Financial risks have nowhere to hide
Prebuilt and scalable algorithms continuously analyze all data, exposing risks through the contextual lens of an auditor, regulator, or bespoke internal controls.
Advanced machine learning
Out of the box algorithms find patterns in datasets without the need of supervision. The platform identifies data relationships and structures, surfacing patterns of unusual behavior that a human would never find.
Discover trends and risks otherwise unnoticed in your most important data, free from external influence and bias.
Process hundreds of millions of rows, offering greater risk coverage and overcoming traditional data volume challenges.
Transparent AI and clear documentation provides credible results, creating trust in your most critical financial data.
A unique ensemble AI approach
By leveraging multiple techniques simultaneously, enhance your ability to identify errors and anomalies, resulting in broader risk detection and coverage.
Data Systems and Sources
Data Systems and Sources
Conduct 100% transaction analysis to understand information flows and identify data sources within systems of record to ensure accurate and accessible data for better analysis.
Fraud and Anomaly Detection
Fraud and Anomaly Detection
Spot unusual patterns early to catch fraud before it escalates into major issues. By identifying irregularities, organizations can take proactive measures to protect your assets and reputation.
Aggregated Risk Management
Aggregated Risk Management
Analyze data from various angles to provide a comprehensive view of risks across the organization. This holistic perspective enables better risk assessment and more effective mitigation strategies.
Accelerated Transformation Initiatives
Accelerated Transformation Initiatives
Empower your organization to implement changes swiftly and successfully with out of the box insights. More accurate information is at your fingertips, driving transformation initiatives that align with your strategic goals.
Operational Efficiency
Operational Efficiency
Streamline processes and reduce inefficiencies leading to smoother and faster operations. By optimizing workflows, organizations can improve productivity and reduce costs.
Statistical Models
Statistical Models
Examine financial data with various statistical models to detect irregularities by comparing it to expected patterns. Techniques such as Benford's Law and linear regression are used to highlight deviations that may indicate potential errors, fraud, or anomalies.
Machine Learning
Machine Learning
Unsupervised machine learning models analyze changes in transaction amounts, rare interactions, and shifts in activity volume without predefined parameters. These models learn patterns from the data itself, dynamically detecting anomalies that may signal risks or irregularities in financial processes.
Business Rules
Business Rules
Customer defined criteria within financial or business processes that flag potential risks. These are hardcoded rules based on expert knowledge, helping quickly identify anomalies in data that trigger exceptions to expected patterns.
A unique ensemble AI approach
By leveraging multiple techniques simultaneously, enhance your ability to identify errors and anomalies, resulting in broader risk detection and coverage.
Traditional financial controls are antiquated and inflexible
Finance and audit teams can no longer keep up with the volume and velocity of data changes caused by digital transformation programs.
The challenge is multiplied by the ever-changing risk and regulatory compliance landscape. Companies struggle to keep up with the velocity of change.
Adaptable transaction oversight with AI-powered financial controls
Choosing MindBridge for anomaly detection offers quicker deployment, ongoing support, and proven effectiveness. This allows your team to leverage a robust, trusted solution without needing specialized machine learning expertise, enabling them to focus on higher value-added work.
Shortcomings of Traditional Approaches
1
Finance, Accounting, Operations
Errors in month-end close
Inaccurate budget forecast
Inefficient manual processes
Regulatory non-compliance
Unknown emerging risk
2
Control, SOX, Risk, Compliance, ERM
Lack of process automation
Ineffective controls testing
Subjective risk assessment
Manual control reliance
Limited scope
3
Internal audit, Investigations
Reactive IA planning
Limited detection coverage
Missed fraud indicators
Highly manual workload
Inconsistent results
Leveraging the MindBridge AI™ platform
Specify data set
MindBridge ingests complex and voluminous transactional data sources, including all relevant fields for analysis.
Algorithms you can trust
Ensemble AI leverages out of the box control points that combine your business rules, statistical models, and unsupervised machine learning.
Flags entries with amounts that do not align with the expected distribution of amounts.
Augmenting digital transformation
To grasp the significance of AI and ML in finance and accounting, it’s essential to understand their capabilities.
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