceptions, tools like VISTA or Aera Technology provide evidence-backed incident tracking and standardized case documentation.
Ignoring hardware dependency and coverage constraints in AI detection performance
Verkada's best capabilities depend on using Verkada hardware at sites, and Agent Video Intelligence outcomes depend on camera coverage and footage quality. Caper Systems and SenNet reduce review friction by linking evidence to cases, but they still require camera and store process coverage to generate useful incidents.
How We Selected and Ranked These Tools
We evaluated Riskified, Shyft Analytics, Verkada, 3M Cogent, SenNet, Caper Systems, VISTA, Aera Technology, Agent Video Intelligence, and Openpath on overall capability fit, feature strength, ease of use, and value for LP operations. We rewarded tools that connect detection signals to investigation workflows and evidence so teams can act on alerts and document outcomes. Riskified separated itself by combining adaptive real-time risk decisioning for transaction approval, review, or decline with dispute-ready workflows for improving chargeback win rates. Tools lower in the list generally required more manual tuning effort or were more constrained to a narrower LP scope like access control in Openpath or hardware-dependent video performance in Verkada.
Frequently Asked Questions About Loss Prevention Software
How do Riskified and Shyft Analytics differ in where they find loss risk?
Riskified reduces ecommerce loss by making adaptive risk decisions on transactions using device, behavioral, and merchant signals that drive real-time approval, review, or decline workflows. Shyft Analytics targets retail shrink by scoring locations and behaviors from operational and transaction signals and prioritizing investigation alerts for LP teams.
Which tool best fits chargeback prevention and evidence workflows for ecommerce?
Riskified is built for chargeback reduction because it routes suspicious transactions through configurable workflows and provides dispute-ready evidence and documentation steps. It also uses adaptive risk decisioning to keep conversion rates stable while blocking higher-risk abuse patterns.
What should a retail LP team use for AI video triage instead of manual scrubbing?
Agent Video Intelligence generates searchable, actionable events from recorded footage so investigators can handle exceptions faster than reviewing long video timelines. Verkada also supports AI-assisted video search but pairs it with access and alarm context so investigations build timelines from multiple signal sources.
How do case management workflows compare across 3M Cogent, SenNet, and VISTA?
3M Cogent centers loss prevention on standardized case management, investigative documentation, and performance reporting tied to measurable shrink outcomes. SenNet turns alerts into assignable investigations with incident capture, evidence collection, and recorded outcomes for manager tracking. VISTA focuses on evidence-backed incident tracking plus analytics that surface recurring patterns across locations and time periods.
Which platform is strongest when video evidence must be tightly linked to incident documentation?
Caper Systems links surveillance findings to auditable cases by combining video evidence with structured case management, plus tagging and searchable event records. VISTA also emphasizes evidence handling and incident tracking so field reporting maps to standardized documentation and investigation workflows.
If your loss prevention relies on physical access control rather than incident tickets, which option fits?
Openpath is designed for access and visitor control workflows with role-based entry rules and cloud-managed door schedules. It connects access events to identities so LP investigations can trace when a person had access to specific locations.
How can Verkada improve investigations using event context beyond cameras?
Verkada unifies camera, access, and alarm signals so investigators can search AI-identified moments and build timelines with event context. Investigators can export evidence for internal review or law enforcement handoff while maintaining role-based access for guard teams and managers.
What workflow differences should teams expect between device-based incident intake and analytics-led investigations?
Aera Technology uses device-enabled incident intake that creates investigator-ready cases with timestamps, ownership, and evidence attachments for standardized store investigations. Shyft Analytics leans on shrink risk scoring and anomaly detection to prioritize investigations using prioritized alerts and audit trails for why alerts were triggered.
What are common implementation starting points for getting value from these platforms?
Riskified typically starts with mapping suspicious transaction and dispute workflows so adaptive risk decisions route actions into review or evidence steps. SenNet, 3M Cogent, and VISTA usually start by standardizing how investigators capture incidents, attach evidence, and record outcomes so reporting reflects the same process across locations.
Tools reviewed
Referenced in the comparison table and product reviews above.
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