Fair Isaac Corporation

11/07/2024 | Press release | Distributed by Public on 11/07/2024 08:47

What Is Applied Intelligence and How Does It Work

In a time when every software provider is hyping their artificial intelligence, and the use of AI has gone from the province of data scientists to your relatives and friends, related terms might be confusing or even seem redundant. Applied intelligence fits this bill - is this just another term for AI?

In fact, applied intelligence has a separate meaning, one that is very important not only to businesses but to the success of AI itself. (To avoid any further confusion, AI here means what you think it means, artificial intelligence.)

Applied intelligence refers to the melding of human and artificial intelligence. The goal of applied intelligence is to empower companies to make ever smarter, ever faster, and ever more profitable business decisions, wherever and whenever data can be leveraged to gain sustained competitive advantage. In other words, applied intelligence relies on AI, but it is not just AI.

Why is this so vital? There are two big reasons.

1. Applied Intelligence - AI Plus Much More

First, AI is just one of the technologies that are required to truly drive performance. As Eric Kavanaugh noted in his article "Navigating the Perfect Storm with Applied Intelligence" from eWeek, "In the time it takes for a seasoned professional to make one decision, AI can ask thousands of questions, get just as many answers, and then winnow them down to an array of targeted, executed optimizations. That's the domain of applied intelligence, a closed-loop approach to traditional data analytics. The goal is to fuse several key capabilities - data ingest, management, enrichment, analysis and decisioning - into one marshaling area for designing and deploying algorithms."

FICO has identified a number of core technologies and functionalities that are important in applied intelligence. These include:

2. Applied Intelligence - Complementing Human Judgment, not Replacing It

Second, no business is ready to be run by pure AI. And they shouldn't be.

My colleague Scott Zoldi, FICO's chief analytics officer, is very clear about the need for Responsible AI, AI that is ethical and auditable. People need to be kept in the loop to make sure that the processes and data AI employs, and the decisions it recommends, are in the best interests of all involved.

AI isn't perfect, but then neither are we. The goal of applied intelligence is to create the most perfect union, if you will, between man and machine, between business experience and algorithmic horsepower. An applied intelligence system empowers this kind of collaboration.

To give just one example, if you are trying to launch a new credit product, you will have several goals to meet. You will want to maximize take-up of the product, you will want to maximize profitability, you will want to keep credit losses below a certain threshold based on your risk appetite, etc. Optimization technology can help you identify the best criteria and produce a decision strategy that meets your varied objectives; it can also simulate the results. It can even plot various strategies along what's known as an "efficient frontier". Ultimately, the choice between these trade-offs belongs to management - and not just one person, as the product manager, the marketing team, the risk team and even the treasury function have a stake in it. This isn't the kind of decision you make by just pushing a button, but neither is it the kind of decision you want to make without high-powered analytics.

What Does an Applied Intelligence Solution Do?

As Kavanaugh noted, an applied intelligence platform gives you the ability to make better customer decisions in real time, leveraging data from across the enterprise using advanced analytics, decision modeling, and AI - all working synergistically in an open and extensible platform to simultaneously transform the customer experience and the corporate goal of accelerating time-to-value.

These systems empower companies to:

  • Unify and mobilize the enterprise: Companies can implement a scalable decision platform across the enterprise to optimize and monetize the use of people, data, and analytics. By leveraging all information from across the enterprise and beyond, a platform fills in the holes in decisioning requirements and ensures better decisions at every point of customer action across the lifecycle, iteratively improving over time.
  • Leverage business users' domain expertise: Disruptive companies are bringing the heat of the marketplace into their planning by encouraging and empowering business users to create and manage the strategies, rules, and analytics that drive decisions and actions - without IT intervention. Applied intelligence unites the technology organization with business users to enable companies to build and test a wider range of scenarios faster than ever before, and foster a market-driven approach to ensure more prosperous outcomes.
  • Ensure seamless, personalized customer experiences: Companies can offer customers consistent, tailored experiences that are reached by, and infused with, customer intelligence from across the organization. By creating personalized customer strategies, companies are able to accurately predict and effectively serve their clients' immediate and future needs.
  • Simulate and optimize strategies before they are put into production: This provides highly accurate predictions about programs' prospects for success, giving companies the highest possible degree of certainty that they will perform as desired when launched. By iteratively simulating, fine-tuning, and perfecting strategies prior to launch, companies ensure optimal, predictable results and maximize both the success rate and ROI of their decisions.
  • Optimize and maximize the use of reusable knowledge assets: This enables companies to leverage and re-use connected decision assets to improve decisions across the customer lifecycle, while making them transparent and explainable.

