Motivations, Classification and Model Trial of Conversational Agents for Insurance Companies

Advances in artificial intelligence have renewed interest in conversational agents. So-called chatbots have reached maturity for industrial applications. German insurance companies are interested in improving their customer service and digitizing their business processes. In this work we investigate the potential use of conversational agents in insurance companies by determining which classes of agents are of interest to insurance companies, finding relevant use cases and requirements, and developing a prototype for an exemplary insurance scenario. Based on this approach, we derive key findings for conversational agent implementation in insurance companies.Comment: 12 pages, 6 figure, accepted for presentation at The International Conference on Agents and Artificial Intelligence 2019 (ICAART 2019

Global Mobility Chatbot: Chatbot model to improve mobile employee experience

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing IntelligenceThe Global Mobility Industry is the area that comprehends the emerging internationalization and growth of companies outside borders. Its overall core essence is to support businesses all over the world in setting up operations, by assigning employees in other cities or countries outside the company's headquarters. These operations have intrinsically a set of challenges and opportunities that both companies and employees need to face while on move. To face these challenges and accomplish international move tasks and goals, software houses have been developing over the past years platforms and solutions to face each of the international moves phases. However, it's hard to keep every task, request, event, and everything on track and both accomplishing and managing it can become a struggle when the number of employees on assignment multiplies and grows year after year. The usage of Chatbots is not new in the tech world, but the technology, features, and capabilities of those have been growing and growing, and those are gaining a significant space and importance in a variety of different businesses and social fields, such as sales, real state, eCommerce, customer support, and even marketing and enterprise bots. Its capacity to work as a true virtual assistant, able to respond and support users 24/7, it’s becoming something more and more desirable for every company and employee. This dissertation has the goal to, first, make a deeper research and study on the Global Mobility Industry and the Chatbot usage and development. Defining and stating how helpful and valuable a chatbot could be when integrated with a Global Mobility software solution. By concluding this study, 2 built artifacts will result from it, specifically a backlog full of business requirements to accomplish, and a prototype of the chatbot using one of the top Chatbot enablers platforms in the market. To work and develop the artifacts, this dissertation will follow the design science research methodology, whose evaluation phase will be supported by a user testing session and a structured interview with carefully selected participants, with pre-defined closed and open-ended questions. Everything resulting from this dissertation will leave open space for future enhancements, by incrementing the value and functionalities of the chatbot, and potential real-world application and integration of it in Global Mobility softwares and platforms

Assisting Provet Cloud Users With Speech Recognition Technologies

Tämän työn tarkoituksena oli luoda prototyyppi, joka yhdistää Google Assistantin ja asiakasyrityksen ohjelmiston, Provet Cloudin. Tarkoitus oli tutkia, olisiko eläinlääketieteen ammattilaisten mahdollista ja hyödyllistä käyttää äänentunnistusapuvälineitä heidän työssään. Tutkimus aloitettiin määrittämällä sen laajuus. Tarkoituksena oli mahdollistaa tiedon haku Provet Cloudista puhumalla Google Assistantille englanniksi. Prototyypissä oli oltava mahdollista kysyä tulevia ajanvarauksia tiettynä päivänä. Lokalisaatio ja muut virtuaaliset avustajat jätettiin tämän työn ulkopuolelle. Seuraavaksi määritettiin käytettävät tekniset komponentit. Tarvittavien komponenttien opiskelu ja niiden päälle rakentaminen vei paljon aikaa, erityisesti Dialogflowin ja Kuberneteksen opiskelu. Lisäksi työn edetessä tuli ilmi, että uuden käyttötapauksen lisääminen oli suhteellisen työlästä. Asia monimutkaistuu entisestään, jos niissä halutaan käyttää edelisen keskustelun kontekstia. Käytettävyystestit suoritettiin asiakasyrityksen ohjaajan ja eläinlääketieteen ammattilaisen kanssa. Lisäksi kaksi ohjelmoijaa katselmoivat projektin aikana syntyneen koodin keskittyen eri alueisiin. Yksi kehittäjä tarkasti Provet Cloudiin tehdyt muutokset ja toinen Provet Flowin koodin. Tämä työ saavutti päämääränsä eli integraatio Google Assistantin ja Provet Cloudin välillä onnistui. Käyttäjä pystyy kysymään Google Assistantilta, mitä ajanvarauksia hänelle on tulossa tiettynä päivänä. Testauksessa tuli kuitenkin ilmi, että Google Assistantin käyttö on melkein mahdotonta eläinklinikalla tai -sairaalassa ympärillä olevan hälinän vuoksi. Sitä voisi kuitenkin käyttää kotona, kun valmistautuu seuraavaan työpäivään. Jatkokehitys koostuu lokalisaatiotuesta, useammasta käyttötapauksesta ja tuotantojulkaisusta. Lisäkehitystä tarvitaan, jotta prototyyppiä voidaan esitellä jossakin, esimerkiksi messuilla.The purpose of this study was to create a proof-of-concept application which integrates Google Assistant and the case company’s application Provet Cloud. The main reason for this was to study whether it is possible and would be helpful for veterinary professionals to use speech recognition in their work. The study started as defining the scope. The goal was to build a solution where one can request data from Provet Cloud by talking to Google Assistant in English. The solution included one use case where a veterinary professional can ask incoming appointments on a specific date. Localization and other virtual assistants, like Amazon Alexa and Apple’s Siri, were left out of the scope. After scope validation technical stack was decided. Studying technical stack required a lot of time, especially Dialogflow and Kubernetes. During solution development it became clear that adding an intention in Dialogflow and providing data for that requires a lot of work. It’s even more complicated when one wants to build conversations that continue. Usability tests were carried with the supervisor and a veterinary professional. In addition, the developed code was reviewed by two developers focusing in the different areas of the proof-of-concept. One developer reviewed changes done in Provet Cloud and the other reviewed the code of Provet Flow. This study achieved its goal and integration between Google Assistant and Provet Cloud was possible. A user can ask his or her appointments on a specific date using Google Assistant. However, it became clear that the end user wouldn’t use this on workdays at the veterinary clinic or hospital due to surrounding distractions, but at home to prepare for the next day. Future development consists of support for localization, more intents and publishing the Action. Additional development is needed to show the proof-of-concept, for example, at a business affair