Artificial Intelligence in Banking and Finance

February 3, 2023 Maitri Katti
Reading Time: 8 minutes

Introduction:

To keep up with the rate of shifting consumer needs, industries are embracing fresh techniques. As word gets out, banking is becoming more digital. There is a clear integration of robots, artificial intelligence, and other machine help into operational process flows. Today’s banking industry is constantly fighting to enhance assets and decrease liabilities. A fast-track plan is needed to provide systematic compliance management and operations. The banking and financial sectors heavily rely on artificial intelligence (AI) to provide dependable and inexpensive banking services. The market for AI in banking, which was valued at $3.88 billion in 2020, is anticipated to grow at a CAGR of 32.6% between 2021 and 2030, reaching $64.03 billion.

Big data is the industry standard, and every company is attempting to extract as much value as possible from unstructured data warehouses. Banking is already undergoing a revolution because of big data applications. Artificial intelligence is now here. Companies are not the only ones taking advantage of AI’s advantages in extracting and organizing the available data; the banking and finance industries are also stepping up to use this data to enhance client relationships.

The global pandemic and the rise of technology have both accelerated the banking industry’s evolution and raised customers’ expectations. There are now more arguments for a user interface that is more effective because of a significant move toward online platforms. Due to these contemporary technical advancements, artificial intelligence and machine learning are gaining momentum in banking and financial services, as banking institutions now see the value of automation for essential processes.

Approximately 85% of top-level industry decision-makers think AI in banking will add some meaning and advantages to their enterprise processes in the coming days. Keep reading below to learn more about the need for AI in banking, along with its existing obstacles and solutions.

Banks are increasingly utilizing artificial intelligence (AI) technology for a variety of objectives, such as enhancing customer service through the use of virtual assistants or using credit scoring to accurately assess a borrower’s risk. But one of the most significant uses of AI in the banking industry is the fight against fraud and money laundering.

AI is strengthening competitiveness of banks through:

  1. Enhanced customer experience: AI improves its knowledge of clients and their behavior based on prior interactions. By incorporating personalized features and easy interactions, this enables banks to modify their financial products and services in order to create real consumer engagement and forge lasting relationships with their clients.
  2. Cognitive process automation: Because of this capability, many information-intensive, expensive, and error-prone financial functions, like claims administration, can be automated. This guarantees ROI, lowers expenses, and provides speedy and accurate results.
  3. Realistic interactive interfaces: Chatbots analyze the text chat’s context and emotions to determine how best to respond. As a result of cumulative cost reductions, these cognitive machines help banks save millions of dollars in addition to saving time and enhancing efficiency.
  4. Robotic automation of processes: AI reviews and transforms processes by applying Robotic Process Automation (RPA). This enables automation of about 80% of repetitive work processes, allowing knowledge workers to dedicate their time in value-add operations that require high level of human intervention.

Examples of AI in Finance:

  1. Risk assessment: According to Towards Data Science, banks and applications are utilizing machine learning algorithms to not only identify a person’s loan eligibility but also to present customized solutions.
  2. Risk management: Risk reduction is a crucial, continuous concern in the banking business (and practically every other industry). According to Built In, machine learning may now assist professionals in using data to “pinpoint patterns, identify hazards, preserve personnel, and assure better knowledge for future planning.“
  3. Trading: Since artificial intelligence is used to analyze patterns within large data sets, it’s no surprise that it’s often used in trading. As Built In explains, AI-powered computers can sift through data faster than humans, which expedites the entire process and saves large chunks of time.
  4. Managing finances/personalized banking: Chatbots and virtual assistants have reduced (and in some cases eliminated) the need to wait on hold for a customer service agent on the phone. According to Towards Data Science, users can now check their balance, arrange payments, look into account activity, ask questions of a virtual assistant, and get tailored banking advice whenever it’s most convenient, owing to technology and AI.
  5. Reducing false positives and human error: Mistakes are made by people, and this unpleasant fact cannot be avoided.94% of polled IT professionals in the financial services sector expressed a lack of confidence in the ability of their staff, consultants, and partners to securely protect consumer data. Thankfully, artificial intelligence can reduce human error and false positives.
  6. Save Money: Every item on the list that was previously discussed can help boost sales. Instead of recruiting extra staff, you can free up people to take on new duties by automating processes. In addition, utilizing AI to help assess whether someone qualifies for a loan often entails finding those with good credit who won’t default. Virtual assistants and round-the-clock Chatbots improve customer support.
  7. Preventing cyber attacks: Artificial intelligence can help consumers feel more confident that banks and financial organizations will keep their money and personal information as safe and secure as possible. Up to 95% of cloud breaches are thought to be the result of human error. By analysing and identifying typical data patterns and trends, artificial intelligence can improve enterprise security by warning businesses of anomalies or odd behavior.
  8. Reducing the need for repetitive work/process automation: AI can automate repetitive mundane, time-consuming tasks, such as reviewing documents or pulling information from applications, which will free up employees to tackle other projects.
  9. Ability to execute tasks of any length: Artificial intelligence has the ability to scale, meaning that you can use this type of advanced technology for short- or long-term projects.
  10. Credit decisions: Towards Data Science explains that artificial intelligence can quickly and more accurately assess a potential customer based on a variety of factors, including Smartphone data (plus, machines aren’t biased).

