DECISION

INTELLIGENCE

What decision intelligence is and what it means for government organizations

8 min.

What is decision intelligence?

Decision intelligence is the application of AI and machine learning technologies, along with data fusion, data visualization and collaboration tools, to augment and improve decision making. The goal is not to replace humans, but rather to empower them to make faster and more accurate decisions. Decision intelligence platforms provide users a holistic, accessible view of all their organization’s data, and delivers actionable insights that would be virtually impossible to obtain through manual analysis.

Main Pillars of Decision Intelligence

Why is decision intelligence important?

While the idea of leveraging data to make better and more informed decisions is not new, with the increasingly sophisticated capabilities of bad actors, and the challenges of constantly evolving technology, the ability to make smarter, data-driven decisions has never been more crucial. Law enforcement, national security and other government personnel must make critical decisions in complex and uncertain situations. Faced with an information overload, it has become virtually impossible to fuse and make sense of all available data points in order to effectively assess potential risks and combat threats.

Traditional analytical tools tend to simply summarize trends or provide insights that are not actionable. Where more powerful analytics solutions are deployed, these tools are often only available to a limited group of data scientists or technical experts. One of the key principles of decision intelligence is data democratization making data and analytical insights accessible to both technical and non-technical subject matter experts, including analysts, investigators, and decision-makers. Data democratization empowers personnel to ask questions, challenge ideas and make use of on data-driven insights, rather than relying on historical trends or gut instincts in making key decisions.

What are the benefits of decision intelligence?

Law enforcement, security and public-sector organizations today have access to massive amounts of data and must make increasingly complex decisions. The source systems, analytical tools and personnel equipped to analyze data tend to be siloed, leading to time-consuming delays and critical gaps in information, when data is not shared promptly, or even at all. As a result, decision making is often characterized by inefficiencies, missed red flags, and biased analysis. 

Decision intelligence can help translate data into actionable insights, quickly and at scale – and deliver those insights in a timely manner to personnel making strategic, tactical, and operational decisions.

Benefits include:

  • Comprehensive big picture view of all available data, including unstructured data
  • Automating time-consuming and tedious manual data correlation and analysis
  • Uncovering hidden patterns and connections, detect anomalies, and predict trends
  • Minimizing biased analysis and critical thinking blind spots
  • Enabling collaborative teamwork and seamless information sharing
  • Reducing IT backlog with self-service analytics and reporting

What are decision intelligence platforms?

Decision intelligence platforms enable organizations to manage, fuse and analyze data from virtually any source, and are designed to easily scale to Big Data volumes. Decision intelligence platforms leverage key technologies, including data fusion, machine learning and AI, as well collaboration and data visualization tools.

When deploying decision intelligence platforms, a one-size-fits-all approach is unwise. While generic analytics solutions and AI technologies have powerful capabilities, an industry-specific, vertical approach to decision intelligence is more likely to lead to successful outcomes. This industry-specific approach is more effective, as organizations can benefit from solutions tailored to their unique data sources, investigations and use cases.

What are the key capabilities of decision intelligence platforms?

Best-in-class decision intelligence platforms provide key capabilities including:

  • Ingestion, storage and management of virtually all data types, via pre-built connectors, API or user upload, capable of scaling up seamlessly to Big Data volumes
  • Fusion of all data, including structured and unstructured sources, into one unified view
  • Automatic creation of holistic, multi-source profiles for all relevant entities
  • AI enrichment to extract insights from unstructured data, including text, audio, image and video
  • Data exploration and ad-hoc querying via dashboards and visual widgets, such as heat maps, timelines and link analysis, allowing users to view high-level summaries and drill down into granular data
  • Fine-grained permissions to keep sensitive data sources, investigations or documents restricted, plus data governance including auditing and data lineage capabilities
  • Dynamic data modeling with the flexibility to model and add new data sources without coding, in order to meet changing analysis and investigation needs
  • Automated analytical insights, generated by machine learning models, such as threat scoring, similarity prediction, and inferred relations
  • Seamless information sharing and collaboration within teams and across organizations, using investigation workspaces, messaging, and digital whiteboard
Key Capabilities of Decision Intelligence Platforms

Who are decision intelligence platforms for?

Decision intelligence is increasingly being adopted by large companies in the private sector to optimize business processes, including pricing, inventory management, supply chain planning, manufacturing and much more. According to the research firm Gartner, 33% of large organizations will use decision intelligence in their decision-making processes by 2023.

