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What is decision intelligence?
Decision intelligence (DI) is the application of AI to enhance decision-making across all areas of a business.
Decision intelligence supports nuanced decision-making at every level – strategic, operational, and tactical. It creates a trusted data foundation to provide confidence in tools such as artificial intelligence that help automate businesses and enable faster, more accurate decisions.
Decision intelligence supports transparent decision-making by letting you know how decisions are made, and how outcomes are evaluated, managed, and improved through deeper insights.
Context plus confidence: It’s this combination that gives you data with meaning, supports your decisions, and builds lower-cost business resiliency.
Trusted data foundation:
A trusted data foundation is essential to unlocking the value of data and achieving your organization's objectives, such as powering applications with high-quality data, enabling data-driven decision-making, enhancing customer experiences, reducing operational costs, phasing out legacy systems, improving regulatory compliance, and supporting AI-driven initiatives.
While the importance of a reliable data foundation is well-established, the technology available to build it is now more advanced than ever.
AI-powered contextual analytics:
Contextual analytics in a decision intelligence platform enhances decision-making by integrating data with its surrounding context to deliver deeper insights. By analyzing not just the raw data, but also the relationships, patterns, and external factors that influence it, contextual analytics allows organizations to make more informed and precise decisions. This approach helps to uncover hidden correlations, predict outcomes, and understand the broader implications of each decision. In a decision intelligence platform, contextual analytics is pivotal for enabling a holistic view of the data, allowing businesses to move beyond surface-level insights and address complex challenges with greater confidence.
Augmented and automated decisions
A decision intelligence platform leverages augmented and automated analytics to enhance the decision-making process, combining human expertise with advanced machine learning and AI-driven insights. Augmented analytics empower users by providing data-driven recommendations, uncovering hidden patterns, and offering predictive insights, all while maintaining a user-friendly experience. Automation within the platform streamlines repetitive tasks, accelerates data processing, and ensures consistency in decision-making, allowing organizations to focus on strategic initiatives.
Transformational outcomes
By building a trusted data foundation, you can achieve truly transformational outcomes.
A robust decision intelligence platform enables you to prepare, onboard, and connect all of your data with exceptional accuracy, regardless of scale or complexity.
Such a platform creates trusted views that reveal the relevant connections between data for any business challenge, providing true contextual insights that are invaluable for advanced analytics and AI initiatives.
Moreover, it empowers you to fully leverage your data, allowing you to build better-performing models and uncover hidden risks and opportunities throughout your organization.
Why is decision intelligence important for organizations?
Context is everything – especially in times of uncertainty and volatility. Organizations are making millions of decisions every day, but when they base those decisions on experience alone, the results can become disconnected from reality.
Data ensures decisions are based on facts, especially when automation is added to data – saving time and effort, and enabling a true digital experience for customers.
To make sound, data-driven decisions, you need the right data in the right context. Without it, there’s a domino effect that results from poor decision-making.
Decision intelligence enables private and public-sector organizations to go from “guess-work” recommendations and decisions to informed and confident ones derived from trusted data.
Running an efficient and resilient business is harder than ever before. And decision-making is becoming more demanding, with little margin for error.
Research from Gartner shows:
By 2024, one-third of large organizations will use decision intelligence for structured decision-making to improve competitive advantage and optimize efficiency. Decision intelligence was also named one of Gartner’s top strategic technology trends for 2022.
By the end of 2024, 75% of enterprises will be leveraging operational AI like machine learning and natural language processing (NLP) to provide powerful insights into operations and supply chains.
By 2026, 75% of Global 500 companies will apply decision intelligence practices, including the logging of decisions for subsequent analysis.
By 2028, 25% of CDAO vision statements will become “decision-centric,” surpassing “data-driven” slogans, with human decision-making behaviors explicitly addressed to improve D&A value.
A study from Bain show a 95% correlation between decision effectiveness and financial performance, and another survey from McKinsey reports that the average S&P 500 company wastes $250 million per year due to poor decision-making.
Indeed, a study by Oracle has found that 74% of employees and business leaders said the number of decisions they make every day has increased 10 times over the last three years, with 85% of them regretting, feeling guilty about or questioning a decision they made in the past year.
