Very often, the success of Debt Collection companies that carry out Phone Collection campaigns depends on the number of collections they manage to carry out in the shortest possible time or on the total economic value they manage to recover.
In order to set up the best possible strategy and achieve their goals, companies need to carry out in-depth analysis on the various types of debtors and debts that make up the different portfolios.
Regarding the types of debtors, in addition to the spontaneous ones , within the list there will be a set of people more or less inclined to repay their debt.
Depending on the company objectives, whether they are linked to the number of recoveries made or to the total economic value of the recovered, being able to know the probability of recovery of each debt or its expected recoverable value allows companies to implement winning strategies.
For example, for a company that needs to recover the largest number of debts in a limited time, it would be advisable to first identify the spontaneous segment and, subsequently, those profiles with the highest propensity to repay their debt, so as to remove the first from the initial processes and immediately have their operators concentrate on the latter.
In the event that a company aims to recover as much money as possible from its list of debts, it would be necessary to carry out an analysis of the expected recoverable value of each debt, in order to identify those with the highest expected repayment and invest your resources in them.
How is it possible to extrapolate all this information from your lists?
Thanks to the Artificial Intelligence of BigProfiles it is possible to carry out all these predictive analyses in a very short time. Being able to get hold of all this information in advance allows companies to increase their recovery rates and optimize campaign times and costs.