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Guard.ai
Risk and anomaly detection, simplified
Why monitoring and oversight need to evolve
The challenge
Organisations are managing growing transaction volumes, fragmented data, increasing regulatory expectations and greater scrutiny over costs and controls. Yet traditional monitoring approaches are often periodic, retrospective and rules-based, making it difficult to identify emerging risks or hidden patterns in a timely manner. In addition, high volumes of false positives can lead to wasted time and resources.
Complexity is increasing. Conventional approaches are limited. Hidden risks persist.
Introducing Guard.ai
Guard.ai enables proactive and continuous detection of risks and anomalies.
It provides organisations with an artificial intelligence (AI)-powered, scalable and data-driven approach to monitoring and oversight. Its advanced insights connect risk signals across transactions, third parties, employees and business processes to surface hidden anomalies, emerging risk patterns and underlying root causes invisible to conventional analysis.
Guard.ai generates value that often exceeds the cost of implementation.
Key benefits of Guard.ai
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Protect value
Reduce fraud, waste, abuse. Identify optimisation opportunities.
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Greater coverage
Analyse 100% of transactions to improve visibility into risks, controls and emerging trends.
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Improve decision-making
AI models prioritise anomalies for review based on associated risk.
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Do more with less
Targeted investigation of anomalies to focus efforts where they matter most.
How Guard.ai works
Guard.ai delivers cost-effective insights by detecting transaction anomalies in near real time. These insights are further enhanced through prompt-based analysis, enabling users to conduct sophisticated investigations using natural-language queries.
Key components:
Data integration
AI- driven hypothesis testing and risk calculation
Risk priortisation and alerting
Human-in-the-loop (HITL) and validation
Risk mitigation and value recovery
- Cloud platform agnostic
Supports deployment on Google Cloud (GCP), Microsoft Azure, and AWS.
- Strict data privacy
Enterprise contracts ensure zero data retention. Client data is never used for public model training.
- Intelligent models
Utilises advanced GPT models by default; architecture is fully portable to other LLMs.
Examples of how Guard.ai presents risks, anomalies and investigative insights to support decision making.
Customisable management dashboard
- High-risk anomalies prioritised automatically
- Trends and emerging risk patterns identified
- Financial leakage and optimisation opportunities highlighted
- Drill down from summary to transaction level
- Incorporates feedback loop from investigative analysis
Get in Touch
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