As applications containing Artificial Intelligence (AI) algorithms become more and more part of our daily lives, in parallel we see a tremendous interest on AI in business life as well. Specifically, a type of Machine Learning approach named Deep Learning (DL) is becoming so popular due to its potential to be able to mimic human brain through Neural Networks approach. DL, together with Natural Language Processing (NLP) capabilities can address several business challenges that were thought to be solved only by human intervention until now. Thanks to the advances in computing power and big data, most of the things considered as science fiction in AI are now becoming mainstream.
Some of the challenges modern organizations face today, can be solved with correct application of deep learning - NLP algoryhtims. We have practical experience in solving below challenges with unique DL approach:
Call Center Capacity:Especially during peak times, such as new campaign runs or service outages, we see a tremendous increase in the calls towards call centers, putting call center managers in a dilemma of long waiting queues vs increasing employee costs. Automation in the call centers would keep the service level high at all times (24/7) while keeping the costs at minimum.
FAQs:A great majority of customer inquiries in call centers can be grouped and answered under a common FAQ list, therefore minimizing a need for an actual human operator. In order to clasify inquiries, pick right answers and maintain such a FAQ list are a great example of a deep learning application.
Fraud Detection:A classical approach for fraud detection is to maintain a list of rules / models that can be labeled as fraud. With deep learning, a learning algorthym can maintain those rules, include new rules and monitor all activities for suspicious flags, again with no or minimum human intervention.
Quality Issues in Customer Interaction: There are several cases where call center agent does not fully undestand what the customer is asking for, or cannot find - phrase the correct reply, thus leading excess times on the call and dissatisfaction of the customer eventually. Also, because of increased tension in the dialogue in such cases, emotional responses can be exchanged. However, a clear algorythm can ignore emotional responses by the customers and just focus on answering the inquiries no matter what happens. This also helps avoiding communication accidents and bad reputation.
In adesso, we have a skilled DL team to support our customers in the following DL applications: