What is AI in banking and finance?

Artificial intelligence (AI) has made waves across many industries, and AI in banking and financial services is no exception. These technologies bring efficiency, speed, and value, automating manual tasks, minimizing the risk of errors, and reducing costs.

Use of AI in banking is on the rise, and for good reason. AI tools can help with risk management, regulatory compliance, fraud detection, investment and portfolio management, data security, and many other critical areas for the banking and finance sector.

Embracing artificial intelligence is no longer a matter of choice — failing to take advantage of this technology will put your organization at risk of falling behind. By strategically embedding AI, you can improve operational performance, enhance customer experience, and ensure your business remains competitive in an increasingly digital and data-driven marketplace.

The rise of AI in banking

AI isn’t a brand-new concept in the banking industry. For a long time now, the sector has leveraged advanced data and analytical methods to enhance operations and boost returns. With technologies advancing, AI tools can now process large amounts of data to produce extensive, accurate forecasts, identify emerging trends, and steer decision making.

Managing market and pricing volatility has quickly become one of the key AI trends in banking. In recent years, the sector has been hit by a number of significant global events including the COVID-19 pandemic, political upheaval, and the war in Ukraine. 

A World Bank Group report estimates the war alone has cost the financial sector a staggering $5.7 billion. These events have meant many organizations have turned to technology to limit their impact and provide stability in times of severe disruption.

Compliance is another one of the major applications of AI in banking. With so many strict laws and regulations to follow, getting this right and monitoring adherence amongst employees is a complex task. Using AI in the banking industry allows organizations to streamline regulatory compliance and ensure all protocols are being followed correctly — a key reason why 68% of financial firms plan to leverage AI for risk management and compliance.

The financial sector has also taken inspiration from other industries when it comes to applications of AI in banking. A wide range of businesses are now using virtual assistants and communications APIs to offer personalized support, automate customer service interactions, and save operational costs. Banks are taking advantage of these chatbots to free up their teams for more strategic tasks and to provide consistent and exceptional levels of service to customers.

Why AI matters to banking services and financial organizations

Ours is increasingly a digital-first world, meaning businesses are quickly realizing the advantages of AI in banking. More and more organizations are using AI-driven tools to automate routine processes and free up teams for higher-value tasks, bolster fraud protection, and deliver faster, more efficient customer service.

Customer expectations are rising, too. Almost three-quarters demand better personalization as technology advances, according to Salesforce’s State of the AI Connected Customer report.

Omnichannel banking is critical to meeting these customer expectations. AI helps enable seamless integration across channels, offering a unified and consistent experience whether customers interact via mobile apps, websites, or in-branch services. This omnichannel approach, powered by AI technology in banking, ensures personalized recommendations, faster responses, and better service delivery.

Benefits of AI in banking

The use of AI in banking and finance isn’t just a box-ticking exercise or a gimmick to impress customers. AI tools offer a variety of significant benefits to streamline operations, minimize fraud and risks, and provide greater service to customers and investors.

1. Improve fraud detection and prevention

AI tools can process and analyze huge swathes of data in a matter of minutes. This capability is critical for protecting customer assets and maintaining trust, allowing banks to monitor real-time activity and flag unusual behavior such as abnormal transaction volumes or unauthorized access attempts. The speed and accuracy of this process are simply unmatched by any human equivalent, making it one of the most important examples of AI in banking.

AI can even adapt to evolving threats, making fraud prevention more dynamic and robust. For financial institutions, minimizing fraud-related losses while ensuring compliance with regulatory standards and laws is vital. Leveraging AI in this way allows banks to address these concerns proactively, offering a much safer banking environment.

2. Provide personalized financial services

Analyzing data isn’t just about preventing fraud. It also unlocks valuable information about customers, such as spending habits, saving patterns, and investment preferences, so you can personalize your business communications and recommend tailored products.

Virtual agents can provide customized financial advice in real-time. This heightened level of personalization is a great way to level up your customer experience and foster customer loyalty. By making interactions relevant and individualized, banks can differentiate themselves and better address diverse financial needs.

