InsureTech: A Platform that Provides Customized Insurance Policies

Abstract

This paper presents a platform that is built for users who find the gap in conventional insurance platforms and need Customized insurance policies. It is an innovative approach that addresses significant gaps in the current insurance systems. Traditional insurance systems lack centralized policy administration, flexible coverage selections, and quick verification methodologies, resulting in suboptimal consumer experiences. Our platform, “InsureTech,” incorporates various policy providers with customizable plans that cover major and general policies like Car, Bike, and Health insurance through an intuitive interface. Our platform has a management framework too that shows all the plans of all policy types at one interface, making it highly user-centric. The key innovations that set us apart from the competition are (1) Implementation of sophisticated digital Know Your Customer (KYC) protocols (2) Plan suggestions are complemented by integrated AI, which suggests tailored, customizable insurance plans to navigate the user more easily based on the user\'s details. (3) A smooth and simple end-to-end management solution from discovering policy to buying a customized plan to finally making claims. Through user assessment, we demonstrated that milestone in task execution speed (68% reduction), calculated the user satisfaction metrics (84% positive evaluation), and policy customization adaptability compared to traditional insurance platforms. All these points from our investigation contribute to developing InsureTech. By illustrating how a user-centric approach, a customizable policy interface, and the management of multiple policies in one place can revolutionize consumer experience while sustaining regulatory terms and data protection.

Introduction

The traditional insurance industry struggles with outdated, rigid systems that lack personalization and create complexity for users. Key issues include:

• Fragmented policy administration across multiple platforms.

• Inflexible insurance packages.

• Time-consuming and document-heavy verification processes (KYC/CDD).

• Lack of short-term or event-based coverage options.

Research Goals:
This study proposes a centralized, digital insurance platform to address these challenges by:

• Unifying multiple insurance types under one platform.

• Simplifying KYC with digital tools.

• Offering customizable insurance plans.

• Evaluating improvements in customer satisfaction and system feasibility.

Significance:
The study contributes to the InsurTech field by:

• Demonstrating digital transformation's potential in insurance.

• Enabling personalized insurance experiences.

• Offering insights into integrating innovation with regulatory compliance.

Related Work:

• InsurTech has focused on niche solutions; full integration remains rare.

• Existing platforms lack cross-provider, comprehensive management.

• Customization efforts emphasize pricing over product tailoring.

• KYC innovations exist in finance but are underutilized in insurance.

• There’s a research gap in unified platforms combining these features.

Methodology:
Using Design Science Research (DSR), the study followed a six-step process to develop a scalable, secure platform using:

• MongoDB, OAuth2, Spring Boot, React, and React Native.

• Agile development with two-week sprints over six months.

Evaluation:
Mixed-methods testing with 48 participants assessed:

• Usability: Task completion, satisfaction (SUS scores).

• Performance: Speed, reliability, and scalability.

• Benchmarking: Compared features and efficiency with existing platforms.

Conclusion

A. Summary of Contributions InsurTech Hub, the sole Integrated Insurance Management System that fills the broad gaps in the insurance industry today, is presented in this report. The system supports tailored insurance policies, Know Your Customer automated procedures, and merges policies from more than one insurer within an economical method. Contrary to conventional insurance systems, results from the tests show enhanced efficiency, performance, and customer satisfaction. Important contributions consist of: ? An integrated architecture of combined insurance management. ? Emerging insurance personalization and customization strategies ? Effective digital verification procedures that are regulation-compliant. ? Empirical data indicate that central control enhances the user experience. Lessons gained from incorporating challenges in the insurance sector. B. Future Research Directions This article responds to some of the most compelling lines of future inquiry: • Next-generation personalization: Summary of emerging artificial intelligence algorithms for personalization from big data sets and behavior patterns. • Cross-border insurance involves consideration of issues with the conduct of insurance under other regulatory regimes. • Ecosystem Integration: Ecosystem integration is used to refer to the language of interaction with other financial services, i.e., in the sense of supporting overall financial management. • Behavioral Insurance Models: Assessing the potential effect of individual insurance on risk behavior and claim patterns. • Platform Economics: A Deep Dive into Business Models for Long-Term Insurance Aggregation Platforms. C. Realistic Next Steps Some possible follow-ups are suggested, and above all, in the instance of the InsurTech Hub: ? The establishment of firms that provide all-round covers. ? Enhancing the depth of the advanced interactive capabilities of the AI chatbot. ? Changing the degree of customization according to consumer feedback. ? Reviewing collaborative alliances for platform-specialized services with insurance providers. ? Developing additional metrics to measure long-term user activity. A key addition to insurance management practice, the flexible and centralized structure provided in this study provides the entry point for innovation in the InsurTech sector.

References

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Copyright

Copyright © 2025 Satadeep Sadhukhan, Samarth , Rahul Soral, Priyanka Maan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.