The Future is Here: 5 Compelling AI Use Cases Transforming the Banking Industry

In the banking industry, the integration of artificial intelligence has emerged as a transformative force, reshaping traditional practices and setting new standards for efficiency and innovation. Beyond mere automation and data analysis, AI is propelling banking into a new era, touching upon crucial facets such as customer service, fraud detection, and risk management. 

Furthermore, according to Autonomous Next, AI has the potential to result in $1 trillion of cost savings for the banking industry by 2030, adding a financial dimension to the revolutionary impact of AI in shaping the future of banking.

This article delves into the dynamic realm of AI applications in banking, uncovering groundbreaking use cases that extend far beyond conventional paradigms.

The AI Advantage: Reimagining Banking with Intelligence

AI in banking is emerging as a transformative force, injecting a dose of intelligence and human-like intuition into every facet of banking. Brick-and-mortar banks and static algorithms are no longer king. But what specific qualities of AI hold the key to unlocking a superior banking experience?

Transformations in the Banking Industry: 5 Impactful Approaches Where AI Is Making a Difference

In recent years, artificial intelligence’s impact on banking has experienced notable growth. Moreover, this trajectory is poised for an even greater ascent—projections indicate that the value of artificial intelligence in the banking industry is anticipated to surge to $65 billion by the year 2030, a substantial leap from the $3.9 billion recorded in 2020.

Now we’ll examine pivotal instances of AI shaping the banking industry’s future and driving its sustained growth.

1. Generative Artificial Intelligence

While artificial intelligence has been a part of the banking industry for years, 2023 marked a significant shift with the introduction of ChatGPT, a groundbreaking deep-learning model poised to change the financial landscape. 

In a departure from previous models, ChatGPT proudly features an unparalleled 170+ billion parameters, establishing itself as the most extensive language model currently accessible.

Although the fundamental applications of artificial intelligence in banking remain consistent, the utilization of ChatGPT promises to enhance their effectiveness. For instance, its capabilities can instill greater confidence in banks when assessing loan applications, thanks to its self-training ability that ensures remarkably high accuracy.

If you’re considering incorporating deep learning into your project, we’re here to help—get in touch with us for assistance.

Moreover, ChatGPT is set to revolutionize the personalization of financial product recommendations, particularly with the rising prominence of open banking. The latest updates make ChatGPT more attractive to different industries; you can learn about it in our article along with a detailed comparison.

In fintech, open banking involves securely sharing customers’ data between banks or financial institutions via APIs, aiming to conduct more in-depth data analysis of customers and offer more relevant suggestions. 

Open banking, by granting banks access to diverse customer data sources, amplifies ChatGPT’s capacity to deliver exceptionally personalized services, offering a holistic view of individuals’ financial situations.

• Wells Fargo’s AI-empowered “Predictive Banking” feature examines transaction patterns, offering personalized financial products such as savings goals and automated bill payments, promoting better financial habits.
• HSBC’s “Fraud Prevention System” powered by AI analyzes millions of transactions daily, identifying anomalies and fraudulent patterns with remarkable accuracy, protecting millions of customers from financial crimes.
• BNP Paribas’s “Goal Planning” tool utilizes AI banking solutions to help customers set and achieve personal financial goals, offering personalized advice and tracking real-time progress, empowering individuals to take control of their financial futures.

2. Smart Banks Driven by AI

AI-powered and smart banks incorporate innovative technologies and AI-driven solutions to revolutionize traditional banking processes, offering a more efficient, personalized, and technologically sophisticated experience.

Millennials, who crave personalized experiences, are leading the charge. In 2022, a whopping 57% expressed interest in ditching traditional banks for digital-only alternatives like Ally Bank. Ally, a prime example of a “smart bank,” utilizes AI in banking to tailor recommendations and deliver a user-friendly experience.

