Purpose

This conceptual paper explores gaps in bank privacy protection practices and advocates for banks to integrate market-oriented (MO) approaches in their corporate digital responsibility (CDR) initiatives to minimize consumer data vulnerability.

Design/methodology/approach

To apply MO in CDR, this study recommends adoption of a behavior change framework comprising of the co-creation, build and engage (CBE) model and proposes the creation of consumer segments based on generational cohort and tailoring strategies through motivation, opportunity and ability (MOA) model to manage vulnerability.

Findings

The study specifies that managing consumer data vulnerability requires a unique strategy different from conventional service delivery. A holistic approach is recommended by integrating corporate digital responsibility as a pivotal element of organizational strategy and by positioning vulnerable customers as a critical stakeholder.

Originality/value

The paper contributes to the research in corporate social responsibility (CSR), privacy and data vulnerability in the banking sector in two prominent ways: first, the study demonstrates the importance of MO as a premise to develop a novel version of CDR called market-oriented digital responsibility (MODR). The study considers MODR as a strategy to reposition vulnerable consumers as a key stakeholder, and, second, the study proposes an innovative set of consumer segments based on data vulnerability and introduces a data vulnerability growth model (DVGM) connecting vulnerability with age.

中文翻译：

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以市场为导向的企业数字责任管理网上银行数据漏洞

目的

本概念文件探讨了银行隐私保护实践中的差距，并倡导银行将市场导向 (MO) 方法整合到其企业数字责任 (CDR) 计划中，以最大限度地减少消费者数据的脆弱性。

设计/方法/方法

为了在 CDR 中应用 MO，本研究建议采用由共同创造、构建和参与 (CBE) 模型组成的行为改变框架，并提出基于代际队列和通过动机、机会和能力量身定制的策略来创建消费者细分市场。 MOA) 模型来管理漏洞。

发现

该研究指出，管理消费者数据漏洞需要一种不同于传统服务交付的独特策略。建议采用整体方法，将企业数字责任整合为组织战略的关键要素，并将弱势客户定位为关键利益相关者。

原创性/价值

该论文以两个突出的方式对银行业的企业社会责任 (CSR)、隐私和数据脆弱性的研究做出了贡献：首先，该研究证明了 MO 作为开发一种称为市场导向的新型 CDR 的前提的重要性数字责任（MODR）。该研究将 MODR 视为一种将弱势消费者重新定位为关键利益相关者的策略，其次，该研究提出了一组基于数据脆弱性的创新消费者细分，并引入了将脆弱性与年龄联系起来的数据脆弱性增长模型 (DVGM)。