Using IoT data, empirical evidence shows the effectiveness of machine learning algorithms in predicting fraud in property insurance

• Main Authors: Victor, Ceronmani Sharmila, Logeshwara, Rishivarthan, Chandra, Abhinay
• Format: Conference Proceeding
• Language: English
• Subjects: Algorithms; Insurance; Machine learning
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0215556

In the insurance market nowadays, data is carrying the major asset and playing a key role. The insurance sector is crucial in today’s world. More information is available to insurance transporters than ever before. We can identify three major eras in the insurance industry’s more than 700-year history. From the 15th century to 1970, the manual age defined the industrial era. from the 1960s to 2000, we were in the systems era; and now, from 2001 to 2020, we are in the digital era. The fundamental insurance sector has been shaped by trust in data analytics and the adoption of changing technologies to maintain and preserve capital. This has been the primary corporate objective throughout all three eras. However, the challenge of advanced analysis remains, as current analytical models and algorithms are inadequate to meet the needs of insurers. This challenge can only be overcome through the use of machines.