Imagine walking into a bank and having every query handled in seconds, loan approvals completed almost instantly, and personalised financial products recommended without needing to speak to a human. This isn’t fiction; it’s happening now. Thanks to generative AI agents, these autonomous systems are changing how large banks operate, driving efficiency, enhancing customer experience, and boosting profitability. To understand the full potential of this technology, check out our in-depth guide to Generative AI in the financial industry.

Let’s explore how these agents are making waves in the financial sector.

Understanding Generative AI Agents in Financial Services

What Are Generative AI Agents?

Generative AI agents are autonomous, AI-powered systems capable of completing complex tasks like customer service, loan approvals, fraud detection, and financial forecasting without human intervention. These agents don’t just follow pre-set rules; they learn, adapt, and make decisions based on vast amounts of data.

Evolution from Traditional AI to Generative AI Agents

Traditional AI in banking largely focused on automating repetitive tasks, such as handling basic customer queries or processing transactions. Generative AI agents, however, are a step further. They’re capable of generating new insights, making decisions autonomously, and even improving themselves through machine learning.

These agents rely on cutting-edge AI models like Generative Adversarial Networks (GANs) and transformers to process complex data and offer intelligent, real-time solutions.

Key Applications of Generative AI Agents in Large Banks

Customer Service Enhancement: Autonomous AI Agents in Action

One of the most visible applications of generative AI agents is in customer service. For example, HSBC has deployed AI agents capable of handling customer queries autonomously, significantly reducing wait times and providing tailored responses. These agents learn from each interaction, allowing them to continuously improve the quality and relevance of their answers.

In Southeast Asia, DBS Bank is leading the charge with its AI-driven customer service agents. These agents autonomously handle everything from answering routine inquiries to providing personalised financial advice. By analysing vast amounts of customer data, the AI agents are able to offer customised solutions, improving customer satisfaction and retention.

Risk Management and Fraud Detection

Generative AI agents are also revolutionising risk management. Take JPMorgan Chase, for example, which has deployed an AI agent called COIN (Contract Intelligence). COIN autonomously reviews and processes complex financial contracts, reducing human error and freeing up employees for higher-value tasks. By processing thousands of documents in seconds, COIN has saved JPMorgan millions in operational costs.

Fraud detection, a critical area in banking, has also benefitted from AI agents. These agents continuously monitor transactions for anomalies and autonomously flag potentially fraudulent activities. This real-time monitoring helps large banks reduce fraud risks, saving money and protecting customer trust.

Financial Forecasting and Reporting

Generative AI agents are capable of automating financial forecasting and report generation. By analysing historical data and real-time market trends, these agents produce highly accurate reports and predictive models, allowing banks to make faster, more informed decisions.

DBS Bank uses AI agents to streamline financial reporting, saving valuable time and resources. These agents can generate daily, weekly, or monthly reports autonomously, reducing the need for human intervention in financial modelling and forecasting.

Benefits of Implementing Generative AI Agents

Increased Efficiency and Cost Savings

Large banks like JPMorgan Chase and HSBC are using generative AI agents to streamline operations, reduce manual workloads, and cut costs. AI agents can autonomously handle tasks such as loan processing and customer inquiries, reducing the need for human resources and speeding up services.

By automating repetitive tasks, AI agents free up employees to focus on more strategic roles, driving efficiency across the organisation. This level of automation can lead to significant cost savings, particularly in large-scale operations where even small efficiency gains can result in millions saved annually. So much so that banking CIOs are increasingly recognising the value of GenAI solutions.

Enhanced Decision-Making Capabilities

Generative AI agents provide real-time data insights that are invaluable for decision-making. By continuously learning from past transactions, customer interactions, and market trends, AI agents enable executives to make faster, more accurate decisions.

Customer Experience Improvement

Customer experience is critical in today’s banking environment, and AI agents are a game-changer in this area. By providing personalised banking services, AI agents create a more engaging customer experience. These agents can offer tailored financial products based on individual customer profiles, increasing customer loyalty and lifetime value.

Large banks like DBS and HSBC are already seeing the benefits of deploying AI agents for customer service, with faster response times and higher satisfaction rates. Customers no longer have to wait for hours to resolve issues, as AI agents can handle requests almost instantly.

Challenges in Adopting Generative AI Agents

Data Privacy and Regulatory Compliance

One of the biggest challenges large banks face when adopting AI agents is data privacy. AI agents need access to vast amounts of customer data to function effectively, raising concerns about how this data is managed and protected.

In regions like Europe, compliance with GDPR (General Data Protection Regulation) is mandatory. Banks must ensure that their AI agents are designed to adhere to these regulations, which can complicate the implementation process. However, data privacy concerns can be mitigated by building robust security measures into AI systems, ensuring that customer data is protected at all times.

Integration with Legacy Systems

Many large banks rely on legacy systems that are difficult to integrate with modern AI technologies. Introducing generative AI agents into these systems can require significant investments in IT infrastructure and may necessitate partnerships with external AI providers to ensure smooth integration.

However, banks like DBS have successfully navigated artificial intelligence challenges by upgrading their systems and leveraging cloud technologies to facilitate the integration of AI agents.

Upskilling Staff

Generative AI agents can perform many tasks autonomously, but staff still need to manage and oversee these systems. Upskilling employees to work alongside AI technologies is essential. Banks must invest in training programs that allow employees to understand and optimise AI agents, ensuring that the technology is used to its full potential.

Future Outlook for Generative AI Agents in Banking

Predictions for AI Agent Adoption

As more banks begin to see the benefits of generative AI agents, adoption rates are expected to skyrocket. According to a study by PwC, AI could contribute up to $15.7 trillion to the global banking industry by 2030, with generative AI agents playing a key role.

Long-Term Financial Benefits

The financial benefits of AI agents are clear: reduced operational costs, increased revenue from personalised customer experiences, and improved decision-making. Banks that invest in these agents now will be better positioned to navigate future market challenges and stay ahead of the competition. Read here to explore the emerging trends of Generative AI in banking.

In a Nutshell

Generative AI agents are no longer an experimental technology—they’re transforming how large banks operate today. From improving operational efficiency to enhancing customer experiences, these autonomous systems offer unparalleled advantages. Large banks that embrace AI agents will not only reduce costs and improve decision-making but also stay competitive in an increasingly tech-driven financial landscape.

As the technology continues to evolve, the banks that invest in generative AI agents now will be well-positioned to thrive in the future. With the ability to automate complex tasks, provide real-time insights, and personalise customer services, these AI agents are becoming indispensable for financial institutions aiming to improve their bottom line.

Now is the time for large banks to take the leap—those that don’t risk falling behind, while those that do will set the benchmark for the next generation of banking.

About JurisTech

JurisTech is a global leading company, specialising in enterprise-class lending and recovery software solutions for banks, financial institutions, telecommunications, and automobile companies worldwide. JurisTech has been mentioned as a Representative Provider for Lending Ecosystems, as a Representative Vendor for Commercial Loan Origination Solutions, and as a Sample Vendor for Commercial Banking Onboarding across Gartner reports in 2024.

We power economies by reimagining financial services with cutting-edge software solutions, leveraging composable architecture and generative AI. Our offerings include artificial intelligence (AI), auto-decisioning, digital customer onboarding, loan origination, credit scoring, loan documentation, litigation, and debt collection.

Our solutions have enabled businesses across a broad array of industries to undergo digital transformation, providing enhanced customer experiences and, most importantly, achieving their business goals.