The financial services industry is no stranger to challenges. Between the constant demand for innovation, tighter regulations, and the growing need to meet ever-increasing customer expectations, staying ahead has become increasingly difficult. Financial institutions have always sought ways to work faster, smarter, and more efficiently.

This is where agentic AI in finance is stepping in. Unlike traditional AI, which assists with specific tasks, agentic AI is capable of making decisions and learning from data autonomously. For financial services, this means a huge shift in how things are done—improving efficiency, reducing costs, and enhancing service quality.

In this article, we’ll explore the role of agentic AI in transforming the financial sector, how it is being used in practice, and the benefits it brings. Let’s dive into what makes this technology so impactful.

What Sets Agentic AI Apart from Traditional AI in Finance?

In many ways, the financial industry has long relied on technology to automate specific tasks like sorting data, conducting research, or generating reports. However, traditional AI often requires a lot of human oversight and doesn’t “think” for itself. This is where agentic AI changes the game.

Agentic AI creates intelligent systems that can make independent decisions, learn from experience, and adapt over time. In finance, these AI agents can autonomously analyze market trends, manage risks, and even create strategies based on real-time data. Here's a quick overview of what makes agentic AI in finance stand out:

• Autonomy: These systems can perform tasks without needing constant human supervision. They draft reports, review documents, and make decisions on their own.
• Adaptability: Agentic AI continuously improves its performance by learning from past data and outcomes, which means it gets better over time.
• Real-Time Decision Making: These AI agents don’t just analyze data—they make decisions in real time, predicting market shifts, spotting fraud, and adjusting strategies instantly.

Unlike traditional systems, which are confined to predefined instructions, agentic AI is designed to understand the complexities of financial data and act on it with minimal human intervention. This makes it a valuable asset in managing the fast-paced, data-heavy world of finance.

Suggested Watch: To gain deeper insights into AI's evolution and its impact on automation and application development, you might find Dr. Ng’s perspective informative: Andrew Ng Explores The Rise Of AI Agents And Agentic Reasoning | BUILD 2024 Keynote

Now that we understand the differences between traditional AI and agentic AI let’s look at how agentic AI is reshaping the way financial institutions handle risk management and fraud detection.

In finance, managing risk is crucial. With agentic AI, financial institutions are not just responding to risk; they are predicting and preventing it. Let’s explore the key applications in this space.

AI-Powered Risk Management and Fraud Detection

Managing risk is at the heart of every financial institution. Traditionally, risk management was a reactive task—waiting for problems to arise before addressing them. With Agentic AI, institutions can now predict, prevent, and address risks before they escalate.

Here's how Agentic AI is transforming risk management and fraud detection:

• Fraud Prevention: Agentic AI can monitor transactions in real time, identifying irregular patterns that may indicate fraudulent activity. These AI-driven systems can respond instantly, blocking suspicious transactions or flagging them for review. For instance, Mastercard uses AI-powered systems to detect fraud across billions of transactions daily, reducing fraud losses significantly.
• Predictive Risk Models: Financial institutions use Agentic AI to build predictive models that forecast potential market shifts, credit defaults, or liquidity crises. These AI systems can analyze vast datasets—ranging from historical data to social media trends—and predict financial risks with unprecedented accuracy. Citigroup, for example, uses Agentic AI for its credit risk assessment, which has enhanced its ability to make informed lending decisions.
• Regulatory Compliance: Regulatory requirements like GDPR or SOX impose strict rules on data handling, reporting, and auditing. Agentic AI assists financial firms in maintaining compliance by continuously tracking changes in regulations and automating compliance reporting. For example, AI-powered systems can scan vast amounts of documents for regulatory compliance issues, flagging discrepancies in real-time.

With risk management and fraud detection covered, it's time to shift focus to customer experience. In today’s financial landscape, where customer expectations are high, providing fast, efficient, and personalized service is a key differentiator.

In this section, we will see how agentic AI is transforming customer service within financial institutions and improving the overall customer journey.

Enhancing Customer Experience Through AI

Customer experience is a key differentiator in the competitive world of financial services. Agentic AI is transforming customer service by offering faster, more personalized interactions and improving customer satisfaction across various touchpoints.

Here’s how Agentic AI is changing the way financial services engage with customers:

• Personalized Financial Advice: Agentic AI systems analyze a customer’s financial history, goals, and market conditions to provide tailored financial recommendations. For example, Bank of America’s Erica, an AI-powered virtual assistant, helps customers track their spending, set savings goals and offers personalized financial advice based on individual spending habits.
• 24/7 Customer Support: With Agentic AI, financial institutions can provide round-the-clock customer service through AI chatbots and virtual assistants. These systems handle inquiries, process transactions, and even resolve common issues—without requiring human agents to step in. This has helped banks like Wells Fargo enhance their customer service capabilities while reducing operational costs.
• Streamlined Onboarding: AI agents can simplify the account opening process, guiding customers through complex paperwork, verifying their information, and ensuring compliance with all regulatory requirements. This speeds up onboarding and enhances the overall customer experience, as seen with HSBC’s AI-powered onboarding system.