This gives companies the ability to create customized, targeted decisioning strategies that are consistent, transparent, and expandable as needed over time.

Applied Intelligence in Financial Services

The reason why applied intelligence is so critical in financial services is simple. Most banks, credit unions, building societies and other financial institutions have siloed systems that prevent both a complete understanding of their customer, and the ability to use that understanding to improve the way they attract, onboard, manage and protect their customers.

According to a recent Accenture Global Consumer Pulse report:

  • 84% of customers say that personalized customer treatments - those based on a deep understanding of their needs, preferences, and past interactions - are very important to winning and keeping their business
  • 76% would re-evaluate their choices if a new company would excel at personalization compared to their current one
  • 73% expect specialized treatment for being a good customer
  • 33% of consumers who abandoned a relationship did so because personalization was lacking

In my role as chief product and technology officer for FICO, I meet frequently with C-level executives in the financial services sector, who are grappling with this issue. A recent executive survey conducted by American Banker listed myriad reasons why traditional financial services institutions are struggling to perfect their decisioning and personalisation strategies; all were traceable back to three systemic points of failure:

  • Only 5 per cent have a unifying, scalable decision platform across the enterprise.
  • Only 14 per cent are proficient at anticipating and pre-emptively serving customer needs.
  • Only 4 per cent have the ability to create the types of fully personalised customer treatment at scale that today's digitally savvy customers demand.

And unfortunately, when it comes to digital transformation, 'investing' in new technology does not automatically equate to 'succeeding.' In recent reports, I read that 87 per cent of major corporations have a digital transformation effort underway (IDG), and to date only 30 per cent of companies have achieved their full desired results (Boston Consulting Group).

In my observation, companies that successfully invested in applied intelligence capabilities are reaping the benefits, both in terms of being able to weather the rapidly changing situation and in driving down their efficiency ratio. In fact, we have identified nine ways that applied intelligence creates success for financial institutions. You can read more about this in my article for the Journal of Digital Banking.

Applied Intelligence vs. Decision Intelligence vs. Enterprise Intelligence

An applied intelligence platform or system is still a relatively new phenomenon. As a result, different terms are used that mean fundamentally the same thing.

The term "decision intelligence platform" is gaining ground, pushed forward by analyst firms such as Gartner and IDC. Gartner produced its Gartner® Decision Intelligence Market Guide in July, and IDC produced its "IDC MarketScape: Worldwide Decision Intelligence Platforms 2024 Vendor Assessment."

IDC describes decision intelligence platforms as "software technology that helps organizations design, engineer, and orchestrate decisions by fully or partially automating all the steps in the decision-making process." As you can see, this is how we have defined applied intelligence.

The Forrester Wave Report on AI Decisioning Platforms uses a different term - an AI decisioning platform.

In my view, applied intelligence and decision intelligence mean the same thing. In practice, an AI decisioning platform is another name for an applied intelligence platform, an enterprise intelligence platform or a decision intelligence platform.

FICO Platform and Applied Intelligence

At FICO, we understand what it takes to turn data and insights into actions in order to achieve the desired business outcomes. At the end of the day, if an organization isn't yet achieving their outcomes at the speed they need, they aren't truly successful. Our longstanding heritage in decision management has helped leading companies around the globe operationalize their analytic and machine learning insights to make smarter, faster, and more profitable decisions.

FICO Platform represents the future of our software business as the next-generation cloud platform for applied intelligence. With FICO Platform, you are able to build a rich, contextualized view of your customer with all the right data, apply the latest AI and advanced analytics to gain competitive insights, put these insights into action with real-time decisioning, and ultimately drive the tangible business outcomes that matter.

Our open, unified, and extensible platform architecture connects data and decisions across departmental siloes to enable an event-driven, holistic approach to building, maintaining, and growing profitable customer relationships. No matter the use case, FICO Platform provides you with all the capabilities you need to quickly deploy intelligent solutions across the customer lifecycle.

Bringing these capabilities together into a single, unified platform is the result of years of experience implementing game-changing line of business solutions for customers in banking, insurance, telecommunications, and automotive finance. Combined with our deep domain expertise in these industries, FICO is helping enterprises across the globe deliver an optimal customer experience at each and every interaction.

Learn How FICO Platform Can Power Your Digital Transformation with Applied Intelligence