Forensics

Forensic Analytics & Behaviour Analysis for Regulated Environments

In highly regulated sectors such as banking and financial services, security and compliance depend on the ability to understand, monitor, and explain behaviour across complex digital systems.
Alice Data Science provides forensic analytics and behavioural analysis solutions designed to support regulatory compliance, risk management, and enterprise security.

Behaviour Analysis for Banking and Financial Institutions

Modern banking systems generate vast volumes of logs and digital traces across applications, networks, access controls, and transaction platforms. Hidden within these data are behavioural patterns that may indicate risk, misuse, or non-compliance.

Typical applications include:

  • Analysis of user and operator behaviour across systems
  • Detection of anomalous or inconsistent access patterns
  • Identification of deviations from established operational baselines
  • Early signals of insider risk, misuse, or procedural violations

Value: proactive risk detection and stronger compliance posture.

Alignment with Circulare n.285 Banca d’Italia anno 2013 and Subsequent Regulatory Updates

Alice Data Science’s forensic and behavioural analytics approach is designed to support compliance with the Supervisory Provisions for Banks issued under Circular No. 285 of the Banca d’Italia, as subsequently updated and integrated over time.
In particular, our methodologies are aligned with the principles governing internal controls, ICT risk management, operational continuity, and traceability of processes and decisions.

Behaviour analysis and advanced log analytics contribute to:

  • Strengthening the second- and third-level control functions through continuous, data-driven monitoring
  • Supporting ex post and ex ante controls on user activities, system access, and operational processes
  • Enhancing auditability and evidentiary robustness, in line with supervisory expectations
  • Providing structured analytical support for risk assessment, incident analysis, and remediation processes

By transforming log data into interpretable and documented analytical outputs, organizations can demonstrate a systematic and proportionate approach to ICT and operational risk, consistent with the evolving regulatory framework defined by Circular 285 and its subsequent amendments, as well as with broader European requirements on cybersecurity and operational resilience.

Log Analysis as a Security and Compliance Asset

Logs are not only technical artifacts, but forensic evidence and strategic assets.

Alice Data Science supports organizations in:

  • Correlating logs from heterogeneous systems (applications, networks, IAM, endpoints)
  • Identifying hidden regularities and cross-system inconsistencies
  • Detecting weak signals that traditional rule-based monitoring may miss
  • Transforming raw logs into structured, interpretable intelligence

Value: improved visibility, traceability, and audit readiness.

Regulatory Alignment and Risk Reduction

Our forensic analytics approach is designed to support alignment with:

  • Italian and European banking regulations
  • Internal control and audit requirements
  • Cybersecurity and operational resilience frameworks
  • Progressive alignment with NIS / NIS2 requirements

By combining behavioural analysis with advanced analytics, organizations can demonstrate:

  • Continuous monitoring of critical systems
  • Early detection of security-relevant events
  • Documented and defensible analytical processes

Value: reduced regulatory exposure and stronger supervisory confidence.

AI-Driven Forensics with Human Oversight

Alice Data Science integrates AI and Machine Learning with Human-in-the-Loop principles to ensure that forensic results remain interpretable, defensible, and actionable.

This includes:

  • Anomaly detection guided by behavioural baselines
  • Unsupervised discovery of previously unknown patterns
  • Supervised models for known risk scenarios
  • Human validation for high-impact findings

Value: advanced analytics without loss of control or accountability.

From Reactive Security to Predictive Control

Traditional security models react to incidents.
Forensic behaviour analysis enables organizations to move toward predictive and preventive security, where risks are identified before they escalate into incidents or regulatory breaches.

Alice Data Science helps banks and enterprises transform log data into a strategic security capability, supporting compliance, resilience, and long-term trust.