Government organizations such as law enforcement, intelligence, homeland security and customs agencies also stand to benefit from adopting decision intelligence.

  • Analysts and investigators use decision intelligence to conduct investigations, intelligence analysis and risk assessment.
  • Senior decision makers use decision intelligence to understand strategic trends, make key decisions regarding organizational focus, and optimize workforce and resource planning.
  • Data scientists and data engineers use decision intelligence to develop new machine learning models that are tailored to their organization’s data sources, investigations and use cases.

Decision intelligence platforms can be deployed in a dedicated fusion center staffed by all-source intelligence analysts, or can be deployed for the organization-wide use by multiple teams in an organization.

Decision intelligence platforms support multiple users cross-organization

How is decision intelligence used for investigations and intelligence analysis?

Decision intelligence empowers analysts and investigators to perform intelligence analysis and conduct investigations faster and more effectively across all domains, including, organized crime, drug trafficking, financial crime, terror and cyber-crime investigations. Whether conducting criminal investigations or intelligence investigations, Decision intelligence can help analysts and investigators in numerous ways, by generating new investigation leads, helping to prioritize which suspects to investigate, following the money trail, mapping the structure of criminal and terror organizations, and more.

How is decision intelligence used for risk management?

By replacing outdated risk assessment systems with advanced decision intelligence platforms, government organizations can improve the accuracy of customs and tax regulation enforcement, and can take a more efficient, targeted approach, leading to the discovery of more violations. With improved risk management, organizations can more effectively detect tax evasion, money laundering, and customs fraud and smuggling, and can boost revenue collection, optimize operations and increase case resolution rates.

How does decision intelligence leverage data fusion?

Government organizations have access to a multitude of data from disconnected, siloed data sources, both internal and external. These sources can include structured data, such as population registries, tax records, border crossing records, financial transactions, criminal records, and more. They also include unstructured data, including police reports, field agent reports, intelligence reports, and social media and web content — all of which arrive in various formats, including text files, audio files, images, videos, and device logs.

Decision intelligence platforms leverage data fusion technology to enable organizations to ingest their disparate and siloed data sets, aggregate them into a unified data pool, and align the data into a uniform format that can be easily queried. Then, through the process of entity resolution, all relevant data points belonging to the same entity are matched and fused together. The fusion of data into entities enables users to easily access a holistic, multi-source profile for each entity, whether a suspect, organization, vehicle, bank account, shipment, etc., and to see the relations between entities.

Decision intelligence platforms automatically fuse disparate data sources into multi-source entities and map the relations between them

How does decision intelligence leverage data visualization?

Decision intelligence platforms leverage data visualization tools and widgets, including visual link analysis, heatmaps, timelines and more, to query and explore complex data in an intuitive, easy-to-use manner. Analysts and investigators can easily see high-level trends and aggregated metrics, and drill down into a granular view of the data with one click.

How does decision intelligence leverage machine learning?

Decision intelligence leverages machine learning models to effectively surface patterns and predict trends, thus accessing insights that analysts and investigators would likely have missed.

Machine learning algorithms can perform unsupervised learning, which entails searching for and uncovering patterns in data, with no need for a human to define what to look for ahead of time. Machine learning algorithms can also make predictions based on historical data, without a human telling the model how to provide such predictions.

Both capabilities can contribute valuable insights for investigations, intelligence analysis and risk management. For example, when investigating an incident, such as a bombing or arson attack, incidents with similar characteristics can be automatically surfaced to the investigator who can then examine whether they are related and whether the same bad actors were involved.

How does decision intelligence leverage predictive analytics?

Decision intelligence leverages predictive analytics to make predictions and model likely outcomes, enabling investigators and analysts to make more accurate decisions. Predictive analytics uses statistical algorithms and supervised machine learning techniques to identify the likelihood of future outcomes based on historical data. This enables investigators and analysts to take a more proactive, data-driven approach to decision making, by predicting the answers to questions such as:

  • Where is the next attack likely to take place?
  • Which online followers of a radical extremist group are likely to conduct violent attacks?
  • Which brokers or import/export companies are likely to engage in customs fraud?
  • Which travelers entering a country are likely to overstay their visas, smuggle contraband or engage in drug trafficking?

What is the difference between decision intelligence and AI?

