Don`t talk to strangers..
How come you never learned the golden rule
Don’t talk to strange men, don’t be a fool
I’m hearing stories, I don’t think that’s cool
Rick Springfield..Don’t talk to strangers (1982)
Yes rocking Rick Springfield may have issued a stern warning about the big bad wolf but Malcolm Gladwell`s latest book `Talking to Strangers` (2019) has been able to join the dots observing a pattern of recurring events. Malcolm suggests a correlation based on a series of unfortunate consequences that initiates with the meeting of….strangers.
Who`s the worst British Prime Minister in modern times?
Right now the first name that pops into everyone`s mind is probably David Cameron. During his time as Conservative leader (2010–16) he faced pressure from the public and his fellow Ministers of Parliament to allow a Brexit referendum. With hindsight, I believe that the title for the worst British Prime Minister in modern times goes to Neville Chamberlain (1937–40) and for what? Neville will always be remembered for his meeting with a stranger…. Adolf Hitler.
Neville was famous for negotiating the partition of Czechoslovakia with Adolf Hitler at the Munich conference in 1938. Chamberlain believed that by appeasing Nazi Germany he could secure peace in Europe. All Neville actually did was to condemn millions to live under a brutal murderous regime and bring a world war closer.
Neville actually met Hitler three times in 1938 and was not able to grasp his real intentions, whereas many of the world leaders at the time, including Winston Churchill, never met with Hitler and Churchill figured him out to be a potential tyrant-in-waiting.
Stranger Things
Was Neville really such an ingenuous and naïve judge of character? Malcolm is kinder to Neville than most historians. Malcolm provokes us to consider if we would have done any better than Neville. Certainly the evidence suggests not; given the fact that people whose job it is to look strangers in the eye can be fallible in their judgement: Let`s consider some examples.
1) Judges who set bail have the power to establish the monetary amount of bail which is a major factor to determine if the defendant can be released conditionally or incarcerated. Malcom shares information regarding a bail study performed by a Harvard economist, three elite computer scientists and a bail expert from the University of Chicago. This study shows computers using Artificial Intelligence (AI) beat humans hands down. Operating on the same information about an applicant but without the personal appraisal of a human judge, computer decisions were 25 per cent more accurate in predicting which applicants would not show up for trial or commit further crimes while on bail. Was Churchill using a subconscious AI model to judge Hitler?
2) Daniel Kahneman’s — ‘Thinking, Fast and Slow’ (Nobel Prize in Economics 2002) discusses a study that shows a prisoner’s chance of parole depends on when the parole judge hearing the case last took a break. As judges tire and get hungry, they slip towards the easy option of denying parole. It would appear that in order for Lady Justice to be impartial to wealth, power, or other status she must both be blind and well fed.
3) Malcolm reports that the Transportation Security Administration (TSA) often acts like a mystery traveler and actually places weapons into luggage to test the screening system. About 95% of the time, the weapons go undetected! And before reading this `fun fact` I bet your biggest flying concern was turbulence. The TSA agent knows that the probability of actually finding a weapon is extremely low (needle in a haystack kind of low), so even when a TSA agent sees a suspicious object he will let it pass if the accompanying mystery traveler/strange is judged to be very ordinary looking.
I read the news today, oh boy!
Malcolm then makes reference to other unfortunate events that involve mundane interaction between strangers that regularly makes the news. Such as police officers stopping minorities with lethal outcomes, the night after a college party involving a `he said, she said` accusation, and of course financial con-men like Bernie Madoff misleading investors. Let`s not forget that many unfaithful spouses go undetected for a lengthy time in extramarital affairs; and spouses are not exactly strangers.
So why is it that we all believe that we have special insights to assess a person`s character from their outer appearance? Sadly our over confidence in being a perfect judge of character is embedded in human nature. No one would ever consider hiring a baby-sitter without a lengthy personal interviewer and even most bosses would like a face-to-face meeting with a new employee that may be even two or three levels below in reporting hierarchy. However, there is a growing list of companies that are looking to automate portions of the hiring process using AI but it`s early days for hiring to be fully automated. Seeing is believing!
Which brings us to Insurance…data analytics to the rescue.
We know that our industry is not perfect. There is a vast insurance protection gap, mis-selling of insurance policies has led to record financial penalties, early cancellations/ poor persistency of polices that did not meet the client`s real needs and of course the tarnished image of a slippery insurance salesman is embedded in our folklore.
The Edelman Trust Barometer 2019 ranks trust in businesses. Technology is way at the top with 78% of respondents indicating trust, however Financial Services is ranked 15th with a corresponding 54% trust factor . LIMRA`s 2017 Insurance Barometer Survey also identified trust issues (both of agents and insurance companies) as prime reasons why people don`t buy life insurance.
Has anyone stopped to consider that the trust issues regarding insurance is rooted in the flawed human interaction between strangers (agent and client). And since those sales meetings are the foundation to our industry; might it be that our financial houses are built upon sand?
I don`t think that insurance agents are more or less inefficient than professional judges when they conduct face-to-face meetings.. but no one has performed a study of the resulting inefficiencies when insurance agents pitch to potential clients. What should we do to lend a helping hand to our agents?
1) Consider incorporating data analytics and predictive modelling to assist the sales agents e.g assessing client`s propensity to buy and thus identify interested leads, introducing Artificial Intelligence (AI) for `needs analysis` at point of sale, assess likelihood to cancel to improve persistency.
2) Take a deep dive into what are the sources of the `trust` issues between insurance companies/agents and their clients. Certainly we can improve how we remunerate agents (high up front commission leads to high pressure tactics), improve agents` training and simplify policy wording to name a few.
3) let’s try to learn from Ben Feldman. Ben who? Ben is considered to be the world’s most prolific life insurance salesman. He worked for New York Life (USA) and sold US$1.5 billion of face value between 1942 and 1993. We all like to read about Michael Jordan, Pele, Usain Bolt but alas we are amiss about the most successful life agent. Why the hubris? Don`t we think that we can learn something from the best life insurance salesman? Books about the Feldman method are available on Amazon.
I believe that the main driver for improved trust during the life insurance transaction is first admitting that meeting up with strangers is fraught with misunderstandings and misconceptions. With that realization, rethinking the sales process is likely to deliver considerable upside with little or no downside. Perhaps Mark Carney (Governor of the Bank of England) summarized it best with his wise words … `Trust arrives on foot and leaves by Ferrari`
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