Ethics of Banking and Finance Sector in AI:

Artificial intelligence does not come without some ethical challenges, especially when it comes to protecting your personal and financial information. The Fintech Times highlights three areas of concern when it comes to AI in the finance sector:

  1. Bias: AI failures can happen, and in many cases, it’s a problem with the algorithm. Here’s an example from The Fintech Times: “If an AI system calculating the creditworthiness of a customer is tasked to optimize profits, it could soon get into predatory behavior and look for people with low credit scores to sell subprime loans. This practice may be frowned upon by society and considered unethical, but the AI does not understand such nuances.
  2. Accountability: Who is responsible if artificial intelligence makes an incorrect decision? For example, who should be at fault if a self-driving car gets into an accident?
  3. Transparency: How and why do algorithms come to particular conclusions? It’s not always easy to tell.

Use Cases of AI in the Banking Sector:

In the banking industry, artificial intelligence makes banks more effective, reliable, helpful, and understanding. In this digital age, it is enhancing the competitive edge of modern banks. The expanding influence of AI in the banking sector reduces operational costs, enhances customer service, and automates processes.

  1. AI Chatbots: One of the major benefits of utilizing artificial intelligence in the banking industry is Chatbots. Bank using Arch abbots to assist clients in a variety of ways. One of the important applications of AI in the banking business is the use of Chatbots in the financial sector.AI Chatbots in banking are updating how companies offer their clients’ services.AI Chatbots in the banking sector can serve clients around the clock and provide thorough answers to their questions. Users receive a tailored experience from these Chatbots.
  2. AI Enhances Customer experience: AI financial apps are quite useful. The goal of AI-powered mobile banking apps for Android and iOS is to enhance client satisfaction and service level. Utilizing AI and machine learning in banking enables businesses to track user activity and provide more customized services to clients. Based on user search trends, intelligent mobile apps may monitor user behaviour and extract insightful information. This data would help service providers make tailored recommendations to customers
  3. Data Collection & Analysis: Automated data collection and analysis is one of the numerous advantages of AI in banking and finance. Processes for data collection and analysis can be carried out effectively by artificial intelligence in the banking industry. Massive data collections are processed by AI machines, which also uncover insightful information. With the help of this analysis, banks will be able to predict business and industry trends more easily.
  4. AI For Risk Management: One of the best uses of AI in banking is for risk management.It is one of the key benefits of smart banking services with AI support. For instance, risk-related duties for bankers include reviewing financial conditions, verifying documents, and approving loans. This can be intelligently handled by the use of AI and machine learning in banking. This task can be completed by AI and machine learning in banking with more accuracy and privacy.AI-based mobile banking applications simplify financial transactions and analyze the borrower’s banking information. Bankers could find it useful to assess the dangers of making loans to these people. Additionally, lenders can examine the borrower’s behavior using the AI-driven risk assessment process, which lowers the likelihood of fraud.

Conclusion:

Artificial Intelligence is slowly changing the way people think and act and it is taking our mind to the next level. Imagine a machine that has the ability to think, learn, create and form its own ideas and thoughts. With the benefits and potential of such platform, computer power has increased by massive amounts. It is obvious that artificial intelligence will have a significant impact on the financial services industry. Banks will reevaluate how they operate, what they offer, and how they communicate with both clients and staff. For an AI-enabled process and operational effectiveness, they will redesign their operating structures. A new AI application will help the bank grow by enhancing employee and customer experiences.

 

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Reading Time: 8 minutes

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