Key features:

• Data Analysis: Advanced analytics and machine learning algorithms are utilized to analyse vast amounts of data. We use machine learning services to gain insights into customer behavior, identify patterns, and make data-driven decisions for risk management, fraud detection, and personalized financial recommendations.
• Automation: Smart banks automate various tasks and processes, reducing manual workload and minimizing errors. This includes automating routine transactions, account management, and administrative tasks, allowing human resources to focus on more complex and strategic aspects.
• Personalization: AI in banks enables the personalization of services for individual customers based on their preferences, behaviour, and financial history. This can include personalized product recommendations, targeted marketing, and tailored financial advice.
• Security: AI-powered security measures, such as biometric authentication, behavioural analysis, and anomaly detection, enhance the overall security of banking operations. These measures help prevent fraud and unauthorized access to accounts.
• Innovative Products: Smart banks often introduce innovative financial products and services driven by AI, such as robo-advisors for investment management, predictive lending models for credit assessments, and AI-driven risk management strategies.
• Accessibility: AI-powered banks prioritize accessibility through digital channels, providing customers with user-friendly mobile apps and online platforms. This ensures seamless and convenient banking experiences anytime, anywhere.

AI Use Cases in Banking

• Nubank uses AI to analyze spending patterns and offer micro-loans tailored to individual needs. They’ve eliminated bureaucratic hurdles and provided instant loan approvals, empowering financially underserved communities.
• Bank of Montreal uses AI in banking to identify suspicious activity but doesn’t rely solely on algorithms. Trained advisors follow up on AI alerts, adding a human layer of understanding to ensure accurate fraud detection while minimizing false positives.
• ABN AMRO (Netherlands) “InvestLab” AI platform analyzes client goals and risk tolerance to create personalized investment portfolios. It eliminates expensive financial advisors, making responsible investing accessible to everyone, regardless of income.

3. AI Banking through Conversation

Conversational banking refers to a banking approach that utilizes natural language processing (NLP), artificial intelligence, and chatbot technologies to facilitate communication and interactions between customers and financial institutions. 

This innovative AI banking model aims to create a more user-friendly, efficient, and personalized experience by allowing customers to engage in natural language conversations with virtual assistants, chatbots, or AI-driven interfaces.

Key aspects:

• Chatbots and Virtual Assistants: Conversational banking often relies on the deployment of chatbots and virtual assistants that can understand and respond to user queries and commands. These AI-driven entities are designed to simulate human-like interactions, providing immediate assistance, answering questions, and guiding users through various banking processes. At LITSLINK, we believe that virtual assistants will become commonplace soon.
• 24/7 Accessibility: Unlike traditional banking models that adhere to business hours, AI banking solutions provide round-the-clock accessibility. Customers can engage in conversations, perform transactions, and seek assistance anytime, enhancing convenience and meeting the demands of a global and interconnected world.
• Transaction Support: Conversational banking extends beyond simple inquiries to include transactional support. Users can perform various banking transactions through natural language interactions with the chatbot or virtual assistant, such as fund transfers, bill payments, account inquiries, and more.
• Educational Services: Chatbots in conversational banking often serve as educational tools, providing users with information about financial products, explaining banking terms, and offering guidance on financial planning. This fosters financial literacy among users. One of the ways to improve the learning experience in this case would be to use AR technology with its advantages.

AI Use Cases in Banking

Well-known instances encompass Bank of America’s Erica and Ally Bank’s Ally Assist, providing functionalities that extend beyond mere language comprehension.

For instance, Erica, the conversational chatbot from Bank of America, not only handles bill payment, fraud detection, and account management but also gives users helpful insights to manage finances better. 

With features like Spend Path, customers can optimize budgets. Ally Bank’s assistant can even connect with solutions such as Amazon’s Alexa, showing how AI in banking teams up with smart technologies at home.

CIMB Bank`s, (Malaysia), virtual assistant, “Cimb A.I.,” goes beyond answering basic questions. It understands financial jargon, analyzes user data to offer personalized recommendations, and even jokes around, creating an engaging banking experience.

