Health and Hospitals
One of the biggest challenges in recovery and preventive management is ensuring outreach isn’t just effective, but also timely and well-received. At Algonew, we know the channel is as critical as the message. That’s why we design intelligent multi-channel strategies that cover more ground—with surgical precision.
At Algonew, we know that anticipating customer behaviour isn’t just a tactical advantage—it’s a strategic necessity. Predictive technologies, especially those powered by artificial intelligence (AI), have become indispensable for the early detection of financial risk signals and effective delinquency prevention.
At Algonew we understand that operational efficiency and customer experience need not be at odds. This is especially true in pre-collections, where well-timed, tactful outreach can mean the difference between preventive recovery and solidified debt.
At Algonew we firmly believe that the most critical stage of the credit cycle does not begin with default—it starts much earlier. Pre-collection represents a strategic window to anticipate customer behaviour, build healthier relationships, and, most importantly, significantly reduce early delinquency.
The data is overwhelming: 1 in 2 customers (49%) abandon calls due to long wait times. This reality, which directly affects business profitability, finds an effective and scalable solution in Artificial Intelligence.
In recent years, artificial intelligence (AI) has become an increasingly prevalent technology in the healthcare sector, with virtual assistants being one of its standout applications. These computer programs can be of great assistance to both patients and physicians.
A recent report published by the World Health Organization (WHO) highlights the growing use of Artificial Intelligence (AI) in healthcare, pointing out both the opportunities and challenges this poses for governments, providers and communities.
A recent report published by the World Health Organization (WHO) highlights the growing use of Artificial Intelligence (AI) in healthcare, pointing out both the opportunities and challenges this poses for governments, providers and communities.
Medicine is a field in constant evolution, where precision and speed in diagnosis are essential for patient care. In this context, multilayer neural networks have emerged as a revolutionary tool that has transformed the way medical data is analyzed and interpreted. Let’s focus on medical image analysis, disease diagnosis and…
In May 2023, the World Health Organization (WHO) issued a statement calling for caution in the use of AI-based tools that use large linguistic models. The aim is to ensure the safety, autonomy, and well-being of individuals, as well as to preserve public health. As these tools become increasingly popular…