3. Streamline loan approval processes

Loan approvals are traditionally a lengthy process involving lots of manual evaluations. Implementing AI that uses advanced models factoring in both conventional and alternative data points can analyze income and spending behavior to assess credit worthiness virtually instantly.

For customers, faster decisions improve satisfaction, and for banks, automation reduces operational costs, expands access to credit, and limits human bias. Since AI can provide more accurate risk assessments, it also reduces the chance of default risks, ensuring the bank's financial stability while enabling more inclusive lending practices.

4. Leverage predictive analytics for investment

Using AI in the banking industry empowers you to make smarter decisions. AI-driven predictive analytics helps investors and financial organizations identify promising investment opportunities. That allows for optimized portfolio management and more informed trading strategies.

This is particularly important in fast-moving markets, where timing can mean the difference between profit and loss. Being able to process vast amounts of data in a short space of time means traders can act quickly, optimize their portfolios, and achieve better returns.

For clients, this translates to more reliable investment strategies and increased trust in financial services. A portfolio manager, for example, can use AI technology to analyze historical stock performance, current market trends, and economic forecasts. This can help predict how a particular stock might perform in the future and guide the portfolio manager on how to adjust investments accordingly — such as by increasing shares in a growing technology company or reducing exposure to a struggling sector.

5. Enhance regulatory compliance with automation

Compliance is a crucial consideration for any banking or financial business. Operating under strict regulation means organizations must have robust processes in place to fulfill all their legal obligations, meet industry standards, and satisfy service requirements. This demands a huge amount of time, resources, and effort — and even then, human error is commonplace.

AI can help automate some of these processes by verifying customer identities, analyzing transaction data, and flagging suspicious activities. Natural language processing (NLP) can also review compliance reports and legal documents for inconsistencies. This reduces human error and accelerates regulatory processes.

Compliance is vital for avoiding legal penalties and maintaining a strong reputation. AI enables banks to handle these requirements efficiently, allowing staff to focus on strategic tasks while maintaining a high standard of accountability.

6. Offer better customer support

Virtual assistants are everywhere these days. Businesses are opting for AI-powered customer service solutions to offer personalized interactions, speedy responses, and real-time issue resolution. This also enables seamless, consistent customer support across multiple channels, including apps, websites, and branches.

With the ability to handle high volumes of queries simultaneously, using AI technology in banking for customer support reduces wait times and improves customer satisfaction. This fosters loyalty and positions banks as technology-forward institutions.

Uses of AI in banking

The applications and possibilities of AI are almost endless. Whether it’s simply automating manual tasks, identifying suspicious activity, or optimizing portfolios to maximize investment returns, artificial intelligence is a game-changer. Let’s take a closer look at some AI use cases in banking:

1. Blocking suspicious transactions

One of the most important examples of AI in banking is its use in preventing fraud. For example, AI tools can immediately identify if a customer’s credit card is used in two countries within an hour. The system can flag this, block the transaction, and alert the customer quicker than any human could. This real-time capability is crucial for minimizing financial losses and protecting customer trust.

2. Detecting money laundering in complex transactions

AI systems can analyze large volumes of transaction data at once. Using these tools allows banks and financial firms to uncover hidden money laundering schemes, such as layering funds across multiple accounts and jurisdictions. 

For example, if multiple small deposits from different locations are transferred to a single account, AI can flag the pattern. This process would overwhelm human analysts but is routine for AI, which excels at detecting subtle, large-scale anomalies. This ensures compliance with regulations while saving time and resources.

3. Automating mortgage pre-approvals

Banks receive millions of mortgage applications every year. Unsurprisingly, processing these applications takes a significant amount of time and requires a great deal of human scrutiny to assess affordability.

AI streamlines mortgage pre-approvals by analyzing applicant data, such as income, credit behavior, and property value, to calculate eligibility in minutes. For instance, a first-time homebuyer can use online banking to receive a quicker decision. 

AI also eliminates human bias and accelerates processing, making homeownership more accessible. This efficiency benefits banks by reducing costs and customers by offering fast, transparent decision-making.

Real-world examples of AI in banking

The power of AI sounds impressive on paper, but how does it work in practice? Let’s explore a couple of AI in banking examples below to discover the real-world applications of artificial intelligence:

Challenges with artificial intelligence and banking

Having seen the potential benefits, you might be wondering about the disadvantages of AI in banking. Using any technology is not without risk, but being aware of these risks and taking steps to mitigate them will ensure you can implement tools successfully and maximize their effectiveness.

Security and data privacy

Data security threats are one of the most significant risks of AI in banking. Due to the sheer amount of customer data banks must process daily, it’s no surprise that cyberattacks and breaches are a serious concern for the entire sector. This could result in loss of customer trust, reputational damage, and hefty regulatory penalties.

To avoid this, banks should implement robust security processes and train staff on the importance of complying with regulations and protocols. This might include strengthening encryption techniques, conducting regular security audits, and enforcing strict access controls.

Bias in AI models

If your systems have been exposed to biases in their training data and models, AI algorithms can inadvertently perpetuate these. This could result in discriminatory outcomes in areas like credit approvals or personalized financial advice, which puts you at risk of legal liabilities and reputational damage.

Making sure your data sets are diverse and robust is the first priority to ensure your AI tools are trained appropriately. Involving cross-functional teams during AI development will also help to promote inclusivity and equity, and regular audits will reduce the risk of biases going unnoticed.

Regulatory compliance

The speed at which AI technology is developing often outpaces the regulatory frameworks governing its use. For this reason, there is a real risk of non-compliance — leading to fines, operational disruptions, or reputational damage.

Actively collaborating with regulators will help to mitigate this, empowering organizations to prioritize transparency in AI decision-making and adopt adaptive compliance frameworks. These efforts will reduce risk and ensure artificial intelligence is being used fairly and ethically.

How banks should approach AI: best practices

Artificial intelligence in banking and finance can be a powerful tool, but only if implemented and maintained correctly. These best practices will set you up for success and give you confidence in your AI systems:

Develop robust, explainable AI models

Building an accurate and reliable AI model takes serious time and effort, but it’s an absolute necessity. If your AI technology is based on poor data or biases, the output is worthless. 

Providing clear, interpretable reasoning for your AI’s decisions (e.g., credit scoring) helps satisfy regulatory requirements, enhances customer trust, and ensures that employees can effectively oversee and understand the AI's actions.

Implement ethical AI guidelines

Creating industry-specific ethical guidelines will support you in addressing challenges like fair lending practices, anti-money laundering, and fraud prevention. 

These should include rules for minimizing bias in loan approvals or trading algorithms and guidelines for ensuring equitable outcomes for all customer segments.

Invest in AI-specific training

Your tools are only as effective as the people using them. Targeted training programs will support employees to understand AI tools and their applications in banking. That will give them the ability to monitor and analyze AI outputs, manage any challenges, and maintain ethical regulations. 

AI does not replace human oversight, but this training will align human expertise and machine intelligence for maximum efficiency.

Future of AI in banking

What might the future of AI in banking look like?

With technology developing so rapidly, banks and financial businesses should continue prioritizing AI innovation if they want to stay ahead of the curve. This means investing in new applications, updating existing tools, and being open to change.

As more organizations employ artificial intelligence, transparency, compliance, and ethics will become key issues. Businesses will have to be proactive in sharing their policies and guidelines to ensure their AI tools are operating properly and customers and regulators are satisfied.

Banks are under increased pressure to provide the best experiences they can. As customer expectations continue to rise, leveraging artificial intelligence will enable financial firms to personalize advice and interactions, provide prompt and effective services, and maintain compliance and regulatory requirements.

Integrate communication solutions with AI in banking to boost client service, security, and operational efficiency

Integrating AI into banking operations helps institutions deliver better client service, strengthen security, and improve operational efficiency. With the right communications solution, you can enhance customer experiences, support compliance efforts, and improve business outcomes.

Vonage offers advanced communication tools to ensure you achieve all of this and more. From automation and virtual assistants to fraud protection and robust security measures, Vonage delivers a full suite of AI-powered solutions to keep your business running smoothly.

Interested in improving your banking operations? Explore Vonage Communications APIs today.