Decision intelligence is the practical application of artificial intelligence (AI) to specific decision-making processes, alongside data visualization, data fusion, collaboration tools and other technologies. An AI system can go beyond traditional analytics by autonomously making assumptions, querying data, performing tests, learning from data, and optimizing processes, all without human intervention.

Decision intelligence platforms leverage AI in numerous ways, which include extracting intelligence from text, audio, image, and video files. AI-powered engines can perform face detection, face recognition, object tagging, transcription of audio content to text, and detection of image-inferred relations.

The AI domain is broad, encompassing machine learning, traditional rules-based systems, different optimization techniques, natural language processing and graph technologies. Decision intelligence leverages the concept of composite AI, which is the combined application of different AI techniques to improve learning efficiency, including the ability to solve a wide range of investigation and intelligence questions.  A vertical approach to AI, which is industry and domain-specific, will ultimately be more successful in achieving the desired outcomes for an organization. With this approach, organizations leverage solutions tailored to their unique data sources, investigations and use cases, rather than relying on generic technologies and platforms.

What is the difference between decision intelligence and data science?

Decision Intelligence platforms can empower data science teams by providing them a unified pool of all relevant data sources and a platform on which to flexibly tailor and run new machine learning models that are tailored to the organization’s unique data sources, investigation types and use cases.


Decision Intelligence platforms encompass the functionality of multi-persona Data Science and Machine Learning (DSML) platforms which provide the tools and data sandboxes needed by expert data science teams for their specialized work, while also providing a low-code/no-code user experience to non-technical users that have a limited background in data science but have significant subject matter expertise and require the ability to analyze data and access analytical insights.

How does decision intelligence accelerate customs risk management and investigations?

Decision intelligence can provide valuable assistance to investigators and analysts engaged in customs risk management and customs investigations. Decision intelligence platforms empower organizations to make data-driven decisions that they would likely be unable to make using outdated business rules and risk assessment engines. In turn, data-driven decisions lead to increased customs revenue collection, improved detection of customs fraud and smuggling, and optimization of the customs clearance process.

Customs Fraud & Tax Evasion Case Study

How does decision intelligence accelerate AML and financial fraud investigations?

Decision intelligence can help government agencies accelerate anti-money laundering, fraud and tax evasion investigations. With the ability to analyze massive volumes of diverse data sources, decision intelligence platforms can automatically surface suspicious activities, detect anomalies and reveal hidden connections between companies, people and financial accounts, in order to assist analysts and investigators in uncovering financial crimes and tracking down the key ringleaders responsible.

How does decision intelligence accelerate criminal investigations?

Leveraging a decision intelligence platform can accelerate the work of investigators and analysts conducting a criminal investigation. Decision intelligence platforms can enable law enforcement agencies to resolve cases faster, predict crime trends more accurately, and detect potential threats. Decision intelligence platforms empower authorities to take an intelligence-led policing approach, based on data-driven decision making, rather than gut instinct or outdated practices.

How does decision intelligence accelerate terror investigations?

National Security and Homeland Security agencies are often overwhelmed with data when conducting terror investigations, as extremists and bad actors use increasingly sophisticated methods for recruitment, fundraising and communications. Decision intelligence platforms enable analysts and investigators to contend with information overload, and extract critical insights from vast amounts of data, in order to identify potential terror threats, score suspects based on risk level, develop comprehensive profiles of suspects, and generate new investigation leads.

How does decision intelligence accelerate drug trafficking investigations?

Law enforcement organizations combatting drug trafficking must uncover and disrupt cross-border webs of criminal activities along the entire supply chain – from the sourcing of raw materials to the production of illicit drugs, the distribution of the final product, and the laundering of profits. Decision intelligence platforms enable authorities to fuse data from disconnected sources, to employ machine learning to uncover hidden connections between people, criminal groups, shell companies, bank accounts and other entities, and to map organizational structures and key ringleaders.

Learn more about the NEXYTE decision intelligence platform

NEXYTE is a decision intelligence platform built for government agencies that enables investigators and analysts to make faster and more accurate decisions. NEXYTE empowers authorities to rapidly assess risks, conduct investigations, mitigate threats, boost revenue collection and optimize resources across multiple domains and types of investigations, including organized crime, financial crime, cybercrime, customs and terror, all in one platform.  

NEXYTE Decision Intelligence Platform

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