Partner & Financial Services Lead at IBM Consulting – Nesrine Besbes

Caroline: So you currently work at IBM Consulting as a lead partner for financial services. Can you tell us a bit more about your job, and can you describe a typical day?

Nesrine: The one thing I love about my job is that there is no typical day. It’s always changing. There is always something new. And that’s what keeps me going and excited to wake up for this job over the past 15 years. That being said, we can talk about the key ingredients or typical components, which are really about understanding what the client’s issue is, understanding what the client is trying to achieve, and setting that within the bigger context of the client’s company, the market, and the ecosystem. From there, we start to assemble the most suitable solution.

You could think of the solution as a puzzle. We bring the best of IBM Consulting from our various delivery teams across the globe, and also the best from our ecosystem partners. We then fine-tune and sharpen this puzzle in co-creation mode with the client. So, these are the typical ingredients: understanding what the client wants or is trying to achieve and then creating something new and effective to address that specific problem or drive that particular value. The sky is the limit in terms of where to get those pieces for the solution puzzle, from IBM and beyond.

Caroline: It seems like it requires a lot of creativity.

Nesrine: Yes, absolutely. In my business, it certainly does. I’m not creative in the sense of being a musician or an artist, but I am a consulting musician, if you will. It’s like a symphony we are building together for that client. I like to think of my work as a piece of art that addresses an issue for my client, and I aim to leave behind something truly useful that makes the client really happy.

Caroline: Can you share an example where creativity has made you particularly proud?

Nesrine: Every project has made me proud in one way or another, but nostalgia takes me back to the very first project I worked on as a consultant. It was in Paris, 15 years ago. We were working for a private bank to develop, design, and build an in-house tool for risk monitoring in the private banking space. We collaborated with the bank’s business teams, and IT teams in Paris, Asia, and India.

The fact that it was such an intense project, starting from a blank page and resulting in a tool that still operates and functions to this day, 15 years later, is something I’m very proud of. We formed friendships that have endured, and as a personal anecdote, that’s where I met my husband.

This project holds a special place in my heart. Creativity was key, from conceptualizing how to monitor risk to designing the tool’s interface. We worked on PowerPoint slides to illustrate what the tool would look like, tested it, and co-created it with end users from the bank’s various offices. It was a lot of fun and a truly rewarding experience.

Caroline: Thanks for sharing the anecdote. As a consultant, your job is to help companies manage their businesses. And today, generative AI is revolutionizing how business is designed. So how do you see the impact of generative AI in your work on a day-to-day basis?

Nesrine: I’m already seeing a significant impact in my daily tasks, largely thanks to our own IBM generative AI tool, based on Watson X, from IBM’s technology branch. I have a generative AI assistant that helps me read client documents and publications. It also aids in development by summarizing annual reports, identifying key regulatory updates, and contextualizing those updates for clients. This assistant can draft proposal skeletons, automate market research, and create initial content, which saves me and my team a tremendous amount of time, allowing us to focus on higher-value tasks.

This impact is evident in how I prepare my work for clients. But it’s also about the solutions we create for our clients. Even when the initial request from a client isn’t specifically about generative AI, it often becomes part of the project as we look for optimization opportunities and innovative ways to bring the next best solution to the client. Generative AI gets infused into our projects, enhancing creativity and efficiency in delivering solutions.

Caroline: So how does it contribute to increasing the success of your clients?

Nesrine: Generative AI and AI are revolutionizing the way banks and insurers operate and serve their customers. To make it tangible, let me share a few examples.

First, consider an internal application: AI can address the shortage of skills in legacy IT languages. For instance, generative AI can understand, summarize, and reverse engineer legacy code, potentially rewriting it in modern languages. This improves maintenance and documentation of applications, enhancing the day-to-day life of IT and development teams.

Now, looking at client-facing examples, AI’s ability to consume and digest data is invaluable. In asset management, for example, generative AI can read and analyze fund prospectuses to ensure compliance with regulatory and investment rules. This simplifies the asset manager’s job, enabling them to make better investment decisions without getting bogged down in the groundwork.

For more client-interactive scenarios, in banking and insurance, customers are increasingly interacting with chatbots and voice bots. Interestingly, some insurers have found that customers are more comfortable reporting injuries or claims to AI bots than to humans, possibly because they feel less judged. This leads to smoother claim processes and frees up employees to focus on more complex cases, tailoring responses based on the client’s specific situation and policy.

Ultimately, this increases customer satisfaction, reduces operating costs, and minimizes operational errors in capturing client information. This improved efficiency and accuracy significantly contribute to the success of our clients.

Caroline: What kind of complex cases are employees going to face?

Nesrine: Employees will increasingly focus on complex policies and credit cases, particularly in banking. By doing so, they can enhance their value proposition to customers. Just as my generative AI assistant at IBM Consulting handles much of the groundwork for me, freeing up my time to build tailored solutions for clients, banking and insurance employees will also have more time to understand and meet their clients’ needs.

Generative AI helps them better understand client behaviors and the vast amounts of data available, allowing for a more precise articulation of what customers expect. As a result, employees can develop and package better products tailored to client requirements.

In conclusion, AI, and particularly generative AI, is significantly transforming customer service in the banking and insurance sectors. It helps these organizations improve customer experiences, reduce expenses, and increase revenues. By deploying generative AI technologies, businesses can remain competitive and adapt to the ever-changing market, introducing new products and new ways to serve their clients effectively.

Caroline: So you’ve talked a lot about customer and partner trust. And it’s a crucial topic in the banking sector. And it is something that you are particularly passionate about. And that’s why you’re specifically interested in AI governance. Can you tell us what AI governance is?

