Phone Collection campaigns are very complex and must take into account several variables that, if not addressed in the right way, can prevent or slow down the achievement of company objectives.
Debtors are not all the same, there are some of which are “spontaneous“, but also complex practices that require more attention and for which a simple call is not enough to bring a person to pay off the debt. Quite often, especially referring to considerable sums to be recovered, in order to be able to finalize the recovery it is necessary to entrust an operator with good experience able to manage the situation in the best way possible.
Currently, the lists of debtors are divided and randomly assigned to operators who take care of the contacts; in this way many of the complicated practices will end up with inexperienced operators, compromising the recovery process.
Credit Collection companies need to obtain the most recoveries with the highest associated value in the shortest amount of time, which is why it is critically important to have the ability to thoroughly analyse debtors lists and know the propensity for recovery of each position, to set up consequently the best strategy and achieve goals more easily.
How is it possible to know in advance the probability of recovery associated to each position?
Thanks to Artificial Intelligence, companies that carry out Phone Collection campaigns can analyze their lists of debtors and know in advance which positions are simpler and which are more complex to recover, along with their value in economic terms. In this way, companies are able to assign the simplest practices to new operators and more complex profiles to experienced collectors, greatly increasing the recovery rate and decreasing the time it takes to reach goals.