AI and its role in the banking industry

AI and its role
in the banking

artificial intelligenc

AI’s rise in banking reshapes financial interactions and decision-making. 

The banking sector is rapidly embracing artificial intelligence (AI). By 2030, AI capabilities might release $1 trillion in global banking revenue pools, according to banking leaders surveyed by Roland Berger. Additionally, AI capabilities could result in up to a 25% reduction in expenses related to operations, compliance, and customer care.

AI is changing how banks operate, from automating routine tasks to providing advanced analytics for decision-making. AI is not just enhancing efficiency but also redefining customer engagement through personalized experiences and sophisticated risk management. This article will explore the practical impact of AI on banking, highlighting the benefits and challenges it brings to financial institutions and their customers. We’ll delve into the ways AI is integrated into the core functions of banks, setting the stage for a new era of digital financial services.AI in the banking industryFigure 1. AI in the banking industry

Artificial intelligence in banking and its applications

AI in baking is about the application of machine learning algorithms, data analytics, and computational logic to financial services. It is used to streamline operations, enhance customer service, and improve decision-making. Below, we’ll examine the applications of artificial intelligence in banking and how it is changing the services that banks provide:

  • User inquiries. Rather than carefully searching for a button or feature, a user can ask AI questions and get conversational answers. For instance, users might want to create spending reports or determine their account balance. Using banking AI, they can obtain all the data instantaneously without going through a lengthy process to accomplish these tasks. The use of banking AI improves the convenience of services, saves the user time, and requires less work to make an inquiry.
  • Financial management. AI-powered chatbots, trained on extensive datasets, can provide clients with guidance and financial management assistance. Users can interact with these chatbots to receive personalized advice on improving their financial handling and insights into investment trends and financial opportunities within their industry. By analyzing their income, essential expenses, and other financial areas, customers can gain valuable information that helps them make informed decisions. In essence, AI serves as a virtual financial advisor, offering free, data-driven counsel to help clients optimize their financial strategies.
  • Management of credit score. The AI bank can assist with monitoring credit scores as well. Chatbots can consult users at any moment for guidance on raising their credit score. From the business perspective, AI-powered solutions may analyze large amounts of financial data, such as transaction data or credit scores, to identify credit risks early on and shield an organization from losses.
  • Finance-related activities. Users can utilize AI-powered chatbots to make banking transactions easier. They can instruct the AI to move money to their accounts or the accounts of others, for instance. When placing online orders, users have the option to ask the chatbot to finish the payment process. They can save time by assigning this task to AI rather than manually entering the payment information. Additionally, AI is capable of creating and sending payment recipes to sellers as a confirmation of the transaction.
  • Customer service. Banks may use chatbots driven by AI to ensure top-notch customer support around the clock. For example, banks can refer a user to artificial intelligence as the first step in providing an answer to their query. If AI is unable to help on its own, a user can be connected to a human assistant. This strategy can save a significant amount of staff time that would otherwise be wasted on meaningless activities and inquiries. Client satisfaction rates will also rise as a result of their getting timely responses to their questions.
  • Management of accounts. Banking systems enhanced with artificial intelligence can be programmed to assist customers in managing their financial accounts. A model can be trained to perform many tasks, such as modifying bank information, setting up automatic payments, and sending alerts when payments are due. Clients will use the technology to complete the task instead of requesting management to do it manually, which will increase efficiency.
  • Management of insurance. A client’s insurance claim process takes a long time. Furthermore, there is usually a ton of paperwork and checks involved in this procedure. Businesses can use AI to expedite this process for clients and banks. Users will receive the claim procedure checklist with the solution, confirm that they follow the guidelines, and submit their applications.
  • Management of loan applications. Both for individuals applying for loans and for banks reviewing applications, the process can be time-consuming. AI can make this process easier for everyone. An applicant for a loan may begin by utilizing AI banking chatbots. AI will determine whether or not a user’s application satisfies the standards and then send it to managers for a human review. The application of AI will benefit customers as well. If they need advice or information on the loan application, they can consult the chatbot. Users will always receive assistance and advice on how to move the process forward.

