AI for Banking: Examples, Use Cases & How Artificial Intelligence is Changing the Banking Industry in 2024?

Artificial intelligence (AI) is spearheading a formidable transformation within the realm of finance, particularly in the banking sector. As technology continues its relentless march forward, AI stands at the forefront, catalyzing profound changes in traditional banking procedures and revolutionizing customer interactions. Its impact is unmistakable, from the deployment of virtual assistants offering tailored financial guidance to the fortification of security through advanced fraud detection systems.

This article embarks on an exploratory journey into the multifaceted landscape of AI's integration into the banking industry. We will scrutinize a range of illustrative examples that showcase the manifold applications of AI, elucidate the advantages it bestows upon both clientele and financial institutions, and dissect prominent use cases that underscore its practicality. Furthermore, we will delve into the intricacies of implementing AI in banking, acknowledging the challenges and constraints that emerge, while also venturing to foresee the path this transformative technology charts for the future of finance.

How are Banks Leveraging AI in Banking in 2024?

Artificial intelligence (AI) is revolutionizing the banking industry by automating tasks, enhancing efficiency, reducing costs, and elevating the customer experience. According to McKinsey & Company, AI has the potential to generate up to $1 trillion in annual value for the banking sector by 2030. Banks are already leveraging AI in lending, finance and in various capacities, including:

• Fraud Detection and Prevention: AI-powered systems identify and prevent fraudulent transactions in real time.
• Risk Management: AI aids in more effective risk assessment, such as AI-driven credit scoring for improved lending decisions.
• Customer Service: AI-driven chatbots and virtual assistants offer 24/7 customer support and swift, accurate responses.
• Investment Advice: Robo-advisers provide personalized investment guidance based on individual needs and risk tolerance.

AI investment in banking reached $10.6 billion in 2022, a substantial increase from the previous year. AI startups in the banking sector have surged by 50% over the past year. Key trends include a focus on fraud detection and prevention, increased AI adoption in customer service, enhanced risk management, and the development of innovative banking products and services.

5 Examples of Companies Using AI in Banking

Top 5 AI companies for banking and finance are given below:

Ally Financial

Ally Financial is a digital financial services company that offers a wide range of banking, lending, and investment products and services. Ally is a leader in the use of artificial intelligence (AI) for banking and in the financial services industry.

Ally uses AI to improve its customer experience, automate its operations, and make better business decisions. For example, Ally uses AI to:

• Power its conversational banking chatbot, Ally Assist, which can answer customer questions, provide financial advice, and help customers with tasks such as budgeting and bill pay.
• Detect and prevent fraudulent transactions.
• Personalize its marketing and product offerings to each customer.
• Make better investment decisions and manage risk more effectively.

In 2023, Ally launched Ally.ai, a proprietary, cloud-based AI platform. Ally.ai combines traditional AI functionalities with generative AI tools, emphasizing human intervention, data security, and ethical considerations crucial to the financial services sector. 

Capital One

Capital One is a technology-driven financial services company. It is one of the leading users of artificial intelligence (AI) in the banking industry. Among the 50 banks examined in the CB Insights report, Capital One is the top applicant for AI patents in the US, having submitted more than 430 applications to far. Capital One places a high premium on using AI to prevent fraud and enhance cardholders' online experiences.

In 2018, it became one of just three banks on the list to purchase an AI company when it bought the AI consultancy business Notch.

Capital One uses AI for banking in a variety of ways to improve its business, including:

• Fraud detection: Capital One uses AI to develop and deploy fraud detection models that can identify and prevent fraudulent transactions. These models are trained on massive datasets of historical transaction data, and they are constantly being updated to keep up with the latest fraud trends.
• Credit risk assessment: Capital One uses AI to develop and deploy credit risk assessment models that can help the company make more informed decisions about who to lend money to. These models are trained on a variety of data points, including credit history, income, and employment status.
• Personalization: Capital One uses AI to personalize its products and services to each individual customer. For example, the company uses AI to recommend credit cards and other financial products to customers based on their spending habits and financial goals.
• Customer service: Capital One uses AI to power its customer service chatbot, Eno. Eno can answer customer questions about their accounts, transactions, and financial products. It can also help customers with tasks such as budgeting, bill pay, and transferring money.

