How to Extract the Maximum Value from Your Information Assets
Since "data is the new oil,” it's critical to find much more efficient ways to find it, extract it, and refine it into something valuable for your digital transformation
In the late 1800s, John D. Rockefeller, J. Paul Getty, H.L. Hunt, and many others started making vast personal fortunes in oil. Today, it’s often said that with modern digital technologies “data is the new oil.” Indeed, eight of the ten richest people in the world are not oil magnates, they are founders and owners of information purveying conglomerates like Google, Facebook, Twitter (X), Amazon, and Oracle, according to Forbes.
Just as oil has little value in its raw state, data only becomes valuable when a company finds it, extracts it, and refines it into something of value. Their motivations could be two-fold: ward off competing digital disruptors – like fintechs and insurtechs – or to leverage their data as the raw material for next-generation, information-rich products and services of their own as part of their digital transformation innovation strategy.
When harnessed, data has two intrinsic forms of value: for internal use and for external marketability. Both are critical to a digital transformation effort:
Internal use: this is data that helps your company make smarter, faster, more profitable strategic decisions. It is operational in nature and serves as the “secret sauce” that helps companies outsmart and outpace their competition.
External marketability: this is data you use to create information-based products and services that can be marketed to customers and prospects. It could be new direct-to-end-consumer products, or API-based features and functions that complement solutions from third-party technology partners.
A Platform for Success
In the competitive digital economy, a gold rush mentality is driving companies to invest trillions of dollars into digital transformation. The overarching goal of digital transformation is unifying all information across the enterprise, using digital technologies to democratize it regardless of its source or the role of domain experts using it, and rallying everyone in the organization to use the resulting information assets to build agile, transformation-rich, customer-centric solutions. Such innovation will accelerate the development of offerings that result in higher levels of short-term customer satisfaction and long-term retention, which in turn fuels longer customer lifecycles and higher lifetime value (share of wallet).
From the outset, this requires a massive data integration effort. For years, the most common approaches to data integration have been digital technologies like ETL (Extract, Transform, and Load) and ELT (Extract, Load, and Transform). While these were once new technologies and effective to a point, they don’t solve the problem of “siloed” data or allow for the persistent instantaneous transfer and analysis of data in a manner needed to enable real-time decisions and actions.
Because of the time, costs, and technological shortcomings of previous-generation approaches, more and more companies are turning to agile enterprise decisioning platforms to accelerate the attainment of their digital transformation goals by holistically orchestrating their enterprise information. In a recent study by IDG, it was reported that the top priority cited by IT leaders responsible for new technologies was “Evaluating optimal IT Platforms,” and more than 65% are already executing towards it as part of digital transformation strategy. .
Why are enterprise decisioning platforms a vastly superior alternative to old-school ETL and ELT approaches in transformation? For starters, solutions like FICO Platform enable the corporate cloud-wide sharing of information in real-time. This eliminates challenges caused by siloed systems, to allow companies to:
Share, democratize, and mobilize all information assets across the company. This is essential to digital transformation because it allows businesses to use automation to unify all of their data from every source, they can connect the dots and fill in the gaps between siloed departmental applications. This enables business model and business process changes that ensure better corporate, not just departmental, decisions at every point of the customer lifecycle. The persistent application of AI, machine learning, and algorithmic analytics applied in real time iteratively improves the quality of data, and thus decisions, over time.
Codify business users’ domain expertise into ubiquitous, persistently applied automated intelligence. By empowering and encouraging business users to create and manage information strategies, rules, and analytics that drive decisions and actions, companies combine the “book smarts” of the technology organization with the “street smarts” of business users. This enables companies to respond swiftly to shifts in business scenarios and foster a customer-driven mindset that ensures more prosperous outcomes, the ultimate goal of digital transformation
Leverage and re-use connected decision assets to improve decision automation across the enterprise and across the customer lifecycle. This is a transformational capability that gives companies the ability to create customized, targeted decisioning strategies that are consistent, transparent, explainable and expandable as needed over time.
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 programs will perform as desired when launched. By iteratively simulating, fine-tuning, and perfecting strategies prior to launch, companies ensure optimal, predictable results, to maximize success rate and ROI.
Consistently deliver automated, seamless, hyper-personalized customer experiences. This enables companies to offer customers consistent, tailored experiences that are reached by, and infused with, customer intelligence. Armed with AI-validated personalized customer strategies, companies can more accurately predict and effectively serve their clients’ immediate and future needs, paving the way for cross-selling and up-selling. This is the key to consistently delivering a compelling customer experience, which raises short-term customer satisfaction and loyalty, as well as long-term customer retention and share-of-wallet, the payoff for your digital transformation investment.
