Analytic Predictions 2018: 31 Flavors of AI
Here are some of the top things I think we'll see among the 31+ flavors of AI in 2018.
Although my predictive powers don’t hold a candle to Carnac the Magnificent, this prediction from my 2017 analytics forecast certainly held true: “I think that we are just at the beginning of the golden age of analytics, in which the value and contributions of AI [artificial intelligence], machine learning [ML] and deep learning will only grow as we accept and incorporate these tools into our businesses.”
As it happens, AI, ML and deep learning didn’t just grow up during 2017. They blew up.
In 2018, development and use of these technologies will continue to expand and flourish—in so many ways it’s hard to quantify. But just as Here Come Da Fudge and Bubblegum were my childhood favorites at Baskin Robbins (famed for its 31 flavors), here are some of the top things I think we'll see among the 31+ flavors of AI in 2018.
1. AI Will Learn to Fight Back
In 2018, Defensive AI will be front and center. We’ve long talked about how machine learning and AI will help companies to drive differentiation in competitive markets. This applies in the criminal world too, where attackers will use malicious AI and ML to circumvent the ones companies have in place. This arms race, in which criminals arm themselves with “adversarial machine learning,” tops McAfee’s 2018 security forecast.Earlier this year, I wrote about FICO’s patent-pending Defensive AI technology, which will usher in systems that will seed their outputs with “faint signatures” to mislead, confuse or identify the attackers learning the AI system’s response.
2. AI Will Have to Explain Itself
The need for Explainable AI (XAI) is catalyzed by regulations like the European Union’s General Data Protection Regulation (GDPR), which requires explanations for decisions based on scores, including those produced by AI and ML systems. We’ve long dealt with this challenge in fraud and credit risk decisioning, but in using ML across multiple industries, there are entire sets of proposed explanatory algorithms which are either right, ineffective or flat wrong. Under GDPR, it’s imperative that companies can correctly explain the decisioning processes of AI and ML systems.Here’s a telling metric on interest in XAI: As the May 2018 deadline for GDPR enforcement gets closer and closer, views on my nearly year-old blog on Explainable AI have quickly increased.
3. AI Will Augment Us
The idea that AI and humans will play nice together, rather than battling in a Terminator scenario, is not new. (My favorite of the franchise is, of course, T3.) But in 2018, AI will augment much more of the workplace, not just through better software, but increasingly better versions of ourselves.Whether it’s drawing the information together for us to be superhuman at investigation, data recall, or improving how we learn new topics, AI will augment our ability to process new information. The question will be as to whether our human brains will atrophy, improve or simply evolve to the rate and frequency of data.
4. AI Will Get Operationalized
In 2018, companies will focus on operationalizing AI, particularly in the cloud, to more easily build, refine, deploy and enhance machine learning environments.5. Chatbots Will Get Better at Understanding Us - and Manipulating Us
In many aspects of society it is becoming difficult to determine what is human versus a robot, organically occurring versus automated, real or fake. (This reminds me of the old ad ‘Is it live or is it Memorex?’)In 2018 chatbots will rapidly become more sophisticated, dramatically reducing costs of routine customer care activities, and often improving the customer experience. In the coming year chatbots will quickly understand the tone, content and predicted highest-value conversational paths to meet various objectives. On the dark side, this subtle “engagement” can turn to manipulation through AI that learns the magic words to sway our attitude, actions and possibly elicit en masse reactions.
For now, at least, I’ll still go for the real human on the other end of my iPhone.
6. AI Will Combine with Blockchain
Beyond its association with cryptocurrencies, blockchain technology will soon record “time chains of events,” as applied to contracts, interactions and occurrences. In these “time chains,” people and the items we interact with will have encrypted identities. The blockchain that is distributed will be the single source of truth, allowing audit trails of data usage in models, particularly in data permission rights.Here’s an example of where the blockchain rubber hits the road. Think about renting a car. Today you’d go to a traditional car rental agency like Hertz or Avis, or belong to an “alternative” rental organization like ZipCar or car2Go. In the future, you will be able walk up to a car to lease it, but you’ll do so with a micro-loan for which you are approved to lease the car for, say, an afternoon. This micro-loan will have insurance contracts attached to the chain, and a codified history of the car’s history of drivers, events, and maintenance. As you drive through the city and interact with toll roads and parking spaces, all of this information will be automatically recorded and monitored on the blockchain. When you leave the car and lock it, the lease is complete and auditable on the chain.
Beyond that, data event chains will create new opportunities for graph analytics and novel new AI algorithms to consume relationship data at scale. In 2018 we will see new analytics around relationship epochs. Here’s a quick definition: Think of your daily interaction with money, people, places and things. Most days are relatively routine but sometimes chains of events occur that have new meaning, perhaps indicating money laundering activity, bust-out fraud, suicide prevention opportunities and many others. Clearly, understanding these webs of relationships of events will add more insight to any analysis of individual components. These webs, or relationship epochs, will feature scoring based on shifting chains and graphs, delivering tremendous predictive power.
As you scoop your last few ice cream cones in anticipation of 2018 resolutions, follow me for the good stuff on Twitter @ScottZoldi.
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.