In addition to these core applications, Capital One is also using AI to explore new and innovative ways to improve its business. For example, the company is using AI to develop new credit scoring models that can help more people access credit. Capital One is also using AI to develop new products and services, such as its AI-powered financial advisor, Capital One Venture X.

Vectra AI

Vectra AI is a cybersecurity company that provides AI-driven security solutions. Vectra AI's solutions are designed to help organizations detect, investigate, and respond to cyber threats, such as ransomware, malware, and data breaches.

Vectra AI's security solutions are powered by its Attack Signal Intelligence™ technology. Attack Signal Intelligence™ is a proprietary AI technology that analyzes network traffic and endpoint data to identify suspicious activity. Vectra AI's solutions can detect a wide range of cyber threats, including:

• Ransomware
• Malware
• Data breaches
• Lateral movement
• Command and control
• Exfiltration

Vectra AI's AI technology is able to detect these threats by analyzing patterns of behavior that are common to attackers. For example, Vectra AI's solutions can detect ransomware attacks by identifying patterns of data encryption and exfiltration. Vectra AI's solutions can also detect malware attacks by identifying patterns of malicious code execution.

Kensho

Kensho Technologies is a financial technology company that uses artificial intelligence - AI for banking and other financial institutions make better investment decisions and manage risk more effectively. Kensho's AI platform is powered by a massive dataset of financial data and machine learning algorithms that can identify patterns and trends that are difficult or impossible for humans to see.

Kensho's AI platform is used by a wide range of financial institutions, including hedge funds, investment banks, and asset managers. Kensho's customers use its platform to:

• Generate investment ideas
• Analyze market risk
• Make better trading decisions
• Develop new investment products and services

Kensho's AI platform is powered by a variety of machine learning algorithms, including:

• Natural language processing (NLP)
• Machine learning
• Deep learning

NLP algorithms are used to extract information from financial news and research reports. Machine learning algorithms are used to identify patterns and trends in financial data. Deep learning algorithms are used to develop more complex and sophisticated models for financial analysis and prediction.

Kasisto

Kasisto is a financial technology company that provides AI-powered conversational banking solutions to banks and other financial institutions. Kasisto's solutions help banks to create chatbots and virtual assistants that can answer customer questions, provide financial advice, and help customers with tasks such as budgeting and bill pay.

Kasisto's conversational banking solutions are powered by its KAI AI platform. KAI is a proprietary AI platform that is specifically designed for the financial services industry. KAI has a deep understanding of financial concepts and products, and it can be used to create chatbots and virtual assistants that can interact with customers in a natural and engaging way.

Kasisto's conversational banking solutions are used by a wide range of banks and other financial institutions, including some of the largest banks in the world. Kasisto's customers use its solutions to:

• Improve customer service in banking
• Reduce costs
• Increase customer engagement
• Drive new business opportunities

Here are some specific examples of how Kasisto's conversational banking solutions are being used by banks and other financial institutions:

• A bank uses Kasisto's conversational banking solutions to create a chatbot that can answer customer questions about their accounts, transactions, and financial products. The chatbot can also help customers with tasks such as budgeting and bill pay.
• A credit union uses Kasisto's conversational banking solutions to create a virtual assistant that can help members with loan applications and other financial services. The virtual assistant can also provide members with financial advice and help them to manage their finances.
• A wealth management firm uses Kasisto's conversational banking solutions to create a chatbot that can help clients with their investment portfolios. The chatbot can answer client questions about their investments, provide them with market updates, and help them to make investment decisions.

Top 10 Use Cases of AI in Banking in 2024

1. Fraud detection and prevention

AI can be used to analyze large amounts of data to identify patterns and anomalies that may indicate fraudulent activity. This can help banks to detect and prevent fraud before it occurs, saving them money and protecting their customers.