Why are these capabilities so powerful, empowering, transformational? Circling back to our oil metaphor, they lay the foundation for us to achieve our original goal: finding, extracting, and refining data. Here’s how this plays out in a typical digital transformation scenario:
Finding the most relevant data: Most data – whether for internal and external data use – exists in what is largely a “raw” state. It may be structured data, as in a database or application, which makes it partially refined, but on its own it’s not typically ready for use in collaborative, enterprise-wide transformation solutions. Estimates vary, but most experts report that 80-90% of data is unstructured, which means to make it useful, you’re going to be relying heavily on AI, machine learning, and algorithmic analytics… which, in turn, is done most efficiently in an enterprise decisioning platform designed for that purpose.
Extracting and storing data: Once the locations of information are identified, a platform exposes and unifies data – wherever in the enterprise cloud it resides – to make it interoperable across the organization. This promotes widespread assimilation and reusability of information, with each application filling in the blind spots of the others. And because of platform features like no-code composability, verified information assets can be used (and continually re-used) by technical and business users alike to combine the best book smarts and street smarts from across the organization.
Refining raw data into actionable insights: Once composable information becomes the lingua franca for the organization’s people, processes, and technologies, companies can unleash astonishing collaboration, innovation, and acceleration. Armed with continually refreshed ideas and insights, domain experts can pursue, simulate, and optimize both customer and business strategies at an astonishing pace, making transformation a reality. These strategies can be constantly enriched by AI, machine learning, and algorithmic analytics, allowing the system to “learn” the most effective and efficient strategies and their outcomes, incrementally producing an ever more powerful base of knowledge.
Just as oil was the road to riches 150 years ago, today data – or rather, smarter customer strategies resulting in actionable customer insights – is the key to lucrative business outcomes in the modern world, especially in data-intensive industries like banking and insurance with vast digital transformation goals. According to a report by McKinsey & Company, business leaders across all industries predict that by 2026, half of their revenues will come from products, services, or businesses that haven’t yet been created. This may or may not hold true for industries like banking and insurance, whose core services are largely the same as they’ve been for centuries, but smarter, faster, more profitable decisions will always be worth their weight in gold… or oil.
Learn How FICO Platform Can Power Your Digital Transformation
Explore innovation with FICO Platform
Watch the video “FICO® Platform: Applied Intelligence, when and where it matters”
Read the whitepaper “FICO® Enterprise Intelligence Network: Redefining the next generation of applied intelligence”
Read the article from The Journal of Digital Banking, “How Financial Services Leaders Are Using Enterprise Intelligence to Optimize Efficiency Ratios”
Watch FICO Platform in action with the story of your everyday consumer, Digital Jane
Popular Posts
Average U.S. FICO® Score at 716, Indicating Improvement in Consumer Credit Behaviors Despite Pandemic
The FICO Score is a broad-based, independent standard measure of credit risk
Read more
The GSE Data Is Public. Here's What It Shows About Credit Score Modernization.
Independent Milliman analysis of GSE historical data confirms what anyone can now verify directly: FICO® Score 10T is the most predictive score.
Read more
FICO® Score High Achievers: Is Age the Only Factor?
