BigProfiles Platform EN LORENZO
The AI autopilot for predictive analytics Autonomous, scalable and streamlined end-to-end predictive modeling, from data cleaning to real-time predictions Book a demo Let BigProfiles model and predict For each predictive model, BigProfiles performs data cleaning, tests dozens of Machine Learning algorithms and trains the best one, deploys the model and integrates it in real time […]
Debt collection and the banking sector: how Artificial Intelligence supports precise and advantageous collection
Debt collection and the banking sector: how Artificial Intelligence supports precise and advantageous collection The COVID-19 pandemic has brought about such economic instability that most governments have proposed moratoriums on insolvencies. At the same time, many institutions have had to quickly adopt new digital services to continue serving customers, regardless of how prepared they were […]
Artificial Intelligence and Phone Collection: assigning the best agents to the most complex practices
Debt collection campaigns can be very complicated to manage and the companies that manage them must take into account numerous variables in order to achieve their objectives, such as the propensity of a debtor to repay their debt and the economic value that has to be recovered. Currently, the processing method used by most companies dealing with Debt Collection consists of randomly assigning the contacts present in the lists to the operators, without performing any prior analysis on them.
BigProfiles Platform
Predict customers behaviour Predict purchases, churn, cross-selling, debt repayments and much more with Artificial Intelligence. How it works The power of automatic machine learning Train a predictive model just by plugging in your CRM Whether it’s purchase or churn, each behaviour you want to predict needs its own predictive model. By connecting your CRM, BigProfiles […]
How Artificial Intelligence allows for the optimization of debt collection services of banking and insurance companies
The current economic and commercial instability is playing an increasingly important role in the world of debt collection, with particular reference to companies in the banking and insurance sector.During the pandemic crisis, both of these sectors provided the necessary liquidity to companies to relaunch themselves, but now, with the challenges arising from the increasingly uncertain geopolitical and economic situation, they must be prepared to face the growing difficulties that are arising as a result of the struggles of individuals and companies to pay their debts.
Debt Collection and Utilities: Artificial Intelligence enables more effective credit management
The Utility sector is experiencing very complex and delicate phases: the conflict in Ukraine and the international tensions that have arisen have led to a lack of energy supply and a consequent increase in market prices which has affected both individuals and businesses.
Telco and Debt Collection: how to best implement it in 2023
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.
Phone Collection and Artificial Intelligence: how prioritizing lists facilitates the achievement of goals
Companies that work with debt collection, and especially Phone Collections, must be able to establish strategies that cope with different levels of difficulty, some related to the very nature of the debt to be recovered and others related to the debtor’s propensity to pay, or not to pay, their debt.
Debt collection: predict the behaviour of each debtor to increase the recovery rate of Phone Collection campaigns
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.
Artificial Intelligence and Debt Recovery: Value Based Predictive Models
Any company that deals with debt recovery needs to know in-depth the positions that make up the list of debtors and the recoverable values associated with it, in order to be able to set up strategies that allow it to achieve the pre-set objectives in the shortest possible time. and with the best possible result.