Nesrine: Sure. We need to trust AI and generative AI and the outcomes they provide to clients and organizations as a whole. To achieve this, we must have robust AI governance.

AI governance can be defined as the arsenal of processes, policies, and procedures put in place to manage and oversee the functioning and use of artificial intelligence within an organization. Think of AI as a new employee that needs to follow a set of rules regarding data management, data access, security, ethics, and compliance—similar to the rules that apply to all other employees and systems within a bank or insurer.

Applying these rules to AI ensures that AI systems operate in alignment with organizational goals, values, and principles. It also ensures that AI operates transparently, accountably, and under appropriate controls. This is what AI governance, or responsible AI, is about: ensuring we can trust the outcomes of AI solutions and tools.

Caroline: And how do you approach it at IBM Consulting?

Nesrine: At IBM Consulting, we believe that AI must be governed to earn trust. This is a principle we adhere to strongly. However, AI governance cannot be solely the responsibility of individual companies. Both corporations and governments have crucial roles to play in establishing effective AI governance frameworks.

IBM has actively collaborated with governments globally to advocate for smart AI regulations that prioritize mitigating risks associated with real-world AI applications, rather than regulating the underlying algorithms themselves. This approach is akin to regulating the use of wheels in transportation (cars, trains, planes) rather than the wheels themselves. It focuses on ensuring safe and ethical AI deployment across various sectors.

Recently, IBM launched the AI Alliance, a diverse community comprising AI researchers, creators, developers, and enthusiasts. This initiative aims to foster open, inclusive, and responsible AI innovation. Additionally, IBM has established a Center of Excellence for Generative AI to support organizations of all sizes worldwide in adopting effective and ethical AI solutions for their business needs. These efforts underscore our commitment to advancing AI responsibly and inclusively.

Caroline: So what are the challenges of AI governance in your profession in the banking world?

Nesrine: It’s difficult to provide an exhaustive list of challenges in AI governance, as they vary significantly based on companies, banks, markets, countries, and other factors. However, one prominent challenge that immediately comes to mind is data and its governance.

AI technologies heavily rely on data. If the data is incorrect or poorly governed, the outcomes produced by AI using that data cannot be trusted. Allow me to step back from AI for a moment and highlight two critical data points that I recently encountered:

Firstly, concerning data governance within banks, two-thirds of banks lack a comprehensive data governance framework. Moreover, 70% of these banks cite regulatory requirements as the primary driver for addressing data governance issues. This underscores the regulatory complexity surrounding data governance.

Secondly, 80% of major IT projects fail to deliver on time and within budget due to data integration and data quality challenges. This statistic emphasizes the critical role of data governance in the success of IT initiatives, including those involving AI and generative AI.

Considering these points, implementing generative AI in banks or insurers, or any company for that matter, becomes significantly challenging when starting with inadequately governed data. This highlights why I always emphasize to my clients the importance of beginning AI and generative AI initiatives with thorough data governance and quality assessment.

There’s a saying, “garbage in, garbage out.” With AI, it’s amplified—garbage in, amplified garbage out. Therefore, effectively managing and governing data is paramount in ensuring trustworthy AI outcomes.

In conclusion, I believe data governance represents one of the primary challenges in AI governance within the banking sector.

Caroline: Moving away from technology and AI and going back to the human aspects of an organization. What is the proportion of women at IBM Consulting in the same level of expertise as you are?

Nesrine: A lot of progress has been made in this area, obviously, but there is still much to be done. Several years ago, when I was promoted to partner at IBM, a study showed me that there were more CEOs named John in American companies than there were women CEOs. So clearly, there is still significant work to do. It strikes me that women are often treated as a minority despite representing 50% of the global population. This is why I believe we need to emphasize not just gender diversity, but true diversity across all aspects—race, religion, social backgrounds, culture, sexual orientation, and more. We all have work to do at every level to challenge biases and recognize the value and enrichment that come from a diverse workplace.

Caroline: How do you assert yourself in this predominantly male environment that you’re talking about?

Nesrine: I think I simply remain true and genuine to my values and the way I operate. I focus on doing the right thing no matter what, and I lead with empathy.

Caroline: Speaking of being true to yourself, do you have any advice that you would give to a young man or woman starting their career?

Nesrine: This ties back to the first question as well. Starting a career can be challenging. One of the lessons I’ve learned is the importance of continuous learning and staying open-minded. It’s not just about acquiring knowledge but also about questioning what you learn because things are constantly evolving. Embrace change and don’t be afraid to adapt and grow.

Caroline: Are there women or men role models who have guided you?

Nesrine: Of course. At the end of the day, these are the people who lead with empathy and integrity. They always do the right thing for their clients, their teams, and their community, no matter what.

Caroline: To conclude this podcast, I’d like to know what does ambition mean to you?

Nesrine: My view of the word “ambition” and my interpretation of it have evolved over the course of my career. In the beginning, it may have meant advancing from one career level to the next as quickly as possible. Then it shifted to achieving what’s best for the project, the client, the teams, and the people involved. But today, it has evolved again. Now that I look at my kids and my family, ambition to me means leaving a legacy that truly matters. It’s about making a meaningful impact on my clients, my team, my community, and my family. This can only happen by always doing the right thing in all aspects of my life and work. So, that’s what ambition means to me today—leaving behind something that is useful, beneficial, and meaningful to others.

Caroline: Thank you, Nesrine, for being with us.

Nesrine: Thanks a lot, Caroline.