Now that we’ve explored customer experience, let’s turn our attention to one of the most dynamic areas of financial services: investment and portfolio management. Here, we’ll delve into how agentic AI is reshaping investment management, from portfolio rebalancing to algorithmic trading.

AI’s Role in Investment and Portfolio Management

The world of investment management is evolving, and Agentic AI is playing a central role in this transformation. By automating key processes and analyzing massive amounts of financial data, Agentic AI is enabling better, faster decision-making.

How Agentic AI is influencing investment and portfolio management:

• Automated Portfolio Rebalancing: Agentic AI can automatically adjust portfolios in real time based on market conditions and client preferences. For example, BlackRock has leveraged AI to help re-balance investment portfolios based on client risk tolerance, market conditions, and performance metrics—ensuring that portfolios stay aligned with long-term goals.

Source: LinkedIn Post by Sohil Gandhi discusses the role of AI in the changing financial market.

• Algorithmic Trading: High-frequency trading is now driven by AI, where Agentic AI can analyze stock prices, market movements, and financial reports at lightning speed. Goldman Sachs utilizes AI-driven trading algorithms to make real-time trading decisions, optimizing returns for clients while managing risk.
• Sentiment Analysis: AI can analyze news articles, social media posts, and even earnings reports to gauge market sentiment and predict market trends. Morgan Stanley uses sentiment analysis to give traders real-time insights, improving their ability to make informed investment decisions quickly.

To illustrate the tangible benefits of implementing AI in customer support, let's explore a real-world example.​

Enhancing Customer Support Efficiency at TrueLayer with Ema

TrueLayer, established in 2016, is a leading fintech company in the UK and EU, specializing in open banking APIs that enable secure access to financial data. As their customer base expanded, TrueLayer's support team faced challenges in managing a high volume of complex technical inquiries. The need for a solution that could handle routine queries while allowing human agents to focus on more intricate issues became evident.

Challenges:

• High Ticket Volume: The support team was overwhelmed with repetitive technical queries, leading to slower response times.
• Complex Technical Inquiries: Customers required detailed assistance with APIs and integration processes, demanding specialized knowledge.​
• Operational Scalability: Expanding the support team to match growth was not a sustainable solution due to resource constraints.​

TrueLayer implemented Ema's Customer Support AI Employee, which was designed with Generative Workflow Engine and EmaFusion to manage complex support workflows autonomously. The integration process was streamlined:​

• Seamless Integration: Ema connected effortlessly with TrueLayer's existing Zendesk system, utilizing pre-built integrations.​
• Continuous Learning: By analyzing TrueLayer's Notion knowledge base, Ema rapidly adapted to the company's terminology and support processes.​
• Intelligent Escalation: Ema efficiently handled routine queries and accurately identified cases requiring human intervention, ensuring a smooth transition between AI and human agents.​

Results:

• Increased Automation: Within weeks, Ema autonomously resolved over 82% of incoming support cases, significantly reducing the workload on human agents.
• Enhanced Efficiency: The support team experienced improved response times and the ability to focus on more complex inquiries, leading to higher overall productivity.​
• Continuous Improvement: Ema's performance is continually enhanced through weekly updates, building trust and delivering consistent, high-quality support.

Elizaveta Shevchenka, Technical Support Lead at TrueLayer, remarked, "I’ve been truly impressed by the evolution of our partnership with Ema. Every week, Ema's Customer Support Assistant kept improving its accuracy and efficiency. The rapid progress is a testament to Ema's unique approach to building Gen AI applications."

Having explored current applications, let's now look ahead. The future of agentic AI in financial services holds tremendous promise. Let’s take a closer look at what the future holds for agentic AI in finance and how financial institutions can prepare for the changes ahead.

The Future of Agentic AI in Financial Services

The potential for agentic AI in financial services is vast, and as technology continues to evolve, we can expect even greater advances. Future trends include:

• Smarter Fraud Detection: AI systems will become even more sophisticated at detecting fraud by analyzing more data points, including social media activity and behavioral patterns.
• Predictive Analytics for Customer Behavior: AI will be able to predict customer behavior, allowing financial institutions to offer personalized services and anticipate needs before they arise.
• AI-Powered Investment Management: As AI systems become more advanced, they will be able to manage and optimize investment portfolios, offering real-time adjustments based on market conditions.

Conclusion

The integration of agentic AI in finance is reshaping how financial institutions operate. From enhancing fraud detection to automating customer service and ensuring regulatory compliance, AI is driving efficiency, reducing costs, and providing more personalized services. As technology continues to evolve, the future of financial services will become even more data-driven, intelligent, and autonomous.

If your financial services business is ready to take the next step in digital transformation, explore how Ema’s agentic AI solutions can help modernize your operations and boost productivity. Visit Ema today to learn more about how AI can revolutionize your business.