RPA Complaints Management

Complaints Management

The entire future relationship with the customer depends on proper complaint handling, which is why it is essential to streamline procedures and offer an efficient and effective service in resolving the complaint. 

By its very nature, complaints management requires particular attention and speed, elements that collide with criticalities typical of complex systems: the complaint must be collected, analysed, verified and then resolved positively or rejected. It is a complex process that requires a considerable commitment of resources. 

Intelligent automation deploys tools capable of emulating human interaction, interpreting requests and triggering initial checks, and delegating operator intervention only to the most complex cases (autonomous resolution in 80% of cases and 30% reduction in costs, IBM survey). 

Criticalities

Data extraction from multiple channels and systems

Customers, suppliers, and administration, but also social media, email and instant messaging: the company communicates with a multitude of subjects and systems that are never the same. The data received must be manually extracted and converted at great expense in terms of time and effort. 

Multiple interactions with customers

Customers use different systems at different times, making it difficult to create a linear follow-up. 

Interpretation of unstructured data

The difference in operating methods leads to data without a predefined model, which are cumbersome, difficult to understand and ambiguous. 

Third-party system audits

The fragmented nature of the documents requires numerous conversions, making manual verification of the data indispensable. 

RPA Criticalities
RPA Solutions

Solutions

Extracting information from archives and databases

RPA systems collect information from multiple sources and organise it into databases for future use, increasing the algorithm's ability to resolve complaints on its own.  

Natural language normalisation and interpretation

Pattern recognition and natural language processing algorithms are able to assign meaning to unstructured data and integrate them into existing databases. 

Automatic responder and virtual assistant

Chatbots and Artificial Intelligence can emulate human interaction and solve most cases without operator intervention. 

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