In the fast-paced world of online trading & fintech, staying ahead means embracing innovation and it is safe to say, Artificial Intelligence (AI) is part of this new wave of innovation whether we like it or not. AI tools are no longer futuristic concepts; they are actively redefining how brokerages operate, innovate, and scale.
The latest episode of Brokeree Add-On Interview Series offers a closer look into that. Host Paulina Parowicz (Brokeree Solutions) together with Katerina Burtsava (ThinkHuge) dive deep into the topic of AI agents exploring how they are leading the transformation within online trading and beyond.
We have summarised the key insights from this conversation, including:
- What AI agents are in the first place and why they matter for brokerages;
- Practical applications of AI agents, e.g. customisation & training.
- Essential considerations for AI agent implementation, such as security & compliance.
If you’re curious about AI’s impact on brokerages, read on for the highlights and actionable takeaways!
Katerina Burtsava & Paulina Parowicz discussing AI Agents for Brokers | ADD-ON EP.02
What exactly is an AI agent?
Katerina Burtsava, whose vast experience lies in dealing with fintech and trading projects, including AI solutions, explains that AI agents are advanced software systems powered by artificial intelligence, designed to autonomously perform tasks, analyze large sets of data, and make decisions without direct human involvement. Unlike static tools, these agents adapt and respond in real time, making them invaluable for modern online trading operations.
Who should consider using AI agents?
AI agents are suitable for any fintech company, regardless of size, jurisdiction, or specialization. Whether it’s a small brokerage or a large financial institution, any organization aiming to enhance customer service, streamline internal processes, or provide tailored communication can benefit from adopting AI agents.
Why are AI agents important for brokers, and what are the main business applications?
For brokers, AI agents can offer three main advantages:
- Provide instant and efficient communication with traders, supporting better client retention;
- Revolutionise and upgrade trading education by delivering personalized, on-demand learning experiences;
- Boost operational efficiency and cost savings by automating processes such as customer support, marketing, and risk management.
AI Agents can be trained to handle both client-facing tasks and internal operations, suggesting that they can be flexible and valuable across departments.
How can a broker know if adopting AI agents is worth the investment?
Katerina asserts that in today’s fast-evolving industry, the risk lies in delaying AI adoption. The cost savings, efficiency gains, and enhanced competitive edge far outweigh the initial investment. The real question, she says, is not “if” but “when” and “how soon” to implement AI solutions.
What must brokers consider before implementing AI agents?
Brokers should clearly define their objectives for AI integration (for example, whether it’s to optimize customer support or enhance education), identify which user groups will benefit, and establish a budget that accounts for ongoing maintenance and potential upgrades. Assigning a dedicated project lead is essential to ensure successful deployment and continuous improvement.
How can brokers ensure data security with AI agents?
Security is paramount for brokers. One suggestion is to deploy AI models on private, secured servers (VPS or dedicated machines behind firewalls). Sensitive data should be safeguarded, especially if using third-party AI services, and robust authentication processes must be implemented to protect both clients and the business.
Can AI agents help detect scams and fraud?
AI agents can indeed strengthen fraud detection by validating and filtering user inputs before they reach core systems. They authenticate user sessions, similar to human agents, and escalate suspicious or uncertain cases to human support teams for further action.
What regulatory considerations apply?
Brokers must comply with data protection and financial regulations relevant to their jurisdiction (such as GDPR and MiFID in the EU). It is crucial to involve legal departments from day one, from the moment the decision has been made to implement an AI Agent solution in order to ensure compliance as large volumes of sensitive client data are used and processed.
How do AI agents differ from chatbots and trading bots?
Unlike chatbots, which follow predefined rules and provide static answers without memory of past interactions, AI agents are context-aware, adaptive, and can learn over time. Trading bots, meanwhile, follow fixed rule-based strategies and do not adapt or improve through experience, unlike AI agents that continually evolve.
What are the customization possibilities?
Customization and training of an AI agent go hand-in-hand. AI agents can be trained and customized using a brokerage’s internal data—such as historical trade logs, policy documents, and CRM systems. They can integrate with live market feeds and other company systems to offer specialized, up-to-date support and even tailor their responses to adhere to brand voice or regulatory requirements. Additionally, testing is highly suggested before going live to ensure that the AI agents are performing correctly and according to the needs and expectations of the company.
How long does it take to implement and train an AI agent?
There is no one frame that fits all. Implementation timelines vary based on data volume and project complexity. Building a customized, effective AI agent can take anywhere from 1–2 months for straightforward solutions to six months or more for comprehensive, multi-department integrations. Moreover, continuous monitoring, training, and updating are essential for optimal performance.
Curious to learn more?
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