Usage of algorithms and intelligent systems in the financial engineering process of insurance business in the VUCA world

Ratnakaram, Sunitha and Chakravaram, Venkamaraju (2024) Usage of algorithms and intelligent systems in the financial engineering process of insurance business in the VUCA world. AIP Conference Proceedings, 3217 (1): 020018. ISSN 0094-243X

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Abstract

Algorithms and Intelligent Systems (A&IS) have the potential scope and play a major role in the Insurance business in the VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) world. A&IS is transforming the major sectors of the economies worldwide. Particularly in the Insurance business, these two technologies are influenced by the ever-changing game rules of the sector. This sector has started using A& IS as one of the important tools in the design and development of Financially Engineered (FE) insurance products. Also, Insurance companies are using these technologies in their core business operational areas. FE is a process of creating innovative financial and insurance models using financial theory, financial mathematics, statistics, economics, econometrics, computer software, and other computational intelligence systems like algorithms, intelligent systems, machine learning, deep learning, etc. The main focus of the present research study is, how A& IS are contributing or playing a major technical tool role in the financial engineering process of the insurance sector. A& IS-enabled financial engineering process is happening at the product design, and development stage. Also, these are used in the core insurance business operational areas. These areas are, identifying customer behavior to convert and list them as prospective customers, filing of applications, underwriting process, claim settlement, fraud detection, reinsurance [15] [8], etc. Exploratory cum Descriptive research methodology was followed in the present study by researchers and proved finally the significant role of A&IS in the financial engineering process of the insurance business.

Item Type: Article
Keywords: Computer software | Deep learning | Artificial intelligence | Machine learning | Engineers
Subjects: Social Sciences and humanities > Decision Sciences > Information Systems and Management
Social Sciences and humanities > Economics, Econometrics and Finance > Banking and Finance
Social Sciences and humanities > Social Sciences > Social Sciences (General)
JGU School/Centre: Jindal Global Business School
Depositing User: Dharmveer Modi
Date Deposited: 18 Jan 2025 04:59
Last Modified: 18 Jan 2025 04:59
Official URL: https://doi.org/10.1063/5.0234840
URI: https://pure.jgu.edu.in/id/eprint/9019

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