With over 20 years of banking experience, Rasha specializes in regulatory/tax programs, financial crime, network management, and data management (including governance, quality, and privacy) across the Middle East, North Africa, and Turkiye. Currently, she leads data management risk for Wealth and Personal Banking, driving sustainable business growth.

In a recent conversation with Global Woman Leader Magazine, Rasha shares insights on the critical role of women leaders in shaping data risk management strategies amid evolving wealth and personal banking landscapes, characterized by global uncertainties and digital transformation. She highlights how their involvement can drive innovation in oversight practices and enhance interdepartmental collaboration in risk management.

In the evolving landscape of wealth and personal banking, with increasing global uncertainties and digital transformation, how do you foresee the role of women leaders shaping data risk management strategies?

In my views, the role of women leaders has significantly increased over the past few years across many landscapes and financial fields, and Data Management is one of them, this is as organizations recognize the value of diversity in decision making and risk management. Women leaders bring diverse perspectives and leadership styles which help promote comprehensive strategies along with building trust with different stakeholders and I personally was lucky to participate in the mentoring program by EDM Council Women Data Professionals and was so proud to meet so many women leaders who hold crucial roles in the data risk management landscape across various organizations across the world. As more women are taking on leadership roles in data governance and risk management, they will continue to shape data risk strategies embracing new challenges for a more resilient and adaptive data risk strategies that can both address and mitigate the complexity and evolving requirements of today’s data driven world.

With the ongoing evolution of technological tools such as AI and machine learning in finance, in what ways might the involvement of women leaders influence the trajectory of innovative practices in data risk oversight?

AI Technologies can always be developed and deployed in ways that not only drive innovation but also protect against potential data risks. Reflecting on the continuous evolution of AI and ML, data risk oversight -like many other risk governance frameworks –will have both opportunities and challenges. The involvement of women leaders can develop a more inclusive and effective approach shaping unbiased outcomes in the context of AL and ML such as ensuring that models are built with diverse datasets that reflect the broader population. Another approach is promoting responsible data use ensuring transparency in AI decision making and addressing possible biases in algorithms.

Based on your experience with global and regional programs, how do industry leaders in the Middle East and Turkey approach data risk management differently?

Data has become the front and center of strategic transformation journeys enabling organizations’ growth when adequately prioritized, analyzed, monitored, and controlled. Several drivers may be considered - which of course -are subject to local variations, when approaching Data risk management across different regions given also the increasingly stringent data protection regulations in some regions. For example, there is heavy focus on compliance with local regulations and requirements, establishing data protection frameworks with proactive risk identification, promoting digital transformation to enhance data protection and streamline processes, and of course investing in security technologies with regular risk assessments with the aim of strengthening cyber security. The strategies to address these should be tailored to tackle the unique challenges and to identify potential opportunities in each region so that the data risk management strategy and approach are both robust and adaptive.

With increasing regulatory scrutiny on data privacy and protection, how can leaders in wealth management balance the need for robust data governance while embracing more agile and innovative approaches?

There is a strong drive towards digital transformation across industries with substantial investments in technologies to ensure customers’ data is secured and protected in alignment also to the increasing regulatory scrutiny. For example, innovative solutions are being adopted with the aim of minimizing privacy violations and are being integrated into the solutions’ systems and technologies to ensure data governance is also built into the core of these solutions. Another example is the adoption of AI and ML to streamline data governance and monitor processes, data access, and data classifications with the aim of reducing manual intervention and ensure data monitoring for compliance. Having said that, it is crucial to also empower our people with the adequate data literacy programs promoting a data led culture with appropriate and targeted data literacy programs, along with the regular reviews of data policies and governance frameworks -aligning both governance and innovation goals.

Data risk management requires collaboration across multiple departments. How can industry leaders foster stronger cooperation between IT, compliance, and business development to enhance the overall risk management framework?

Data risk management is everyone’s responsibility within an organization, the cross functional collaboration ensures that data risks are managed effectively and towards the same goal ultimately enhancing the organization’s ability to manage risks effectively. That’s why it’s important to establish the right and effective Data framework with clear roles and responsibilities so the teams understand how the risk may impact their area and the expectations from their teams. Additionally, the data strategy must be clear and aligned across different areas so everyone across has a common understanding of the goal and the framework within which they can collaborate to achieve this goal. For example, leaders should communicate how technology supports business strategy and objectives, and how business decision influence technology risks. It is also crucial to create a unified language to help bridge any communication gaps and encourage teams to identify and report risks proactively with continuous upskilling of their knowledge.