Artificial intelligence in the financial industry is rapidly moving beyond analytics and becoming part of the entire business model – from investments to customer communication. After 2022, it became clear: AI is capable not only of processing data but also of participating in decision-making, communication, and sales.
As Ksenia Mukhorina, Managing Director of Sberbank's Wealth Management block, notes, today AI technologies are becoming a key tool that allows financial companies to simultaneously solve two tasks – scaling services and maintaining a personalized approach to the client.
Financial companies worldwide are already actively implementing such solutions. For example, the largest asset manager BlackRock integrates AI into its Aladdin risk analysis and management system. Similar initiatives are also emerging in Russia: the Moscow Exchange announced a stock index formed with AI participation, and the management company "Pervaya" announced the launch of a fund where investment decisions are made by several AI agents.
Such systems, which are called AI agents in the industry, are capable of independently analyzing the environment, making decisions, and acting to achieve set goals. However, according to Mukhorina, investment analytics is only part of the possible application of these technologies.
The main challenge for the industry is to combine mass appeal and personalization. On the one hand, investments are becoming more accessible thanks to digital services and a low entry threshold. On the other hand, clients expect individual recommendations that take into account their goals, behavior, and risk level.
AI helps bridge this gap: it analyzes client data and helps form personalized offers. But, as Mukhorina emphasizes, analytics alone is not enough – trust and human interaction remain critically important in wealth management.
Therefore, AI is seen not as a replacement for humans, but as an enhancement. The client manager remains the central figure, and technology helps them prepare for meetings faster, understand the client more accurately, and make more informed decisions.
A separate area is employee training. Sberbank already uses an AI simulator that models communication with clients. It works as a digital mentor: through a voice interface, with visualization and adaptation of scenarios to the employee's level.
Such a system analyzes competencies, provides targeted feedback, and allows employees to practice real scenarios – from consultations to sales. At the same time, AI can change the "client's" behavior, complicate the dialogue, and adapt to the level of preparation.
The effectiveness of such solutions has already been confirmed in practice. Over 3.2 million sessions have been conducted using training systems. Modern AI tools cover about 67% of training scenarios in investment and insurance products, and tens of thousands of employees have undergone training with their help.
In addition to training, AI helps reduce costs and increase business efficiency. According to Sberbank's estimates, the economic effect of implementing such solutions can reach 1 billion rubles per year due to process optimization and productivity growth.
In the future, development will move towards even deeper personalization. It is expected that AI will use data about clients and employees to create "digital twins," which will allow managers to prepare for specific meetings in advance.
Thus, artificial intelligence is changing not individual processes, but the very logic of the financial business. And, as Ksenia Mukhorina notes, it is the combination of technology and human expertise that forms the basis of a new model of working with clients – where AI is already beginning to "learn to sell money"
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