When it comes down to writing year-in-review roundups about what surged and what didn’t in any given year, the challenge is always in not omitting something important or miscategorizing something entirely. One man’s sizzle can be another man’s fizzle after all.
And after spending week-in and week-out keeping our personal tally of what was working in a big way and what needed to just get to work, there is an awfully wide field of competitors on both sides of the Sizzle/Fizzle continuum that all could make a perfectly reasonable case for inclusion on the big list and an even longer list that at least merits a solid honorable mention.
But, tragically, rules are rules, and there can no be no winners (or winning losers) without making tough choices.
As for firms that sizzled in 2016, how about bank stocks, which helped propel U.S. bourses to record levels? The benchmark Dow is, of course, within striking distance of the 20,000-point level. Interest rates are on the rise, along with inflation, and this means that net interest margins are also going to benefit. The incoming Trump administration also is gunning for a rollback of many parts of Dodd-Frank, which should also free up capital on banks’ books.
Consumer Spending & Employment
Two data points, economic ones, could also be said to have sizzled this past year (and dovetail with the bank stock rally). The consumer keeps spending, and employment levels remain tight, auguring well for wages and, by extension, support for activity at the register, virtual and otherwise.
Acquisitions & Partnerships
What else sizzled? If you were a payments giant seeking scale along with global ambitions, acquisitions sizzled and so did partnerships.
Mastercard made a vocal statement of sorts about faster payments with its acquisition of VocaLink, garnering a presence in the U.K. and beyond via faster payments rails. Shortly thereafter, Mastercard and Visa, separately, did their deals with PayPal to make network-branded cards a warmer and friendlier option in that digital wallet. And speaking of Visa, it was a long time coming, but the deal to combine with sister firm Visa Europe finally became reality.
Yahoo & Hacking
If there was an overall theme in the Fizzle Department this past year, it was the hack. And if a fizzler lit up like the very type of firecracker you don’t want and outpaced fellow fizzlers in hacking, it was Yahoo. In September, it was half a billion users’ data stolen.
Then, in December, it was a cool billion. Then, there was speculation that the deal to be sold to Verizon for $4.8 billion might fetch a price that would be significantly under that level. The damage to reputation and user trust has been done; the question is what is to be done next, which, as recently as earlier this week, seems to suggest that, just like the show, the acquisition must go on. At what price remains to be seen (or at least disclosed publicly). Speaking of price, we do know that a bundle of personal data was sold for a cool $300,000 on the Dark Web, leaving all of us with Yahoo accounts from back in the day fearful that our digital doppelgängers are lying in wait to take over accounts when we least expect it.
But beyond Yahoo, who else made headlines of the worst sort? Bitcoin was not immune, as BitFinex was hacked and cyberthieves made off with $65 million of the digital currency. POS systems were not immune, either, at retail and hotel chains. At the latter, HEI Hotels got hit and inadvertently gave up credit card and other financial data. And just a few days ago, InterContinental Hotels Group suspected that it’s been hacked, too. Nothing like those lucrative business travel accounts to tempt those cyberthieves, we suppose. KFC’s loyalty database was hacked, further evidence of just how valuable personal data is these days. Who needs credit card numbers when you can get other goodies and open up entirely new accounts? Most recently, hackers even broke in and took over Netflix’s Twitter account.
Want another noteworthy fizzle? How about Wells Fargo, which has gained ongoing fizzle notoriety over several months, starting when the first inklings of broker malfeasance surfaced. Sham accounts, sham payments, sham activities — all in the name of meeting sales-driven quotas. Then-CEO John Stumpf went to Capitol Hill, got grilled and abandoned ship. And by the way, there were some earnings misses and, even more recently, whistleblowers pointing to fraud at the Prudential unit. But as they say, paybacks are H-E-Double Hockey Sticks as new account openings are down more than 40 percent.
Online lending, anyone? A fizzle that cut across a whole industry. The poster child here, of course, was Lending Club in 2016, which discovered improper lending procedures, leading to the CEO’s ouster. It also got hit with slowing demand for loan sales to outside investors. This last issue tended to bedevil peers, too. Oh, and regulators are eyeing the space with increasing interest — not exactly a harbinger of easy sledding ahead.
Polling And Predictive Algorithms
Almost everyone in America got something of a shock on Nov. 8 when Donald Trump won the presidency, whereas usually only half the country wakes up shocked after an election. But this time around, even members of Team Trump were pretty shocked since it was the certain, definite and carved-in-stone conclusion of pollsters, pundits and experts everywhere that Hillary Clinton was going to win the election. The polls said so and the algorithms confirmed it and so most people went into the election thinking that it was a done deal.
And lest you think we are picking on political pollsters, note that their algorithms weren’t the only ones that took a beating this year, though perhaps they took the most public one. For the last several years, the fall of the house of FICO has been a favored financial service industry prediction, spurned on by the fact that, in a world full of digital data on consumers and their habits, there should be no such thing as a thin-file applicant. Alt-lenders and alt-credit evaluators of all stripes maintained that, with the right input and algorithm, they could predict creditworthiness better than the bank’s FICO scores.
Several months of mounting defaults within the worlds of marketplace lending and subprime lending tell a slightly different tale. There are a lot of ways to evaluate a person’s creditworthiness. At the end of 2016, it is clear that some are better than others and that how good a standard is really only becomes apparent once that standard starts to fail.
The big lesson we all learned in 2016 when it comes to data and data science is that algorithms are many things, but magic isn’t one of them. They are only as good as the assumptions and data the human programmers place inside.
And so, we sign off of 2016 with the following advice: If you are looking to avoid fizzles in 2017, you might just always want to check, recheck and then check again your data and your assumptions.