Respondents also reported feeling overwhelmed by the sheer volume of information they receive, and find it challenging to extract valuable insights from different dashboards and data analytics tools.
Here's some of the reasons it's harder to run an efficient and resilient business than ever before:
Using artificial intelligence, decision intelligence unlocks the power of entity resolution and graph analytics to turn data into accurate decisions at scale. This means that data becomes more than the sum of its parts – not piecemeal, siloed, and afflicted with poor quality. Entity resolution connects all data from previously siloed and scattered points, and creates a single, trusted, connected, and reusable resource.
What is the difference between decision intelligence and artificial intelligence?
Artificial Intelligence (AI) is a branch of computer science focused on creating systems or machines that can perform tasks typically requiring human intelligence. These tasks include learning from experience, recognizing patterns, solving problems, understanding natural language, and making decisions.
Decision intelligence puts AI to work by creating a trusted data foundation with AI-powered data ingestion, entity resolution and graph generation, and then running analytical and AI models to turn the data into insights for decision-making.
How does decision intelligence use artificial intelligence?
In today's fast-paced business world, decision-makers are often under intense pressure to make fact-based, consistent decisions in a hurry. This is why enterprises turn to technologies such as AI and machine learning (ML) to augment their decision-making capabilities.
The problem is that organizations often deploy these technologies without fully understanding the importance of placing the data they collect in context to gain the bigger picture of what data is being collected and how it is being applied to the decision-making process. Without context, AI predictions lack dependability, opening the door to a wide range of long-term automation challenges and other setbacks that can sink profits.
Entity resolution is what gives data context by connecting billions of data points spread across multiple systems into a single, accurate view that reflects the real-world connections between people, places, and organizations to create a single source of truth.
When it comes to employing AI and ML as part of the decision-making process, the quality of the data you use is everything. This is why data scientists are so tightly focused on using reliable, transparent data to make the best algorithms possible.
What are the critical components of a decision intelligence platform?
Decision intelligence platforms employ a new generation of software designed to automate or augment processes – empowering operational teams to make faster and more accurate strategic, tactical, and operational decisions.
By utilizing the power of artificial intelligence, these platforms connect billions of data points across internal and external data sources to provide a trusted and reusable data foundation enriched with vital intelligence about the relationships between real-world entities such as: people, organizations, events, and places.
Quantexa brings these capabilities together in its single Decision Intelligence platform to give organizations the ability to protect their most valuable assets, optimize their resources, and identify opportunities for growth by providing the tools. Quantexa's platform takes these three steps:
With multi-source data ingestion, you can rapidly onboard any source – internal, external, structured, or unstructured.
Using Entity Resolution, you can bring siloed, disparate, and messy data together at scale for accurate single views.
Continuously improve data quality as part of the unification process.
Reveal the relationships and context of how people, organizations, places, and other entities interact with each other.
Generate insights that build stronger, more meaningful analytical models.
Use open and easy-to-use tools and frameworks to make use of the full power of innovative graph, AI, and machine-learning methods.
Automate manual, high-volume operational decisions and maximize your investments in AI for efficiency and cost savings.
Transparent models mean each decision is explainable, with full visibility for security and regulatory requirements as well as model validation and optimization purposes.
Empower teams to proactively explore insights and act — making faster, more confident, and more accurate decisions.
The ideal decision intelligence platform should also integrate easily with your existing IT landscape and support flexible deployment options: native or containerized, for private and public cloud, to future-proof your business and its growing data needs.
This platform should also provide quick time-to-value through a modular approach, allowing you to expand your platform's capabilities as your business grows.
IDC MarketScape Recognizes Quantexa as a Decision Intelligence Leader
What are the decision intelligence platforms used for?
Decision intelligence platforms are used for decision-making across different industries and use cases, helping professionals with their everyday work. Some examples include:
Customer-facing teams
Relationship managers, Sales representatives and Customer support staff use data-driven insights for better customer experience, timely engagement and new sales opportunities.
Financial crime detection and prevention
Financial crime and Fraud analysts and investigators benefit from a truly connected and detailed view of risky behavior to detect and prevent fraudulent activity.
Business decision makers
Business decision makers use insights to understand trends, make predictions and support key decisions.