As we can see, AI applications in banking are vast and varied, offering significant enhancements to traditional banking processes. As the industry embraces these technological advancements, we can expect banking services to become more accessible, accurate, and user-friendly, ultimately benefiting both institutions and clients.Applications of AI in banking and financeFigure 2. Applications of AI in banking and finance.

Banking and AI advantages

Banks that employ and embrace AI can benefit from several significant advantages, including:

  • Enhanced cybersecurity. AI plays a critical role in fortifying banks’ defenses against cyber threats. AI systems can analyze patterns and detect anomalies that indicate potential security breaches. Unlike traditional security measures, AI can adapt and respond to threats in real time, providing a dynamic shield against hackers. AI-driven security systems can sift through vast amounts of data to identify suspicious activities, such as unusual login attempts or transactions, and flag them for further investigation. This proactive approach not only prevents financial losses but also protects sensitive customer data from being compromised.
  • Fraud detection. Banks are inundated with transactions, making it humanly impossible to scrutinize each one for signs of fraud. AI steps as a vigilant overseer, using predictive analytics and pattern recognition to spot fraudulent activities. By learning from historical data, AI models can predict typical customer behavior and detect deviations that might signify fraud. For instance, if a customer who typically makes small local purchases suddenly starts making large international transactions, the AI system can raise an alert. AI also enhances the accuracy of fraud detection by reducing false positives. A good example is Danske Bank, Denmark’s largest bank, which successfully implemented AI in fraud detection, reducing false positives by 60%.
  • Enhanced APIs. Banking operations are increasingly relying on application programming interfaces (APIs) to allow clients to track their money across many apps. For instance, for users to monitor several bank accounts, banks must grant authorization for third-party budgeting apps to use their APIs. AI makes APIs more powerful by automating monotonous operations and opening up new security measures.
  • More intelligent customer tools. Due to the emergence of generative AI, the banking and investment sectors can now use more advanced technologies to improve customer service. Artificial Intelligence-driven chatbots and virtual assistants have the potential to improve customer service by assisting clients in resolving minor issues themselves. Budgeting apps, which assist users in improving their financial management and increasing their savings, can also be powered by AI.
  • New markets and prospects. Companies exploring new markets employ AI in predictive analytics to gain a deeper understanding of their clientele. AI-powered predictive analytics can pinpoint new company and consumer growth opportunities and more accurately anticipate which clients are at risk of leaving. For instance, to determine whether a specific client is about to terminate their account, banks can examine their customers’ usage patterns, such as how frequently they check in or make deposits, and compare it with other data.
  • Embeddable banking. Powered by AI, embeddable banking is transforming the financial landscape by allowing banking services to be integrated seamlessly into various non-financial digital platforms. This innovation enables customers to access financial services conveniently through the digital interfaces they use daily. AI provides personalized insights, allowing banks to offer customized financial products on third-party platforms. Machine learning algorithms predict financial needs, suggesting relevant services like loans at the point of sale, enhancing the customer’s shopping experience. AI also streamlines credit assessments, enabling quick creditworthiness evaluations within these embedded services. The result is a frictionless, intuitive banking experience that boosts customer satisfaction and loyalty. Furthermore, embeddable banking expands market reach, opening up new demographics and opportunities for financial institutions. By embedding banking services into commonly used platforms, AI is making financial services more accessible and tailored than before.
  • Better credit card and credit scoring. Creditworthiness assessment is a vital banking service function that leads to more accurate credit scores. Banks must analyze large volumes of client data to decide whether to approve a credit increase or accept a credit card application, among other crucial credit decisions. Banks can quickly approve or reject credit cards, credit extensions, and other consumer requests with the use of AI algorithms and machine learning.

Top reasons banks use AIFigure 3. Top reasons banks use AI.

In essence, using AI in banking is a significant change that will simplify processes, strengthen security, and improve client interaction. As banks continue to leverage AI, they will be able to provide creative, secure, and efficient financial services in the future.

