Adoptive bancassurance models transforming patronization among the insured
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.spl-2.09Keywords:
Adoptive model, Bancassurance, Patronization, Insurance services, Financial inclusion, DigitalizationDimensions Badge
Issue
Section
License
Copyright (c) 2025 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Adoptive bancassurance model is an imperative and flexible developmental model focusing on the concept of a strategic approach that banks adopt in contradiction with other models where control remains rigid. The primary objective pertaining to the study is to determine all reliable characteristics that emerge from the adoption model, which modifies user patronization behaviours. A descriptive study design and a judgemental sampling method are utilized to study the respondents in the Metropolitan area of Chennai City. A Self-designed structured questionnaire was employed to collect data from a sample size of 343, carried out between March-July 2024. Using IBM SPSS and AMOS, the gathered data is analysed using frequency analysis, model fit index, and structural equation modelling. The study asserted that the six adopting bancassurance model indices of Credibility, Personalization, Financial inclusion, Digitalization, User Interface, and Consumer Literacy, had a beneficial impact on insureds' patronage. The adoptive model's user interface's unexplored sense of flexibility goes beyond its basic features. The effects of the insured perspective on customer satisfaction, financial inclusion, and market competitiveness guide the industry toward regulated insurance product simplification and guarantee penetration. Adoptive bancassurance models effectively improve client access to insurance and expedite service delivery while promoting consistency and new product development for client retention and growth. The flexibility of adoptive models provides access to insurance through banking channels, endorsing financial inclusion and literacy, and ensuring socioeconomic stability, especially for those living in underprivileged areas.Abstract
How to Cite
Downloads
Similar Articles
- Sheena Edavalath, Manikandasaran S. Sundaram, MARCR: Method of allocating resources based on cost of the resources in a heterogeneous cloud environment , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Priya Tiwari, Bharat Kasar, Vibhu Tripathi, Decoding Investor’s behavior in tax saving mutual fund: A multi-item scale for evaluating investors’ category , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Subna MP, Kamalraj N, Human Activity Recognition through Skeleton-Based Motion Analysis Using YOLOv8 and Graph Convolutional Networks , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- Vinodini R, Ritha W, The economic order quantity model for sustainable green inventory considers deterioration impact on the real-time replacement and various reorder points with imperfect quality items , The Scientific Temper: Vol. 16 No. 04 (2025): The Scientific Temper
- G Gayathri Devi, R Radha, Smart alerting services: Safeguarding women and children in the digital age , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- A. Sahaya Mercy, Dr. G. Arockia Sahaya Sheela, Speckle-Robust Local Phase and Ternary Texture Encoding (SLaP-TEX) based Feature Extraction for Liver Steatosis Classification in Ultrasound Imaging , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- Ramya Singh, Archana Sharma, Nimit Gupta, Nursing on the edge: An empirical exploration of gig workers in healthcare and the unseen impacts on the nursing profession , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Jyoti Vishwakarma, Sunil Kumar, Mapping Research on ESG Disclosure and Firm Performance: A Systematic Bibliometric Analysis , The Scientific Temper: Vol. 16 No. 09 (2025): The Scientific Temper
- Sivakumar S, Rajasekaran Kondareddy, Kalyani Ayyemperumal, Building SaaS solutions using microsoft azure for achieving safe and secure tax related software , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- Anita M, Shakila S, Stochastic kernelized discriminant extreme learning machine classifier for big data predictive analytics , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
<< < 5 6 7 8 9 10 11 12 13 14 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Anli Suresh, Sandhiya M., Investment model on the causation of inclining attributes towards bank investment options in the investor’s portfolio , The Scientific Temper: Vol. 16 No. Spl-2 (2025): The Scientific Temper