Data scientists and data engineers
Data scientists and data engineers can truly make a difference for their organization by using a decision intelligence platform to run accurate and trustworthy analytics.
What are the benefits of decision intelligence?
Onboarding the right decision intelligence platform empowers enterprises to use their massive databases more efficiently to:
Enhance data governance
Ingest large external datasets while meeting security and data privacy requirements.
Maximize your data
Make the most of data across multiple use cases with a single repository.
Make more informed decisions
Get a holistic view of an entity and its hidden connections to make more informed and accurate decisions at every level – strategic, tactical, and operational.
Increase investigative efficiency
Reduce workloads by using context to generate only high-quality alerts, reduce false positives, and reduce investigation time from weeks to hours.
Automate decisions and enable digital channels
Provide customers, suppliers, or citizens with the most accurate, real-time decisions or recommendations through digital channels, while reducing workloads and costs of operational staff.
Scale with simple integration
Augment and enhance in-house capabilities using an open architecture, which enables rapid scaling to accelerate risk detection across multiple lines of business including retail, markets, correspondent banking, and trade finance.
What industries can use decision intelligence technology?
Decision intelligence is being utilized by more and more businesses, but we've seen the first adopters within these key sectors.
Banking
The impact of new digital applications, processes, and business models is transforming the financial world. There’s fresh competition from fintech startups that threaten to siphon off customers and cut into revenues through more artificial intelligence automation and a lower cost base.
Consumers embrace of all things digital and mobile demands new products and new levels of service, with an expectation of real-time everything. These demands make it critical that financial organizations identify and manage emerging risks and opportunities while preserving the ability to quickly respond.
The right decision intelligence platform can provide unrivaled context through single views of customers and counterparties with rich graphs of their relationships, enabling banking and financial institutions to increase data availability, while maintaining privacy and security. Banks can also tap into the latest advancements in AI to empower digital transformation and enable confident, data-driven decisions and create a digitally resilient, cost-effective organization.
Insurance
The insurance industry’s increasing effort to meet changing customer expectations is driving rapid digital transformation. “Going digital” puts a greater focus on using complex customer data in near real-time to manage risk and offer competitive services to potential customers.
With the continued focus on loss ratios, operational expenses, and providing better customer service, the pressure is on insurance organizations to unlock value from their data to manage risk and offer competitive products and services.
The right decision intelligence platform can help insurers connect and operationalize internal and external data that delivers a holistic view. The result: a faster, richer understanding of every applicant, customer, claimant, third-party, and supplier across the value chain.
When insurers have confidence through the right data and context, they can better protect against fraud risk and focus on growing their business – using a deeper customer understanding to limit customer churn, optimize pricing based on customer behavior, and discover cross-sell or upsell opportunities.
Government and public sector
Agencies in the public sector need to ensure the integrity of payment programs and supply chains, carry out complex operations, counter fraud, enable security, and safely share intelligence. The right decision intelligence platform allows government and public sector agencies to be interoperable, securely integrating into existing systems to boost efforts to stop fraud, ensure compliance, investigate crime, and improve the safe movement of people and goods.
Stopping fraud is vital to the government sector’s bottom line. In the United Kingdom, the government plans to spend £25 million to crack down on fraudsters who steal taxpayer money. Through the secure utilization of data, the right decision intelligence platform aids agencies to foster transparency, improve trust, and enable quick decision-making to create safer communities across the globe.
Telecommunications
Telecommunications organizations are up against an increasingly competitive market as their traditional revenue streams, such as connectivity, infrastructure and voice-centric services are commoditized.
Companies are focused on developing differentiated products and go-to-market strategies that enable new revenues, compelling offerings, and excellent customer experiences.
The right decision intelligence platform can help telecommunications organizations become more data-driven and customer-centric by bringing disparate and ambiguous data together at scale using extremely accurate, dynamic entity resolution capability.
This helps telecommunications organizations get full use of their internal and external data to get a full, customer-360 view so they can grow revenue, reduce churn, increase wallet share, and achieve operational efficiency.
What is the impact of decision intelligence?
