Explore intelligence models for security and investigations. Learn about information collection, analysis, networks, sources, threats, and operational decisions. Strengthen intelligence awareness, case planning, and strategic responses today clearly.
The BEHAVE Investigative Framework by Alan Elangovan helps investigators connect behaviour, evidence, motive, timeline, vulnerability, risk, and findings. It supports fair, structured, evidence-based investigations by reducing bias, improving risk assessment, strengthening report writing, and helping investigators reach clear, defensible conclusions across criminal, workplace, school, healthcare, and security cases.
The Mica Endsley Situational Awareness Model explains perception, comprehension, and projection of environmental elements in dynamic settings. It helps investigators maintain awareness, anticipate developments, and make informed decisions, enhancing operational effectiveness, risk management, and response capabilities in complex investigative and security environments.
The Red Team Analysis Model, rooted in Military Strategy and intelligence practice, challenges assumptions by adopting an adversary perspective. It helps investigators identify vulnerabilities, test strategies, and anticipate threats, strengthening decision-making, reducing bias, and improving operational readiness in complex investigative and security environments.
The Intelligence Failure Analysis Model, grounded in Intelligence Analysis practice, examines why intelligence breakdowns occur. It analyses cognitive biases, information gaps, and organisational issues, helping investigators identify weaknesses, improve analytical processes, and prevent future failures, strengthening decision-making, accountability, and effectiveness in intelligence and investigative operations.
The Investigative Cycle Model, grounded in Investigative Practice, outlines a structured process from information gathering to analysis, action, and review. It helps investigators manage cases systematically, ensure evidence-based decisions, and continuously refine strategies, supporting effective, accountable, and adaptable investigations across diverse operational contexts.
The Paul Brantingham and Patricia Brantingham Environmental Criminology Integration Model combines spatial, behavioural, and environmental factors to analyse crime patterns. It integrates routine activity, crime pattern, and rational choice perspectives, helping investigators understand offender movement, identify hotspots, and design targeted prevention and investigative strategies.
The Pierre Margot Forensic Intelligence Model integrates forensic science with intelligence analysis to support proactive investigations. It uses trace evidence, patterns, and data interpretation to identify links between crimes, support decision-making, and enhance crime prevention, moving beyond traditional reactive forensic approaches toward strategic investigative intelligence.
The National Intelligence Model (NIM), developed by UK National Police, provides a structured approach to intelligence-led policing. It integrates data collection, analysis, and decision-making to prioritise threats, allocate resources, and support strategic and tactical operations, enhancing effectiveness in crime prevention and investigative processes.
The Jerry Ratcliffe 3i Model (Interpret, Influence, Impact) supports intelligence-led policing by linking crime analysis to decision-making. It helps investigators interpret data, influence operational responses, and assess outcomes, ensuring intelligence is effectively used to guide strategies, reduce crime, and improve policing and investigative performance.
The Alan Elangovan ALAN Model integrates behavioural analysis, structured questioning, and situational awareness to guide investigations. It emphasises adaptive thinking, layered information gathering, and real-time assessment, enabling investigators to detect deception, interpret intent, and make precise, evidence-based decisions in complex investigative environments.
The Entrapment Avoidance Model, influenced by Criminal Law doctrine, ensures investigators do not induce individuals to commit offences they would not otherwise commit. It guides lawful conduct in undercover operations, preserving evidence integrity, protecting suspects’ rights, and ensuring investigations withstand legal scrutiny and judicial review.
The Undercover Operations Model, based on Law Enforcement practice, involves covert infiltration to gather evidence and intelligence. It focuses on identity creation, role immersion, and controlled engagement with suspects, enabling investigators to uncover hidden activities, disrupt criminal networks, and support prosecutions while maintaining operational security and legal compliance.
The Surveillance Detection Route Model, derived from Central Intelligence Agency tradecraft, focuses on identifying and evading surveillance through planned movement patterns. It enables investigators and operatives to detect hostile monitoring, confirm surveillance presence, and enhance operational security, supporting covert operations, counter-surveillance, and sensitive investigative missions.
The SIGINT Analysis Model, influenced by the National Security Agency, focuses on collecting and analysing electronic communications and signal data. It supports investigators in intercepting, decoding, and interpreting transmissions, enabling intelligence gathering, threat detection, and strategic decision-making in cyber, military, and national security investigations.
The HUMINT Collection Model, developed within the United States Intelligence Community, focuses on gathering intelligence through human sources. It involves recruitment, handling, and debriefing of informants to obtain valuable information, supporting investigations, threat assessments, and operational decision-making in security, law enforcement, and intelligence environments.
The OSINT Investigation Model, influenced by Michael Bazzell, focuses on collecting and analysing publicly available information from digital and open sources. It supports investigators in identifying leads, verifying identities, tracking activities, and gathering intelligence ethically, enhancing investigative efficiency in cyber, financial, and criminal investigations.
The MITRE Corporation ATT&CK Framework is a comprehensive knowledge base of adversary tactics, techniques, and procedures. It enables investigators to analyse cyber threats, map attacker behaviour, strengthen detection, and improve incident response, supporting intelligence-driven cybersecurity investigations and defence strategies across complex digital environments.
The Lockheed Martin Cyber Kill Chain Model outlines stages of a cyberattack, from reconnaissance to actions on objectives. It enables investigators to detect, analyse, and disrupt threats at each phase, strengthening cybersecurity, incident response, and forensic investigations through structured understanding of attacker behaviour and intrusion processes.
