Abstract
This paper presents a case study of the Project ‘DSS INSURANCE HUB'. Specifically, research activities are carried out in the context of digital transformation in the insurance service sector. In the first part of the paper, a core of Key Performance Indicators (KPIs) of insurance service performance is identified, mainly tracking agents' activities, starting to the Plan, Do, Check, Act (PDCA) process mapping of the insurance activities about claims. Then the study focused on the implementation of a Long Short Term Memory (LSTM) artificial neural network predicting the value of agent-related KPIs. In particular, the neural network is tested on the prediction of the KPI called SP defined by the ratio between the cost of the claims and the insurance premium collected. In order to validate the LSTM model, further artificial records (AR) are added for the training dataset construction, by generating 2.800 records of variables. The LSTM-AR increases of 25% the LSTM performance. The adopted approach is typical for real cases of study where often no much data is available. The LSTM model, created for the SP prediction, is suitable to calculate the value of other KPIs. The formulated KPI dashboards are implemented in a Decisional Support System (DSS) platform providing the agent activity and company information, and opportunities to improve the business processes.
Highlights
A Decision Support System (DSS) is an essential tool in various sectors as it is powerful in finalizing the information extracted from the numerous data available to corporations
Monitoring Key Performance Indicators (KPIs), the company working in insurance services, is able to evaluate its performance during the time, by focusing the attention on processes having the greatest impact on company productivity
The DSS, together with the Long Short Term Memory (LSTM) neural network, solves the critical issues highlighted in the PDCA regarding the efficiency of the activities
Summary
A Decision Support System (DSS) is an essential tool in various sectors as it is powerful in finalizing the information extracted from the numerous data available to corporations. The DSS systems use Artificial Intelligence (AI) algorithms that allow to increase the knowledge of the mechanisms that enable to optimize the management of company processes. For these reasons, DSS systems have been used by an increasing number of companies active in the insurance, health-care, banking and retail sectors in recent years [1,2,3]. This work proves that innovative tools, such as AI [4],[5] and Data Mining (DM) algorithms in combination with KPIs can certainly bring benefits in the insurance service sector, facilitating the improvement of processes.
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