1- INTRODUCTION
The rapid digitization of the banking industry necessitates robust innovation strategies to maintain competitiveness and address evolving customer needs. The sector faces challenges such as integrating emerging technologies, navigating regulatory frameworks, and fostering organizational adaptability. This study aims to develop a paradigm model for strategic innovation in the context of digital transformation within the banking sector. By identifying key drivers and barriers, the research contributes to the theoretical and practical understanding of innovation management in a highly dynamic industry. The study also explores how banks can strategically position themselves to capitalize on digital opportunities while mitigating associated risks.
 
2- THEORETICAL FRAMEWORK
Grounded in the principles of Grounded Theory, the current research adopts a systematic and exploratory approach to construct a theoretical model. The framework synthesizes insights from multiple disciplines, including strategic management, organizational innovation, and digital transformation studies. Key theories influencing this research include:

Innovation Diffusion Theory: Addressing how technological innovations are adopted and spread within organizations.
Dynamic Capabilities Framework: Explaining how firms adapt to rapidly changing environments by reconfiguring their resources and capabilities.
Digital Transformation Theory: Highlighting the role of technology in reshaping business processes and customer interactions.
These theoretical underpinnings provided a basis for identifying and analyzing the core, causal, and contextual factors that influence innovation strategies in the banking sector.

 
3- METHODOLOGY
The study employs a qualitative research design utilizing grounded theory to develop a paradigm model. Data were collected through in-depth, semi-structured interviews with 14 experts from the banking industry, academia, and digital transformation consultancies. Participants were selected using snowball sampling, ensuring diversity in expertise and perspective. The interview topics were innovation management, regulatory compliance, and customer-centric digital strategies. Data analysis followed a rigorous three-phase coding process:

Open Coding: Identifying initial themes and categorizing raw data into relevant concepts.
Axial Coding: Establishing relationships between categories to form coherent constructs.
Selective Coding: Integrating core constructs into a unified paradigm model.

Maxqda software was employed to enhance the reliability and validity of the coding process. Data saturation was achieved after 12 interviews, ensuring comprehensively covering the subject.
 
4- RESULTS & DISCUSSION
The study’s findings reveal a multifaceted model of innovation strategy, encompassing the following dimensions:

The core category named innovation Strategy, positioned at the model center, reflects the necessity of a well-defined strategy to guide digital transformation efforts.
Causal conditions, as key drivers for innovation, represent issues of technological advancements, increasing customer expectations, and intensified competition.
Contextual conditions, significantly influencing innovation outcomes, include organizational culture, managerial support, and industry-specific regulatory environments.
Intervening Conditions refer to barriers such as insufficient infrastructure, resistance to change, and talent gaps that hinder the effective implementation of innovation strategies.
Action strategies are practical approaches critical to achieving innovation objectives, including leveraging AI-driven decision-making tools, fostering cross-functional collaboration, and investing in employee training.
Outcomes, the primary benefits of implementing the proposed strategies, include enhanced customer satisfaction, operational efficiency, and competitive advantage.

The results demonstrate the interplay between internal organizational factors and external environmental pressures, providing a holistic perspective on innovation management in banking.
 
5- CONCLUSIONS & SUGGESTIONS
This study contributes to the literature by proposing a paradigm model tailored to the unique dynamics of the banking industry. It highlights actionable strategies for banks to align their digital transformation initiatives with long-term strategic goals. The key takeaways include:

Developing innovation hubs within organizations to drive strategic initiatives and foster a culture of creativity.
Collaborating with technology providers and fintech firms to integrate cutting-edge solutions.
Advocating for regulatory reforms that facilitate innovation while ensuring security and compliance.
Prioritizing customer-centric approaches by designing personalized and efficient digital experiences.

Policy Implications: Regulators should consider creating a supportive framework that balances innovation with risk mitigation.
Practical Implications: Banking institutions can use the model as a roadmap to navigate digital transformation while addressing industry-specific challenges. Future research could extend this paradigm model to other sectors, investigate its applicability in diverse geographical contexts, or analyze its long-term impact on organizational performance and customer trust.