<p>FICO’s latest research on <a href="http://www.fico.com/en/blogs/risk-compliance/us-credit-quality-rising-the-beat-goes-on/" target="_blank">national FICO® Score distribution</a> shows that US credit quality continues to trend upwards, with an increasing number of consumers scoring in the highest scores ranges. Given that, we decided it was time to refresh our study on “<a href="http://www.fico.com/en/blogs/risk-compliance/infographic-what-does-a-high-credit-scorer-look-like/" target="_blank">FICO® Score high achievers</a>,” where we examine the credit behavioural profiles of consumers with higher credit scores.</p> <p>As expected, our latest study showed that older people generally have higher scores, as has been the case in our <a href="http://www.fico.com/en/blogs/risk-compliance/age-before-beauty-credit-worthiness-before-youth/" target="_blank">past research</a>. This is largely because they have trade lines that have been open longer, which leads to higher scores (assuming the trade lines are in good standing and all other things equal). The most credit savvy among you will remember that length of credit history accounts for roughly 15% of the overall <a href="http://www.myfico.com/CreditEducation/WhatsInYourScore.aspx" target="_blank">FICO® Score calculation</a>.</p> <p>But for younger consumers, it isn’t too helpful to say, “just wait until you are 50 years old, and that will fix things!” Thus, I decided to dive deeper with our analysis, including looking at the credit behavioural characteristics of younger consumers with high FICO® Scores.</p> <p>In this analysis, I looked at credit characteristics for the two highest score bands, 750-799 and 800-850, which have about 16% and 23% of the population, respectively. I further broke this down by looking at the characteristics of the youngest 15% in each group, which occurs at age 29 for the 750-799 group and 43 for the 800-850. We used FICO<strong>®</strong> Score 9 for our analysis, and examined typical variables of the categories that go into the make-up of the score.</p> <p><a href="http://www.fico.com/en/blogs/wp-content/uploads/2016/10/FICO-Score-High-Achiever-table.png"><img class="alignnone size-full wp-image-29367" src="http://www.fico.com/en/blogs/wp-content/uploads/2016/10/FICO-Score-High-Achiever-table.png" alt="fico-score-high-achiever-table" width="715" height="747" /></a></p> <p>Since there’s a lot to dissect in this chart, I’ll highlight a few findings that struck me: <ul> <li><strong>Credit history.</strong> Higher scores are undoubtedly associated with a longer time on file. What’s striking is the higher average time on file for the 800+ group, both overall and for revolving accounts (the most common trade line). Clearly, it helps to start credit use early in life – but that’s not the sole determining factor for high scoring. The younger cohorts in both the 800+ and 750-799 groups have time on file medians significantly less than their older counterparts.</li> <li><strong>New credit.</strong> High credit scorers do, in fact, pursue new credit. We see little variation in months since last trade line opening and last inquiry among all groups observed.</li> <li><strong>Pay on time.</strong> As you might expect, the further in the past the delinquency, the higher the score – and that’s <u>if</u> a delinquency ever happened. 95% of the 800+ people and 72% of the 750-799 group have never been delinquent, which is a striking contrast to the 57% for the total population. The percentages for the younger groups are even higher, especially so for the 750-799ers. Collection items are also scarce for these high scorers. While 23% of the national population have collection items greater than $99, the figures are only 0.5% for the 800+ group and 3% for the 750-799 group. It is clear that, in conjunction with starting a credit file early, paying on time is a key trait of the FICO® Score high achiever.</li> <li><strong>Balance and utilization.</strong> Finally, we look at how credit is being used, focusing on revolving product use. (Since most people only have one mortgage or one auto loan, variation in instalment product figures is minimal and driven by payment history, which is near perfect for high scorers, as we’ve seen.) FICO® Score high achievers tend to have more open revolving accounts. While the % active trades and utilization are generally lower, by no means do high scorers avoid the use of credit products. What drives the difference here is the amount of <u>available</u> revolving credit utilized. The 800+ group is roughly 1/4 of the national median, both in total and on their highest utilized card; they also have lower balances and more cards<em>. </em>The 750-799 group is more active and higher utilized, but still only at 2/3 of the national figures. The young 750-799 group compensate with lower revolving balances and, as a result, lower utilization, which is in line with what we see for the 800+ group.</li> <li><strong>Benchmarks.</strong> I’d like to point out that while this study provides good benchmarks of the typical credit traits of the FICO® Score high achiever, individual credit profiles will vary widely. And keep in mind that when we sort groups of consumers as a whole by different behaviours, some results may look superficially odd. For example, the 800+ band has a longer median average open account time (128 months) than average revolving months on file (140 months).</li> </ul> So, what do we conclude? A huge takeaway is that high scorers don’t have too much in the way of serious delinquencies and negative public record data.</p> <p>In most respects, the young 800+ people are like their peer group. They really only differ markedly in their shorter credit history and higher non-mortgage balance, both of which are a function of life stage. Our results show that you don’t have to be a credit product hermit; these high scorers have more credit cards. The takeaway is to start credit activity early and maintain well-managed and moderate usage.</p> <p>In many ways, the young 750-799 people are more interesting because their age profile is much younger. Their credit characteristics differ more from their peer group, particularly in terms of length of credit history. They compensate by having almost pristine credit records and lower balances.</p> <p>Ultimately, 39% of US consumers are FICO® Score high achievers, which they accomplish by following common-sense credit practices. It ain’t rocket science!</p>
Read moreTake the next step
Connect with FICO for answers to all your product and solution questions. Interested in becoming a business partner? Contact us to learn more. We look forward to hearing from you.