It’s that time of year again! Sixty-four college basketball teams will have earned their way to an opportunity to compete in one of the largest and most competitive tournaments in the world to claim the crown of national champion. But it won’t just be the player’s families and friends who will be tuning into the games; it’s estimated by the American Gaming Association that Americans spent $9.2 billion on March Madness wagers in 2016.
“Picking your bracket” is the most common form of wagering, particularly amongst the office and casual betting groups. This requires an individual to assess the outcomes of the first round and all subsequent rounds before the tournament begins. That’s sixty-three games over nineteen days. If you think that is hard, you would be correct, as it is estimated that the odds of choosing a perfect bracket has been calculated at 1 in 128 billion, with some estimates going even lower.
One of the main features that makes this task so difficult is forecasting the results of six rounds of games before the first game has taken place. This forces you to use only the information that you have at the time on each individual team and match-up. During the tournament, a star player could get injured, a bout of the flu could affect a couple players, or a team’s plane could be late and the hotel noisy – all of which could happen and have a significant bearing on whether that team makes it all the way. Being wrong on the early rounds can have lasting consequences: if you eliminate the eventual winner in the first round, it can be tough to stay in the game at all.
But what if you could re-compute your bracket after each round? Sure, you (and the rest of the United States) didn’t pick the No. 15 ranked Middle Tennessee to upset No. 2 seed Michigan State in the 2016 tournament’s first round, but upsets happen. Since you could re-compute your bracket, you could then compare Middle Tennessee against their next component. You might even give the Blue Raiders some extra consideration now that you know they could beat a powerhouse. If you could amplify this across your entire bracket for the whole tournament, and you’ll certainly fare much better than if you were stuck with the choices you made at the beginning of the tournament.
Now ask yourself, what does picking your March Madness bracket have to do with debt collection? The answer is everything. Think of picking your bracket using only the information you have on day one as the same as planning your treatment strategies based upon a credit bureau score. Assuming the credit bureau can match a consumer’s account with the out-of-date data provided, it’ll be at least 30 days before the score reflects the latest changes. You will have worked the account without taking into consideration external treatments...and the tournament will be over.
But what if you could re-compute a consumer’s propensity to pay on a nightly basis based upon the performance of the account? You may have made a phone call or sent an email, the debt just got one day older, or your information was enhanced from skip tracing – all of these change the expected performance of the account. With this increase of information, you could start defining your daily dialer strategies and letter campaigns based on the information at tip-off, rather than at the start of the tournament.
You now know, daily, which accounts were winners and losers, and additionally, you probably have that information going back multiple years. If you want to significantly increase the probability of collecting on an account, you need to leverage the years of experience you have in your organization’s data. NLP Logix can show you how applying artificial intelligence through machine learning can greatly increase per account performance. Let us show you how to re-score your accounts on a nightly basis to get that competitive edge over those using static treatment strategies.
Like any team’s tournament performance, a consumer’s propensity to pay is subject to variables that change daily. If the main variables you use to drive your dialer strategy – like credit score and available credit – don’t change on a frequent basis, you’re leaving money on the table.
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