Don’t be surprised if your bank knows not just who but also what you are in the future

Don’t be surprised if your bank knows not just who but also what you are in the future
We all know personality tests can be a little hit and miss – some are serious, long and can be scarily accurate. Others you do for fun on a Saturday afternoon whilst reading a magazine, and you never take the results too seriously. I just came across a new type of personality test, Personality Insights powered by IBM’s Watson. According to the description, the test “uses linguistic analytics to extract a spectrum of cognitive and social characteristics from the text data that a person generates through blogs, tweets, forum posts, and more.” Interestingly, it claims to be able to reach conclusions just from a text of 100 words. I was curious to see what the tool would say about me based on some of my blogs. I entered one of the recent texts and I got this back:
You are inner-directed and skeptical. You are empathetic: you feel what others feel and are compassionate towards them. You are philosophical: you are open to and intrigued by new ideas and love to explore them. And you are independent: you have a strong desire to have time to yourself. You are motivated to seek out experiences that provide a strong feeling of connectedness. You are relatively unconcerned with taking pleasure in life: you prefer activities with a purpose greater than just personal enjoyment. You consider achieving success to guide a large part of what you do: you seek out opportunities to improve yourself and demonstrate that you are a capable person.
As always with these things, you never entirely agree, but I could recognise some of my personality there, so I was intrigued. I wanted to try it more and started entering other blogs written by me and my colleagues on this site. Most of the results turned out to be remarkably similar, suggesting that we are “shrewd, skeptical, imaginative, philosophical, driven by a desire for prestige, relatively unconcerned with tradition, etc.” Well, it is possible that we are a fairly homogeneous bunch – as analysts we often talk about new technologies, so we are “relatively unconcerned with tradition”, yet we can’t afford to succumb to the latest hype, so can come across as “skeptical.” But the homogeneity of results made me rather suspicious, so “for something completely different”, I entered an article on English football by a broadsheet journalist. While his profile turned out to be a bit more different, he was also “inner-directed, skeptical, empathetic, and philosophical.” Not surprisingly, I wasn’t the first person to try out the tool with the extremes. A Mashable article described someone submitting “a 1919 letter from Hitler explaining his anti-Semitic agenda to a well-wisher” for analysis. Apparently, Hitler was also “shrewd, skeptical, imaginative, philosophical, laid back, appreciating a relaxed pace in life” and someone who thinks “it is important to take care of people around you.” Now, it’s easy to show how something new is not yet perfect, but there is serious science behind the service. And even though this particular tool still needs to learn and improve, we are convinced that artificial intelligence and Watson-type technologies will have a big impact on customer servicing in Banking and other industries. Implementing and making use of these technologies is not easy, but there is no doubt that in the future more decisions will be driven by data and analytics. So, don’t be surprised if the next time you call up your bank to discuss the latest transactions or the new product you want to buy, you realise they know instantly not just who you are (e.g. via voice biometrics), but also what you are. P.S. I just did sort of a “meta-test” by entering the above text into the service. The tool called me “unconventional” and suggested that I am “intermittent” and “have a hard time sticking with difficult tasks for a long period of time.” Is it not just smart, but potentially vindictive as well? 🙂

Spending a day with IBM’s Watson

Spending a day with IBM’s Watson
As an IBM alumnus (but no longer a stockholder) I’ve gotten pretty used to seeing the company do things a certain way. And then I attended a day-long “Watson at Scale (aka Ecosystem 2.0)” event on October 7 and had a lot of my old notions upended. Watson, of course, came to prominence when it won Jeopardy in 2011. Immediately after that IBM began experimenting with a select number of industries (Healthcare, Travel and Retail) to demonstrate proofs of concept and learn what works and what doesn’t. Beginning in January of 2014, Watson expanded dramatically and is now covering 26 industries. IBM proclaims that Watson is the harbinger of a new era of computing, what they call “Cognitive Computing.” There’s just too much information being created today for any single person to digest; Watson aims to “amplify” experts’ capabilities. Doctors, salespeople, and wealth managers are but a few examples. IBM says there are four key attributes to understand:
  • Watson understands natural language (computational linguistics).
  • Watson is a voracious reader
  • Watson provides recommendations with confidence levels
  • You don’t program Watson, you teach it
Mike Rhodin, the IBM SVP who leads Watson (under an unusual board-governed structure), described the key insight about Watson: it’s not that Watson gives answers, but rather that it generates hypotheses, gives confidence intervals around those hypotheses, and provides evidence trails. It does this by ingesting enormous amounts of data, being taught by humans with a series of questions and answers, and then learning on its own as it proceeds. The more data it has, the better it performs. Watson does a better job providing recommendations for people when it knows something about them. A salesperson will sell differently to an introvert than an extrovert, as a simplified example. Watson can generate a personality profile on the basis of a person’s twitter feed or blog posts – I’m not sure how accurate it is, but the concept alone is pretty startling. Terry Jones, an entrepreneur previously associated with Travelocity and Kayak, introduced a new company called WayBlazer that uses Watson’s technology. It aims to be able to answer queries like, “I want to go on a golf trip with my buddies in October,” or, “Give me an itinerary for Costa Rica in May with my two kids.” Watson might ask clarifying questions, and then would come back with recommendations. The prototype is currently in place for Austin, but a service like this highlighted clearly what Watson has the potential to do, if implemented successfully. Another lightbulb for me was Terry’s description of Watson as a liberal arts major, not a math geek. It could do airline pricing optimization, but that’s not what you’d buy it for. WayBlazer is but one example of the ecosystem that Watson is building. Realizing there’s a shortage of skills in Cognitive Computing, IBM has teamed with ten universities to offer courses on the subject; this fall all of the classes were oversubscribed. From a standing start in January, IBM has about 100 partners and expects that to continue to grow. Watson had 1 API in January; it now has 8, with more than a dozen in development. IBM may have finally figured out how to execute at startup speed under the umbrella of Big Blue. Watson’s interest in financial services is currently very focused. Insurance is one key space, particularly around underwriting. Wealth Management is the other key area, with risk and compliance being a third. You may disagree with Watson’s prioritization, but their intentional focus is spot-on – they’ve got to demonstrate some tangible successes before they begin to branch out. Based on different discussions, Watson’s revenue will come from four sources:
  1. Consulting to investigate and establish what Watson will do for the firm
  2. Priced products (e.g., oncology)
  3. SAAS revenues from running Watson for individual projects
  4. A cut of the revenue that partners earn from Watson projects
What’s ultimately different this time? In this new IBM (a place the company has been forced to by intense competition), Watson:
  • Is playing the role of an ecosystem platform
  • Is using partners to reach consumers, realizing that IBM’s strength is as a B2B company
  • Has built a new physical space, reversing a trend of selling real estate and having employees work remotely
  • Is not trying to do this on the cheap
  • Is focused on just a few areas
What does this mean for banks and financial services firms? The IBM take is, of course, that you’ve got to be exploring Watson or you’ll be hopelessly behind. That’s overly broad, but I recommend that firms at least get up to speed on the potential of the technology and see whether it can apply to them. We’ll have to watch to see if Watson carries through on its promise, but efforts like this are a necessary (if not sufficient) first step in the right direction for IBM.