The Beneficial Ownership Analysis Model, guided by Financial Action Task Force standards, identifies the true individuals controlling assets or entities behind complex structures. It supports investigations into money laundering, corruption, and tax evasion by uncovering hidden ownership, enhancing transparency, and enabling effective enforcement and asset recovery actions.
The Asset Tracing Model, influenced by Financial Investigation practices, focuses on identifying, tracking, and recovering assets linked to criminal activity. It analyses financial trails, ownership structures, and transactions, enabling investigators to uncover hidden wealth, support prosecution, and facilitate asset recovery in fraud, corruption, and money laundering cases.
The Financial Profiling Model, influenced by Forensic Accounting practices, analyses financial behaviours, transaction patterns, and asset movements to detect irregularities. It supports investigators in identifying fraud, money laundering, and illicit enrichment, enabling evidence-based tracing of funds, financial reconstruction, and strategic decision-making in complex financial investigations.
The Stanley Wasserman and Katherine Faust Social Network Analysis Model examines relationships, structures, and interactions within networks. It helps investigators map connections, identify influential actors, detect hidden groups, and analyse information flow, supporting intelligence-led investigations, disruption of criminal networks, and strategic decision-making in complex investigative environments.
The Harrison C. White Network Analysis Model examines relationships and interactions within criminal networks. It identifies key actors, communication patterns, and influence structures, enabling investigators to disrupt organized crime, uncover hidden connections, and target critical nodes, enhancing intelligence-led operations and strategic decision-making in complex investigative environments.
The Lawrence W. Sherman Hot Spot Policing Model focuses on identifying and targeting high-crime areas where offences cluster. By concentrating police resources in these hotspots, it enhances deterrence, disrupts criminal activity, and improves public safety, supporting data-driven decision-making and effective deployment strategies in modern investigative and policing environments.
The Paul Brantingham and Patricia Brantingham Crime Pattern Theory explains how crimes occur based on offenders’ routine movements within familiar environments. It highlights nodes, paths, and edges that shape opportunities, helping investigators predict crime locations, understand spatial behavior, and design targeted prevention and enforcement strategies effectively.
The OODA Loop Model developed by John Boyd describes a rapid decision cycle of Observe, Orient, Decide, and Act, enabling individuals and organizations to adapt quickly, outpace adversaries, and maintain strategic advantage in dynamic, high-pressure environments.
The Intelligence Cycle Model developed by Sherman Kent describes a structured process of direction, collection, processing, analysis, and dissemination, enabling systematic production of actionable intelligence to support informed decision-making in security, policing, and national defense contexts.
The Follow-the-Money Model influenced by financial investigation practice traces the flow of funds across accounts, entities, and jurisdictions to uncover illicit activities, identify beneficiaries, establish evidential links, and support asset recovery, prosecution, and disruption of criminal financial networks.
The Money Laundering Cycle Model influenced by the Financial Action Task Force describes the three stages of laundering—placement, layering, and integration—highlighting how illicit funds are introduced, concealed, and legitimized, guiding detection, compliance, and prevention strategies in financial investigations.
The Threat Assessment Model influenced by the United States Secret Service evaluates potential threats by analyzing behaviors, intent, capability, and risk factors, enabling early identification, intervention, and prevention of targeted violence through structured, intelligence-driven assessment processes.
The Suspect Prioritization Matrix influenced by investigative practice ranks suspects using criteria such as motive, opportunity, capability, and evidence strength, enabling investigators to allocate resources effectively, focus inquiries, and systematically narrow down high-probability individuals in complex cases.
The Criminal Profiling Model developed by the FBI Behavioral Science Unit analyzes crime scene behavior, victimology, and patterns to infer offender characteristics, motivations, and traits, supporting investigative direction, suspect prioritization, and linkage of related crimes.
The Modus Operandi Analysis Model influenced by Hans Gross examines recurring methods, techniques, and procedures used by offenders, enabling investigators to identify patterns, link crimes, and anticipate offender behavior for effective investigative planning and crime prevention.
The Major Incident Room Model used by UK Police provides a structured framework for managing serious investigations, integrating HOLMES systems, information flow, task allocation, and documentation to ensure coordination, accountability, and efficient handling of major or complex cases.
The Incident Command System developed by Federal Emergency Management Agency and U.S. fire services provides a standardized, scalable structure for command, control, and coordination during incidents, enabling effective resource management, clear communication, and unified response across multiple agencies and jurisdictions.
The National Decision Model developed by the College of Policing provides a structured approach to decision-making, integrating information, risk assessment, powers, and ethical considerations to guide consistent, accountable, and proportionate actions in dynamic policing and investigative situations.
The Link Analysis Model influenced by Anacapa Sciences and IBM i2 visualizes relationships between people, events, and entities, enabling investigators to identify networks, patterns, and hidden connections, supporting intelligence-led investigations and strategic decision-making.
The Intelligence-Led Policing Model developed by Jerry Ratcliffe focuses on using data analysis, intelligence gathering, and risk assessment to guide proactive policing strategies, prioritize resources, and target high-risk offenders, locations, and criminal networks for effective crime prevention and control.
The Geographic Profiling Model developed by Kim Rossmo analyzes crime location patterns using spatial algorithms to predict an offender’s likely base, supporting investigative prioritization, resource allocation, and strategic decision-making in serial crime investigations.