4. Robotic Assistance within Bank Branches

AI in banking is making a splash with in-branch robots, adding excitement to the industry. These robots are becoming more common as banks aim to boost efficiency and improve customer experience.

These robots in banks use smart technology to help customers when they visit the bank. Here are some exciting features of these robots:

• Talking and Helping: These robots speak to customers in a friendly way. They can share information about the bank’s services, help customers with different tasks, and answer common questions.
• Like Virtual Assistants: Think of them like virtual assistants. They help with things like checking account details, recent transactions, and managing accounts.
• Doing Transactions: Some of these robots can also help with simple tasks like transferring money, paying bills, and depositing checks. This saves time for customers and reduces the work for human staff.
• Recognizing Faces and Personalizing: The advanced AI banking solutions can recognize customers’ faces and provide personalized help. This adds an extra layer of security and allows the robot to give more customized assistance based on the customer’s history and preferences.
• Managing Lines: These robots help manage lines at the bank by telling customers how long they might have to wait. They guide them to available service desks or even help schedule appointments with bank staff.
• Sharing Information: The robots share information about the bank’s products, promotions, and updates. They also teach customers about different financial services, helping them understand better.

AI Use Cases in Banking

Pepper, crafted by SoftBank, serves as a prime example in the realm of robotics. Banks like HSBC and Mizuho Bank use it. Pepper welcomes customers, answers simple questions, and gives information about bank services.

Originally created for Hilton Hotels, the robot named Connie has found its way into banks. Connie uses artificial intelligence to learn about clients’ preferences, offering personalized recommendations about bank services and products.

The NAB has also joined the trend, installing SoftBank Robotics’ robots in branches. NAO can perform transactions like transferring money and opening accounts.

5. Connected Banking: The Future of Financial Services

In 2021, the global market for the IoT was worth $12.8 billion, and experts predict it will grow to $238.5 billion by 2030 in the banking industry. When we combine artificial intelligence (AI) with IoT in banking, the benefits become more significant, expanding how both technologies can be used.

The Bank of Things is a futuristic banking model. The IoT connects everyday devices to the internet, enabling them to send and receive data. BoT is a system that uses data from these devices to provide improved financial services for individuals and businesses.

Key features:

• Smart Banking Operations: The Bank of Things could seamlessly blend IoT devices into banking tasks, like using smart devices for secure logins, tracking transactions, or customizing financial preferences.
• Smart Transactions: Everyday items like cars or wearables could be part of banking. For instance, a car might pay for fuel automatically, or a wearable device could handle contactless payments.
• Data for Insights: The data from IoT devices could provide personalized insights for customers and AI banking solutions. This information could help assess risks, better plan finances, and enhance the customer experience. At the moment, it is possible to combine IoT with AR to provide a better and wider service.
• Security Boost: IoT might offer new ways to keep accounts secure. Using biometric data from connected devices could replace traditional methods like passwords.
• Automated Finances: IoT devices could automate financial management by keeping track of spending and sticking to set budgets. For example, a smart home system could optimize energy use and payments.

AI Use Cases in Banking

Some banks are using smart ATMs with connectivity and sensors to offer users a more secure experience. These ATMs commonly incorporate security features such as voice and face recognition to deter fraudulent activities.

The significance of AI in banking becomes even clearer when addressing the prevention of money laundering. Cameras empowered by AI can offer proof of questionable transactions and activities, aiding banks in surveilling customer and employee conduct for indications of illicit activities.

Final Thoughts

AI in banking is changing how banks work. It’s not just about automating everyday tasks anymore. AI is now helping with things like stopping fraud and giving personalized service. 

This makes banks more efficient, saves money, and gives customers a better experience. Many banks are ready to use AI even more in the future, transforming how we handle money, invest, save, and talk to banks.

If you’re considering starting a fintech business or need special software or applications for your finance company, team up with LITSLINK. We offer top-notch ML development, legal compliance advice, and QA support. 

Our skilled developers have a lot of experience creating AI solutions to make banks work better, improve services, and save money.