Decision intelligence and the ability to utilize entity resolution to create a complete, meaningful view of data across an enterprise provides the contextual data foundation businesses need to enhance decision-making across the customer lifestyle, uncover hidden risks, and discover unexpected opportunities.
It’s clear that decision intelligence is a critical must-have. The key reason, says Joseph Sieczkowski, CIO and Chief Architect of BNY Mellon, is that data and contextual decision-making are core to the bank’s digital transformation.
“Our hard-won vantage point is allowing us to use data science to highlight future opportunities, which in turn, we can present back to our customers to help them increase revenue, reduce costs, and reduce risks,” says Sieczkowski.
That point is echoed by Bina Mehta, Chair at KPMG, who explains that data is at the core of enterprise decision-making.
“It’s about making better decisions and about managing our risk,” Mehta says. “But it’s not just about our financial performance – it’s about the other commitments we make. In our world, that might be quality, customer service, and ESG commitments. Those measures are harder to pinpoint. That’s why data is really valuable in the broader sense.”
By investing in decision intelligence today, organizations can build trust in their data and establish a culture of confidence in automated or augmented decision-making to protect, optimize, and grow their business.
How has decision intelligence changed traditional ways of decision-making?
Before the advent of decision intelligence to bring data together, data was often scattered across systems, siloed, incomplete, or of such poor quality that it was difficult to make connections. This often led to poor or wrong decisions that hurt the customer experience and lost revenue.
Today, decision intelligence provides the means to harness this fragmented data to provide a holistic, trusted view of B2C and B2B customers, allowing decision-makers and analysts to uncover hidden patterns that were previously unseeable to dramatically increase the value of insights.
With Quantexa's Decision Intelligence platform, decision-makers are now empowered to:
Get a holistic, trusted view of customers
Connect disparate data from internal systems and external sources to form a 360-degree view of your customers.
See a broader picture of relationships
Interlink distinct entities to see the big picture. Gain deep understanding of relationships such as social connections, households, corporate structures, and supply chains.
Uncover hidden opportunities
Use advanced analytics to trigger real-time insights that enhance customer experience and drive growth.
Tap into trusted data insights
Provide a rich visualization layer along with open APIs to allow integration within existing IT landscapes.
What problems does decision intelligence solve?
Financial Crime
Quantexa’s Financial Crime solution suite enables organizations to take a proactive approach to financial crime and fraud detection, prevention, and investigation. The solution suite consists of two key elements:
A standalone investigation tool that enables proactive alert management and generates insights.
A real-time contextual monitoring solution that provides an advanced understanding of parties, counterparties, and their relationships.
Quantexa’s solutions are built to easily integrate and scale with existing case management systems. They generate value by reducing false positives and targeting real risk across multiple lines of business for more accurate, trusted decisions.
Know Your Customer (KYC)
Quantexa’s contextual KYC software helps organizations improve their KYC and customer risk rating processes by connecting internal and external data to create an accurate, holistic view of customers. It provides organizations with the necessary context to get a precise view of customer and counterparty risk, enabling an effective and proactive approach to detection.
Contextual KYC simplifies complex relationships, helps organizations reduce inefficiencies, and facilitates a continuous, realistic understanding of risk through perpetual monitoring.
Risk Management
Quantexa’s risk solutions use Decision Intelligence to visualize and understand risk factors, help remove uncertainty, and increase the speed and efficiency of risk monitoring processes.
Risk is the probability of financial or reputational loss from particular decisions, practices, or activities. Historically, credit risk processes often focused on a limited view, assessing customers in isolation or by product, lacking the context required to prioritize new and emerging risks and meet regulations.
Quantexa’s risk solution suite also enables organizations to:
Monitor data continuously to detect changes and risk factors, such as credit risk or portfolio monitoring.
Trigger alerts automatically based on a configurable range of behaviors to prioritize real risk and meet regulations.
Understand borrowers, counterparties, and their relationships to allow more informed risk decisions for approving loans, facilities, limits, and terms.
Fraud and Security
Quantexa’s Fraud and Security solution suite enables contextual monitoring and alerting for a range of fraud typologies across sectors such as Banking and Insurance.
Fraud prevention aims to identify a criminal’s financial gain from deceptive claims and practices. Fraud is distinguished from other financial crimes because it exploits legitimate payment structures, such as compensation schemes.