Challenges of AI in banking

While the integration of AI in banking has brought about numerous benefits, it also presents a unique set of challenges that the industry must navigate:

  • Prejudice resulting from model bias. In an effort to show transparency and accountability for their actions, banks are investing more money in environmental, social, and governance (ESG) projects. AI models may inherit some of the biases that affect people because they are trained on data that was created by humans. Banks must remove prejudice from their product marketing and creditworthiness assessments, which have historically disadvantaged specific demographics.
  • Difficulties in controlling the precision of the output. Controlling result correctness is difficult since AI models do not yet possess the ability to reason or “understand” their outputs. Instead, AI models create outputs by finding patterns in the data that is provided to them. As a result, the model cannot inform an employee when data is erroneous or inaccurate.
  • Operational legal uncertainty. Effective training of generative AI models hinges on the quality and relevance of the preexisting data sets they are trained on. The question of whether examining data that is freely accessible to the public, such as news articles and explanatory films, violates copyright is still open to debate. Using AI models that have been trained using bank-owned data, such as customer service records or its own proprietary research, is one method to get around this problem.
  • Cybersecurity. Although AI technology has applications in fraud prevention and compliance management, as we discussed before, it is not without concerns. Because AI models are particularly attractive targets for malevolent actors, integrating open AI tools and technologies into banking IT systems presents some security issues. Because of this, banks require a comprehensive strategy for AI governance that successfully strikes a balance between risk management and innovation.

To effectively tackle the challenges presented by AI in banking, it’s crucial to tailor AI solutions to the specific demands of the financial industry. A partner like Avenga, with a nuanced understanding of both technology and the financial sector, can help you effectively integrate cutting-edge AI models into banking services.

While AI presents a massive opportunity for the banking sector, it also brings forth a set of challenges that require strategic planning and collaboration with a proficient partner.

Uncover how Avenga crafted a cutting-edge automated loan management system for Prosper, enhancing loan processing efficiency and compliance and establishing a new paradigm for customer experience in financial services. Success story

Strategies for banks to successfully implement AI

In this section, we share practical advice from Avenga’s experts, underscored by a 2024 survey where more than 50 percent of financial industry experts indicated that AI played a crucial role in the success of their business. These insights are aimed at banks that are looking to effectively implement AI in their banking services:

  1. Establish AI governance. Effective AI governance ensures transparency, accountability, and ethical use of AI. Avenga collaborates with banks to define governance structures, establish data privacy protocols, and create oversight mechanisms. We customize governance frameworks to align with industry standards, regulatory requirements, and your organization’s unique needs. Our experts guide you through policy formulation, risk assessment, and compliance.
  2. Select impactful AI applications. Not all AI applications yield equal benefits. Avenga focuses on identifying high-impact use-cases that directly address business challenges. We conduct thorough assessments to pinpoint areas where AI can drive value – whether it’s optimizing loan approval processes, enhancing customer experience, or predicting marketing trends.
  3. Build a real AI ecosystem. Avenga emphasizes ecosystem thinking, connecting data pipelines, models, and business processes. We integrate AI seamlessly into existing workflows, fostering collaborations across departments. Our holistic approach ensures sustained success beyond individual projects.
  4. Adopt flexible cloud solutions. Cloud platforms offer scalability, cost-effectiveness, and agility. Avenga helps banks choose the right cloud provider and architecture. We assess your infrastructure needs, considering factors like data volume, security, and compliance. Our cloud experts design solutions that align with your AI project’s needs and growth trajectory.
  5. Evaluate pilot AI projects. Pilots validate AI concepts before full-scale deployment. Avenga emphasizes iterative learning and quick feedback loops. We guide you through pilot project design, data collection, and performance evaluation. Our focus is on actionable insights and continuous improvement.
  6. Develop an AI integration hub. Siloed AI models hinder efficiency. Avenga builds integration hubs that connect disparate systems, enabling seamless data flow. Our integration experts create robust middleware layers, ensuring smooth communication between AI components and legacy systems. The result is the enhanced operational efficiency.

These steps provide a framework for banks to strategically approach AI adoption, ensuring that the technology is not only implemented securely but also aligned with the bank’s growth and innovation goals.


Artificial intelligence is reshaping the banking industry, streamlining processes, and enhancing customer experiences. Avenga’s AI solutions are at the forefront of this transformation, offering practical and innovative solutions to financial services. For a partnership that not only meets the current demands but also anticipates the future of banking, reach out to Avenga. Together, we can turn the revolution of AI into your competitive advantage.

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