Every sector is constantly changing, and it is undeniable that in recent times, mainly due to the health emergency, a series of processes have rapidly developed that up until no more than three years ago seemed distant and only feasible in the long term.


The Telco sector is no exception and, although it has been able to find some benefit in the need to rethink work-life with a view to a greater digital presence and smart-working, was faced with new challenges related to the economic crisis and the increasing competitiveness in the market. All this has resulted from the rapid birth of new competitors who have given rise to a real price war, in which every company needs to continuously rethink their strategies in order to maintain their acquired market share without losing service quality.


The latest negative aspect is linked to the energy crisis that has increased the costs of the management and maintenance of the network infrastructures that are the basis of national connectivity.


In this context of crisis and uncertainty, credit and debtor management have assumed a central position within the telecommunications business, to the point of requiring a rethinking of the credit management processes that is increasingly oriented towards greater thoroughness, precision and efficiency.


In order to manage the chain of credit in the most efficient way possible in a sector where the exchange rate and above all non-payment is very high, it is necessary that Telcos make great strides towards those technologies that can simplify their internal processes and analyse large amounts of data, such as Artificial Intelligence, in order to be able to always make the best possible decision.



Using Artificial Intelligence it is possible to carry out preventive analysis of the list of customers and succeed in implementing solutions capable of exponentially increasing the chances of recovering their debts while reducing costs at the same time:


  • Reduce the recovery time by eliminating the spontaneous segments from processing so as to focus on those segments that actually need to be contacted in order to recover their debt;
  • Identify the recovery potential for each debt position.
  • Know the highest potential value recoverable of each debt;
  • Assign the most experienced operators to the most complex practices.


Attraverso l’implementazione di classi tecnologiche innovative come l’Intelligenza Artificiale all’interno dei proprio processo di recupero del credito, quindi, le Telco avranno la possibilità di valutare in anticipo la situazione delle proprie liste di debitori e utilizzare di volta in volta la migliore strategia per riuscire a minimizzare il numero di crediti insoluti e, di conseguenza, aumentare i guadagni dell’azienda.

Therefore, through the implementation of innovative classes of technology, such as Artificial Intelligence, within their credit recovery process, Telcos will have the opportunity to evaluate in advance the situation of their debtors lists and use the best strategy each time in order to minimize the number of outstanding debts and, consequently, increase the company’s earnings.


How is it possible to use Artificial Intelligence within the Debt Recovery process?


Thanks to BigProfiles, the first Artificial Intelligence platform for debt collection, you can use the power of machine learning to analyse the list of debt positions and be able to always put into practice the most suitable strategy to achieve your goals and reach the the top of your target market.