The solution suite connects multiple internal and external datasets to achieve a complete view of individuals, businesses, claims, and policies.
Its analytical capabilities enable banks to accelerate investigations, make accurate decisions to reduce fraud losses, and better protect their customers.
Data Management
Quantexa’s Data Management solution suite enables organizations to connect all internal and external data sources to create trusted single views, address challenging master data and data quality problems, and make contextualized data available where it can make a difference.
The solution suite uses Entity Resolution to enable organizations to:
Achieve greater accuracy even with poor-quality data.
Handle complex hierarchies and relationships.
Support multiple use cases from one instance.
Customer Intelligence
Quantexa enables organizations to extract maximum value from customer data by combining disparate and ambiguous internal and external data at scale using Entity Resolution. With this complete view of their data, organizations can better understand customers and prospects.
The solution suite’s contextual view enables organizations to:
Deliver better client service.
Provide personalized experiences and relevant offers.
Identify new growth opportunities.
How can organizations get started with decision intelligence?
No matter the use case or the business unit, solutions for smart decision-making on every level can deliver immediate value with Quantexa's Decision Intelligence platform. Using this repeatable framework, organizations can:
Unlock value from day one
Pick another line of business and a use case, and continue building out the data foundation as part of your existing infrastructure.
Continue optimizing
With a unified data foundation and additional use cases, a culture of continual optimization takes over, as faster, confident decision-making becomes the norm.
Drive decision maturity
Continually increase your organization’s capabilities by deploying new technology, along with learning and certification opportunities for your workforce.
Become resilient and agile
Your data foundation is ready for any use case – giving your organization flexibility, resiliency, and agility to address any threat or opportunity.
What is the future outlook for decision intelligence?
As we look to the future, technologies will continue to evolve, providing decision-makers with even better tools with which to understand their customers to create more value, discover new markets and revenue opportunities, and increase their competitive advantage through better decision-making.
Adopting Decision Intelligence technologies will not become a substitute for human thinking, however. In fact, quite the opposite is true. Technology and automation delivered through DI platforms will provide a deeper understanding of the decision-making process itself thereby increasing the capabilities of decision-makers, and guiding them through reliable data to make the best decisions possible.
As Gartner recently summarized, "in times of increasing complexity and uncertainty, decision-making as an organizational capability will become a main competitive differentiator. Those who are able to make better, faster decisions will win in the market."
Decision intelligence FAQs
What are examples of decision intelligence? 
Fraud and Financial crime detection and reduction. Organizations across Banking, Insurance and other industries can utilize the Decision Intelligence platform to conduct due diligence, and continuously monitor illicit activities, reducing the impact of fraud and financial crime on the institution by tens of millions, while reducing claims, and improving customer service.
Customer Intelligence. Decision Intelligence can be used to connect difficult-to-match datasets across the business and gain insights into customer interactions to enable sales and support teams to use a 360-degree customer view to be more efficient in their prospecting and support activities, leading to a growth in customer value.
Creating a trusted data foundation. Public and private organizations use Decision Intelligence to achieve data trust, transparency, and explainability, helping to improve digital resiliency and efficiency to provide customers, citizens and patients with simpler and smarter solutions as well as enable analytics and AI programs.
Is business intelligence the same as decision intelligence?
Decision intelligence is the latest step in the evolution of business intelligence. Instead of combining all available data, context-free, and presenting it to a decision-maker, decision intelligence uses artificial intelligence (AI) to provide a single analytical view – to either fully automate decisions or to help data professionals make faster, more accurate decisions through augmentation.
Is decision intelligence the future of decision making?
Decision intelligence represents a significant shift in how decisions are made, moving from intuition-based approaches to more systematic, data-driven methods. As technology continues to advance and organizations recognize the value of more intelligent decision-making, decision intelligence is likely to play an increasingly central role in the future of decision-making across various sectors. However, the full potential of decision intelligence will depend on overcoming current challenges and ensuring that it is implemented thoughtfully, ethically and by using a trusted data foundation.
Useful links
We’ve discussed a lot regarding decision intelligence in this guide. However, there could be more you want to know about the impact it can have on your organization. Browse the following articles for further reading.