Client background and business context

  • Client profile: companies offering financial services, especially in the insurance business. 
  • Proposed solution: RPA- and conversational-AI-based claims digitalisation. 

Challenges

Traditional claims processes prioritise fraud detection over customer service, which results in customer dissatisfaction. Through a combination of chatbots, analytics, machine learning, and user-centred design, companies in the insurance business can get bespoke solutions to fully meet customer demands and establish a fruitful, personalised experience. 

Our approach

Conversational artificial intelligence (AI) is a new IT paradigm that is slowly taking over the way we consume (and expect to consume) technology and, ultimately, any technology-infused product or service. Given this evolution powered by modern IT technologies – RPA, AI, ML – future human–computer interaction models will inevitably involve virtual characters supporting both enterprises and end users. 

We aim to understand exactly what challenges need to be solved for our clients to move forward quickly and to be better suited to the fast-paced business world we’re in today. 

Enter Elli-AI, a multichannel, outcome-driven virtual agent that acts as an expert human-like interface to enterprise operational systems, quickly and consistently solving service tasks at scale. Its mission: both internal and external positive impact on engagement, cost reduction, and a company-wide boost in efficiency and speed as well. 

Our projects start with a discovery workshop, at the end of which strategic goals and objectives are laid out. We understand where our client’s focus is for the next month, the next quarter, the next year, and how we, with the help of Elli-AI, can enable them to do their best against their competitors, as well as for their customers. 

We provide a thorough ROI analysis of the proposed digital solution, Elli-AI, our virtual assistant developed in-house and specifically programmed to meet our clients’ business needs. Decisive KPIs are specified as well. 

Having all this information, we can move on to fully determining the solution: the solution scope, a prototyping roadmap, as well as an estimate of the production timeline and the necessary investment. 

Next, we’re ready to develop the prototype as planned. We assess the results and adjust priorities if necessary. 

We stay on the project for post-launch monitoring and optimisation to ensure that the solution is exactly what our client needs to perform better, whether internally or externally. We monitor the established KPIs, optimise the solution accordingly, and adjust KPIs if necessary. 

Our aim is to be both efficient and effective in responding to our clients’ challenges and concerns: we employ technical and business know-how in order to provide our clients with the right digital solutions, optimally designed and developed to fit their business needs perfectly

Technologies used in this case study

Technologies

  • Cognigy
  • Google DialogFlow
  • Microsoft LUIS
  • UiPath 

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