Margarita Mukhmadeeva, Product at CoinsFlow — Key Strategies for 10x+ Growth, AI’s Role in FinTech, Challenges for Women in Tech, and Future Trends in AI-Driven Payment Platforms

In today’s interview, we sit down with Margarita Mukhmadeeva, a seasoned product leader and current head of product at CoinsFlow, a rapidly growing Web3 start-up. Margarita brings over a decade of experience in FinTech, specializing in high-performance payment platforms and B2B solutions. As a mentor at Women in Tech, she also champions gender diversity in the industry. Join us as Margarita delves into the role of AI and automation in shaping the future of FinTech, the challenges women face in tech, and how AI is revolutionizing product management practices.

Margarita, you’ve led a Web3 innovative start-up to impressive 10x+ growth. Can you share some key strategies or decisions that contributed to this rapid expansion?

There is rarely a single answer to this question—no silver bullet. Instead, our success is the result of a combination of several key factors.

First and foremost, I believe our obsession with customer needs has always been our core value and the cornerstone of our success. We focused on deeply understanding our clients and identifying pain points and opportunities by working closely with customers who were already well-informed about Web3 but were seeking better-tailored solutions to address their existing challenges.

Another important business decision was our commitment to addressing one of the industry’s biggest issues: credibility. From day one, we invested heavily in legal and compliance, secured the necessary licences, and partnered exclusively with the most reputable Web3 projects. These efforts were crucial in establishing trust and credibility—we aimed to create a Web3 finance project with the reputation and trustworthiness of a traditional financial institution.

Lastly, I must emphasise the importance of our incredible team. Hiring the right people can be challenging, but it’s an investment that always pays off. With the help of my extensive experience in building agile processes, we implemented development practices that allowed for quick iterations based on user feedback. Together, these factors were instrumental in driving our success.

With your extensive experience in FinTech, how do you see the role of AI and automation evolving in payment platforms over the next five years?

One of the key lessons you gain from working in fintech is understanding the inevitability of change—particularly the extreme speed of these changes in this industry. It’s difficult to predict exactly what’s next, and there may be more surprises around the corner, but there are several directions in which AI is already transforming the landscape.

• Our payment platforms will continue to become safer with AI-based fraud prevention. AI algorithms will keep improving the detection and prevention of fraudulent activities in real-time.
• Customer support will continue to become cheaper, faster, and better. By streamlining and automating back-office operations, AI will reduce costs and human error. AI-powered chatbots and virtual assistants will provide 24/7 customer support, resolving queries quickly, with even more advancements to come.
• Our payment products will be even more tailored to each customer. Personalisation will continue to grow, with AI-driven analytics providing personalised recommendations and tailored financial products. Greater integration of various financial products, combined with extensive knowledge about users, will enable us to create next-level solutions for everyone.
• Another important business use of AI within payment platforms is improving stability and acceptance rates. The use of AI for optimising payment routing and minimising transaction costs and delays will continue to enhance the overall quality of our payments.

As a mentor at Women in Tech, what challenges do you believe women face in the FinTech industry, and how can organizations better support gender diversity?

Unfortunately, the challenges women face in the fintech industry are far from unique—gender bias and stereotypes, lack of representation, unequal opportunities, and the additional difficulty of balancing demanding careers with personal responsibilities. As is the case across much of the tech sector, women’s representation is relatively strong at mid-level positions but significantly lower in top roles. Despite the progress made towards fairness and diversity, we are still far from a point where we can afford to slow down our efforts. I believe that every company should actively shape its culture and address challenges at every stage of the employee journey.

Our efforts should begin with implementing bias-free recruitment processes to ensure diverse candidate pools. Once a person is part of the company, internal support and mentoring are crucial. Establishing mentorship and sponsorship initiatives to support women’s career growth is vital. Additionally, I want to emphasise the importance of highlighting successful women leaders and creating visibility for female role models in the industry. From my personal experience, the lack of role models often pushed me to search further afield, which could have slowed my growth.

It’s also important to recognise that fostering a culture of inclusivity, respect, and support through regular diversity and inclusion training is often underestimated. For those with families and children, offering flexible working hours, remote work options, and parental leave to support work-life balance can be particularly beneficial.

Finally, it’s essential to acknowledge that it’s not only women who suffer from difficulties and injustices—all types of minorities do. I believe that companies that consistently focus on changing their culture benefit greatly from the diversity they foster.

Can you discuss a specific instance where AI integration significantly transformed a product management workflow you were involved in?

We are now living in incredibly exciting times, with AI tools thriving, yet I believe this is just the beginning! Personally, I use AI, LLMs, and ML tools every day, both at work and in my personal life. The key to successfully integrating AI, in my view, lies in understanding that AI typically doesn’t automate an entire job or function—it automates specific tasks.

My favourite use cases are those that significantly enhance everyday efficiency. For example, all of my customer interviews are transcribed and summarised using AI tools. Additionally, AI assists me in preparing for interviews, identifying recurring topics, and even formulating better hypotheses to test.

Another scenario where AI plays an instrumental role for me is brainstorming. If you’ve ever feared the blank page, this may work for you too. I often include a request in my prompts to generate several options, which helps me quickly determine the direction I want to take.

In our global and multicultural world, AI tools are also incredibly useful for working in international teams, assisting with translations and even adding cultural references to communication when needed.

Of course, we understand that these tools require additional checks and can make mistakes, but they remain unbelievably helpful—almost like pure magic.

In your view, what are some of the most exciting AI-driven tools currently available for product managers, and how are they reshaping traditional practices?

I believe it’s fair to say that we’re now at a stage where AI is being integrated into most of our everyday tools—Jira, Notion, Miro—sometimes so seamlessly that we may not even notice it.

From my personal experience, the most exciting tools are those that handle some of the less enjoyable aspects of a product manager’s job, such as routine operations (transcriptions, follow-ups, hypothesis editing, and user story refinement). However, I think this preference is partly due to my interests.

Another aspect that excites me is everything related to user analytics. As a B2B business in the early stages of growth, we are less dependent on large-scale analytics data. Nevertheless, I find it fascinating to see where this field is heading with tools like Mixpanel and Amplitude, as well as user research and feedback analysis tools like UserLeap and Qualtrics.

What advice would you give to aspiring product managers who want to specialize in the FinTech and AI space?

I’ve encountered the notion that getting into AI or FinTech is too complicated or that it’s too late to start, but this is simply untrue. I believe that anyone can gain an understanding of a field—the key is to just begin. Another valuable piece of advice is that it’s important not just to learn but to start practising as soon as possible. Given how rapidly the industry is changing, staying up-to-date with the latest news and developments is crucial, so a great first step could be following relevant news channels and media.

Additionally, it’s not always obvious, but finding a mentor or even just a friend to talk to can be incredibly helpful. There are plenty of platforms where you can find support, often for free or at a very low cost.

For potential product managers in fintech, I would also add that if you’re transitioning from other industries, you might not be as familiar with regulation and compliance. However, in fintech, these considerations are essential and must be kept in mind constantly.