Customer Service Model
In recent years, the Poste Italiane Group has initiated a digital transformation geared towards operational efficiency and effectiveness, generating positive social impacts, in line with the UN Sustainable Development Goals 2030, in particular Goal 8 (decent work and economic growth) and Goal 10 (reducing inequality).
On the Goal 8 front, AI-based solutions have strengthened and supported internal career paths, creating new roles and providing training on new skills (e.g. those related to the AI-driven knowledge management system). Artificial Intelligence is therefore supporting growth, specialisation and the centrality of the human relationship. In line with Goal 10, the Digital Assistant (self-assistance with AI) and related projects – including biometric voice recognition and personalised experience features – are progressively expanding access to digital services, handling more than 100 million interactions and increasing citizens’ and businesses’ familiarity with new service channels.
AI Models in Customer Care
In order to enhance the capacity and effectiveness of the Customer Service response, the Poste Italiane Group promotes automation in the management of support requests through Artificial Intelligence, to achieve greater customer autonomy in resolving simple and standard needs, optimized of response times, an increased customer satisfaction, and the transformation of internal operations. With a broader view of evolving the way operators work to serve customers, through a fruitful effective Human-Machine collaboration, the Poste Italiane Group has planned several initiatives. Among these, the first initiative launched is a new Knowledge Management model (AI Know) based on generative AI, which provides product information and procedures useful for managing customers to internal staff via real-time conversational chat. The source content (knowledge base) is certified and internal to the Group. Customer service evaluates the responses through structured feedback generating a virtuous circle of continuous improvement of the model. Both content maintenance and feedback are worked on by specialists with new skills (future proof competence model with human in the loop). Further initiatives also follow these principles and contribute to making the role of customer service operators increasingly sustainable. To date, AIKnow is present in several branches and has generated over 4 million interactions with an average accuracy of 95%.
On the customer side, the Poste Italiane Group’s AI-enabled self-service display (Digital Assistant) also allows customers to familiarise themselves with the new AI tools. These services (which have already been available for some time and will be increasingly enhanced) contribute to generating digital inclusiveness among citizens (more than 100 million customer-AI interactions for assistance in the various business perimeters since the introduction in 2019).
The bouquet of initiatives on the digital transformation of Customer Service, both towards internal staff and external customers, is generating social sustainability in line with UN Agenda Goals 8 and 10: in this respect, it received the Digital Sustainability Award from the Foundation for Digital Sustainability.
Digitalisation of back office processes
In order to reduce the negative impacts on customers being served and to optimise and mitigate the risks associated with the service model, the Group is digitalising back office processes with the aim of optimising file handling times, increasing customer satisfaction and improving the efficiency of internal operators, and reducing paper usage.
Biometric customer recognition
In order to simplify access to Customer Service, biometric recognition (by means of a voice print in combination with a “secured” number) was implemented for contacting the Customer Service.
Adhesion is by means of an omnichannel logic from web and telephone, supported by AI throughout the interaction. Subsequently, every time the customer contacts the financial services support (as a first scope of application that can be extended to other support areas), the customer can be identified using only voice in the interaction with both the digital support and the operator.