According to a report by Juniper Research, AI-powered fraud detection solutions will save banks and other financial institutions $17.5 billion annually by 2026. The report also found that AI-powered fraud detection solutions can reduce fraud losses by up to 50%.

2. Credit scoring and lending

AI can be used to develop more accurate and sophisticated credit scoring models. This can help AI in banking method can be used to make better lending decisions, reduce risk, and make credit more accessible to borrowers.

According to a report by Gartner, AI-powered credit scoring solutions will help banks to increase loan approval rates by 15% by 2025. The report also found that AI-powered credit scoring solutions can help banks to reduce loan defaults by up to 20%.

3. Risk management

AI can be used to assess and manage risk across a range of banking activities, including trading, investment, and lending. This can help banks to reduce their exposure to risk and protect their financial health.

According to a report by Accenture, AI-powered risk management solutions will save banks and other financial institutions $20 billion annually by 2025. The report also found that AI-powered risk management solutions can help banks to reduce operational risk by up to 30%.

4. Customer service

AI can be used to power chatbots and virtual assistants that can answer customer questions, provide support, and resolve issues quickly and efficiently. This is one AI for banking use cases that can improve the customer experience and reduce costs for banks.

According to a report by Swiss Cognitive, AI-powered customer service solutions will help banks to reduce customer churn by 10% by 2025. The report also found that AI-powered customer service solutions can help banks to increase customer satisfaction by up to 20%.

App0 is one such AI company that enables financial services to launch AI agents faster and power customer service through AI powered text messaging, that's beyond traditional chatbots that can only answers basic FAQs.

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5. Personalization

AI can be used to analyze customer data and preferences to provide personalized product and service recommendations. This can help banks to improve customer engagement and satisfaction.

According to a report by McKinsey & Company, AI-powered personalization solutions will help banks to increase revenue by up to 15% by 2025. The report also found that AI-powered personalization solutions can help banks to reduce customer churn by up to 10%.

6. Compliance

AI can be used to monitor and ensure compliance with complex financial regulations. This can help banks to reduce the risk of fines and penalties.

According to a report by KPMG, AI-powered compliance solutions will help banks and other financial institutions to reduce compliance costs by up to 30% by 2025. The report also found that AI-powered compliance solutions can help banks to reduce the risk of regulatory fines by up to 50%.

7. Product development

AI can be used to develop new and innovative banking products and services. For example, AI in banking can be used to develop personalized investment portfolios, automated financial planning tools, and chatbots that can help customers with their banking needs.

According to a report by Deloitte, AI-powered product development solutions will help banks to launch new products and services 50% faster than traditional methods by 2025. The report also found that AI-powered product development solutions can help banks to reduce the cost of developing new products and services by up to 20%.

8. Operational efficiency

AI can be used to automate many of the manual tasks involved in banking operations. This can help banks to improve efficiency, reduce costs, and focus on more strategic initiatives.

According to a report by McKinsey & Company, AI-powered automation solutions will help banks and other financial institutions to reduce operating costs by up to 25% by 2025. The report also found that AI-powered automation solutions can help banks to release up to 20% of their workforce for more strategic tasks.

9. Cybersecurity

AI can be used to detect and respond to cyber threats in real time. This can help banks to protect their systems and data from cyberattacks.

According to a report by Gartner, AI-powered cybersecurity solutions will help banks and other financial institutions to reduce the cost of data breaches by up to 30% by 2025. The report also found that AI-powered cybersecurity solutions can help banks to reduce the time to detect and respond to cyberattacks by up to 50%.

10. Financial inclusion

AI can be used to make banking more accessible and affordable for people who are currently underserved. For example, AI can be used to develop mobile banking apps and chatbots that can be used by people in rural areas and by people with disabilities.

According to a report by the World Bank, AI-powered financial inclusion solutions will help banks and other financial institutions to reach 1 billion new customers by 2025. The report also found that AI-powered financial inclusion solutions can help banks to reduce the cost of providing financial services to low-income customers by up to 50%.

How Artificial Intelligence is Changing the Banking Industry?

