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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM34855

Insurance Premium Prediction Using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM34855

Volume:

8 |

5 |

May 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/ijsrem34855

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PN

Pranjal Nimbodiya

PO

Pranav Ojha

RJ

Ruchir Jain

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Abstract

RiskInsight represents an innovative company poised to transform the world of insurance by applying state-of-the-art machine learning techniques. The focus of this project is the Insurance Risk Assessment System, a high-level framework carefully designed using the Python programming language and the sklearn library. Anchored by unprecedented accuracy and operational efficiency, RiskInsight enters the field of risk assessment with unwavering determination. Using the power of advanced algorithms inspired by artificial neural networks, the system navigates huge historical data and evaluates real-time risk dynamics. The cornerstone of RiskInsight is its in-depth analysis of various risk factors carefully curated in a robust database. Combining machine learning capabilities and domain expertise, RiskInsight seeks to redefine the boundaries of risk assessment by transcending traditional paradigms. The goal is to bring about a paradigm shift in super forecasting and provide stakeholders with insights that promote fairer payment structures and informed decision-making. With its innovative design and flexible functionality, RiskInsight promises to catalyze major changes in the insurance ecosystem. By providing accurate payment forecasts and advanced risk management strategies, the platform aims to enhance the efficiency of insurance operations. A testament to its transformative potential, RiskInsight is poised to usher in a new era of efficiency and equity in the insurance industry and sets a precedent for technological innovation in risk assessment and predictive systems.

KEYWORDS

Machine Learning Fairer Payment Structure Efficiency Transformative Potential

Cite This Article

Pranjal Nimbodiya, Pranav Ojha, Ruchir Jain, "Insurance Premium Prediction Using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 5, May 2024. https://doi.org/10.55041/ijsrem34855

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Publication Date

5/28/2024

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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