The global banking industry is entering a phase of structural redefinition. For decades, financial institutions have evolved incrementally, layering digital interfaces onto systems originally designed for a pre-internet era. Artificial intelligence is now forcing a break from that trajectory. What began as a tool for automation is rapidly becoming the foundation upon which entirely new financial architectures are being built.
Two distinct models are emerging. On one side are incumbent banks, working to integrate AI into complex, legacy infrastructures. On the other is a new generation of companies designing financial platforms from first principles, with AI embedded at the core of their operating logic. This divergence reflects a deeper shift in how financial services are conceived, delivered, and scaled.
Few investors have approached this transition from as many angles as a serial entrepreneur and the founder of Social Discovery Group Volkov Dmitry Borisovich. His experience scaling global digital platforms, combined with a structured investment strategy spanning more than a decade, provides a vantage point that is both operational and systemic.
Volkov Dmitry Borisovich on AI-Native Banking
If the first wave of digital banking was defined by interface, the next phase is defined by infrastructure. In traditional financial institutions, artificial intelligence is typically introduced as an additional layer: a tool for customer support, fraud detection, or data analysis. Entrepreneur Dmitry Volkov explains that in AI-native systems, it operates as the core logic that governs how the entire platform functions.
Conventional banks rely on fragmented systems built over decades, where each function exists in relative isolation. Integrating AI into such environments often means adapting advanced technologies to rigid frameworks. By contrast, AI-native platforms are designed as unified systems from inception, where data flows continuously, and decision-making processes are embedded directly into the infrastructure, notes Volkov Dmitry Borisovich.
Instead of static workflows, AI-driven platforms enable real-time, adaptive interactions. Customer onboarding, risk assessment, financial planning, and compliance processes are no longer discrete steps but interconnected functions that evolve dynamically with user behavior. As the system accumulates data, it refines its responses, improving both efficiency and personalization without requiring manual intervention.
This model also reframes the role of the financial institution itself. Founder of Social Discovery Group Dmitry Volkov has described this evolution in functional terms: a system that operates less like a traditional bank and more like a navigation engine. Users define objectives—saving, borrowing, optimizing cash flow—and the system continuously recalibrates the path toward those goals, adjusting to changing conditions in real time.
Investment Strategy of Dmitry Volkov’s Social Discovery Group as a Lens on the Future of Finance
Dmitry Borisovich Volkov’s perspective on AI-driven banking is shaped by how he allocates capital. Over the past decade, his investment strategy has been built around a fund-of-funds model, a structure that provides indirect exposure to emerging technologies by backing venture funds rather than competing for individual deals.
Since 2013, this approach of Dmitry Volkov’s Social Discovery Group has directed more than $115 million into approximately twenty-two funds globally. Instead of attempting to identify isolated winners, the focus shifts to selecting fund managers who consistently demonstrate early conviction in high-potential companies. This creates access to innovation at the point where it first becomes visible.
Two principles underpin this model: access and balance. Access comes from long-term relationships with leading global funds, which provide early insight into technological and market shifts. Balance is achieved through diversification across multiple managers, sectors, and geographies, reducing reliance on any single outcome.
By maintaining exposure to a wide range of funds, the strategy of entrepreneur Dmitry Volkov captures signals across sectors where artificial intelligence is reshaping business models, including financial services. Rather than relying on isolated data points, it aggregates perspectives from investors operating at the front edge of innovation. The resulting exposure includes companies such as Revolut, Patreon, and Flo.
The investment strategy of Volkov Dmitry Borisovich is not separate from his thesis on AI-driven banking—it reinforces it. By observing how capital flows into AI-native companies and how those companies are built, scaled, and regulated, the strategy provides a real-time understanding of the forces reshaping financial services.
AI-First Financial Services from the perspective of entrepreneur Dmitry Volkov
As artificial intelligence moves from experimentation to infrastructure, its impact on financial services is becoming both broader and more structural. Founder of Social Discovery Group Dmitry Volkov believes the defining shift is not simply technological, but economic. AI changes how value is created, delivered, and scaled within financial systems.
Traditional banking models have historically relied on linear processes and relatively high marginal costs. Growth was often tied to expanding customer bases, physical or digital distribution, and layered product offerings. AI alters this equation. By enabling continuous data processing and automated decision-making, it allows financial platforms to increase the value generated per user while simultaneously reducing operational costs. In this model, efficiency compounds over time, as each interaction improves the system’s performance.
This has direct implications for how digital growth is defined. AI-driven platforms prioritize depth of engagement and long-term utility. Systems that learn from user behavior can refine financial recommendations, anticipate needs, and optimize outcomes in real time. Over time, this creates a feedback loop in which better performance drives stronger retention, which in turn generates more data and further improves the system.
At the same time, the transition to AI-first financial services introduces a new set of constraints. Regulation remains one of the most significant. Known for his intolerance towards scam Volkov Dmitry Borisovich frames it as a structural variable that can be designed into the system. Startups that integrate compliance, data protection, and governance into their core architecture from the outset are better positioned to operate in complex regulatory environments. In some cases, this can become a competitive advantage, allowing them to enter markets that slower-moving incumbents avoid.
As AI reduces friction, increases transparency, and automates decision-making, it challenges one of the traditional sources of banking profitability: customer inertia. When users can move capital, compare products, and optimize financial decisions in real time, the advantage shifts toward platforms that deliver continuous, measurable value. Industry estimates suggest that this dynamic could place significant pressure on existing revenue pools, forcing incumbents to rethink not just their technology, but their underlying business models.