Artificial intelligence (AI) is fundamentally reshaping the banking industry, ushering in a new era of automation, efficiency, and personalized services. AI-driven innovations have given rise to chatbots and virtual assistants capable of handling customer inquiries, processing transactions, and providing support around the clock. This automation not only ensures seamless customer service but also liberates human employees to concentrate on more intricate tasks like offering tailored financial advice and nurturing customer relationships. Banks now have the capacity to deliver faster and more responsive service, enhancing overall customer experiences.

AI is not only about front-end customer interactions; it is also making significant inroads into back-office operations, enhancing efficiency and driving cost reductions. AI-powered systems are adept at automating critical functions such as fraud detection, risk management, and compliance checks. This automation empowers banks to streamline their processes, cut operational costs, and ultimately bolster their bottom line. AI's multifaceted role in the banking sector, spanning automation, efficiency, and personalization, demonstrates its potential to revolutionize banking operations and customer engagement, although this transformation is still in its early stages, and there is much more to explore in the evolving landscape of AI in banking.

AI is transforming the banking industry by shifting the focus from transactions to relationships

In the past, banks predominantly centered their operations around transactional services, focusing on activities like account openings, deposits, and withdrawals. However, the advent of AI has ushered in a transformative shift, steering banks toward a more customer-centric and relationship-oriented approach. AI in banking have the capacity to analyze customer data, gaining invaluable insights into their individual needs and preferences. This knowledge enables banks to establish stronger and more personalized relationships with their customers, offering tailored services and support. For instance, AI can pinpoint customers at risk of churning and provide them with personalized retention offers. Furthermore, AI aids in the development of new products and services that cater to the specific needs of distinct customer segments. This shift from a transactional to a relationship-centric paradigm is redefining the banking landscape, fostering deeper customer loyalty and enhancing the overall customer experience.

Conclusion

In conclusion, artificial intelligence (AI) is catalyzing a remarkable transformation within the banking industry, transcending traditional boundaries and propelling financial institutions into a new era of efficiency, automation, and personalized service. The impact of AI in the banking industry is undeniable, as it redefines the way banks interact with their customers, offering tailored solutions and support while optimizing their internal operations. AI has already proven its worth in fraud detection, risk assessment, customer service, and personalization, setting the stage for a brighter future in banking. As we delve deeper into the intricacies of AI in banking, one thing becomes clear: this is just the beginning of a thrilling journey into the uncharted territories of innovation and customer-centric banking. The banking landscape is evolving, and AI is leading the way, promising a future where customers are at the center of every financial endeavor, and relationships matter more than transactions. So, as we navigate this transformative path, we can look forward to an even more dynamic, efficient, and customer-focused banking industry, with AI as the guiding force.

If you're looking forward to powering your financial services using conversational AI, we suggest you check out App0.

App0 is a no-code, conversational AI platform that automates critical elements of customer communication during origination in banks, financial institutions, and fintech. App0 is used by leading financial services companies to power their customer onboarding with AI.

It is a next-gen communication platform powered by machine learning (ML) & large language models (LLM), that allows you to embed communication features directly into your product, with simple no-code integrations that don’t require additional developer bandwidth.

Here are specific instances of how financial services firms are implementing App0:

• In the realm of equipment and asset finance, App0 is employed by companies to introduce conversational AI into the equipment leasing procedure. This integration has led to a decrease in deal closure time, an elevation in deal conversion rates, and an enhancement in overall customer satisfaction.
• Automotive finance companies are utilizing App0 to automate the loan application and approval workflow. This application has contributed to a surge in loan origination volumes for these companies.
• Consumer banks are integrating App0 to automate and digitize the entire consumer lending origination process. This streamlining has resulted in a reduction in the time it takes from the initiation of a loan application to the actual funding of the loan, thereby minimizing the time spent in prolonged interactions with customers.

If you are interested in learning more about how App0 can be used, please request a demo. Our team of experts will be happy to show you how App0 can help you streamline your operations, improve customer service, and grow your business.

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