Emerging digital technologies are redefining industries and changing the way businesses function. From electronic trading platforms to medical diagnosis, robotic control – Artificial Intelligence (AI) and digital disruption have touched every industry function. Each industry is assessing options and adopting ways to create value in the technology-driven world, and the banking sector is not an exception. The introduction of artificial intelligence (AI) has considerably revolutionized the banking industry. With the advent of mobile technology, huge data availability, quick processing needs and proliferation of open-source software -the concept of Artificial Intelligence has gained huge significance within the banking industry. The need for massive data storage capacity and super fast data transmission has led banking companies to hire data processing services, which help convert all critical documents into digital format for better work efficiency.
Lately, the banking sector has been exploring and implementing the technology of AI in smart ways. Right from assisting people in performing daily tasks to giving them a personalized experience, virtual assistants and chatbots have many applications and have revolutionized customer services and business communication to a great extent. One of the initial steps was taken in the year 2015 by Ally Bank (United States) by introducing – Ally Assist – a Chatbot that could easily respond to voice and text, make payments on behalf of the customer, give an account summary, monitor savings and spending patterns, and use natural language processing to understand and address customer queries.
Reports suggest that the Artificial Intelligence (AI) will save the banking industry roughly $1 trillion by the end of 2030. According to a joint research conducted by the National Business Research Institute and Narrative Science (in their 2018 report), about 32% of the participating banks are already incorporating AI technologies like predictive analytics, recommendation engines, voice recognition, and response times in their processes. It is estimated that banks with more than $100 billion in assets are 75% more likely to already be using AI when compared to 34% for those with less than $100 billion in assets. Front-end operations of artificial intelligence focus on direct interaction with clients and include digital wallets, applications and payment interfaces chat bots, or interactive voice response systems. Back-end operations on the other hand, involve the systematic processing of large chunks of data, fraudulent transaction analysis, and report generation.
How AI Is Revolutionizing the Banking Industry
People may doubt why AI is so appealing, especially to the banking industry and what makes it so much better than human intelligence. The reason is quite simple. The concept of artificial intelligence is the future of banking as it brings the power of advanced data analytics to combat fraudulent transactions and improve compliance. AI simplifies the process and automates task management. It also enables banks to manage huge volumes of data at record speed and derive valuable insights from it. Features such as AI bots, digital payment advisers and biometric fraud detection mechanisms facilitate higher quality services to a wider customer base. All this translates to increased revenue, reduced costs and boost in profits.
Here are a few ways in which AI is revolutionizing the banking industry –
- Fraud detection and prevention – With the introduction of mobile banking apps, banks are under increasing pressure to protect consumer data and assets from security threats. Using AI in mobile banking applications, you can detect fraudulent transactions (based on a set of pre-defined rules) and suspicious activities (based on the transaction history and behavior of individual customers). Through AI, blocking a fraudulent wire transfer, verifying foreign exchange, or approving a credit card transaction can be done within seconds. For instance, if a transaction of a huge amount is initiated from a bank account that has a history of minimal amount transactions or logins, AI can immediately hold back the transaction until it is verified by a human. Based on the data fed and the results learned from past actions, the AI-based software can perform such analysis in real time.
- Enhanced customer engagement –AI can be used to derive a better understanding of customers and their spending patterns, which would help banks to customize their financial products by adding personalized features and intuitive interactions thereby building strong customer relationships. According to a survey by Thomson Reuters – about 92% of firms estimated that current Know Your Customer (KYC) on boarding processes cost roughly around $28.5 million each year. With the use of new technologies like machine learning and conversational AI, customers are able to gain quicker access to the information they needed, without the need to visit the branch. In fact, according to McKinsey – for every one-point increase in customer on-boarding satisfaction on a ten-point Net Promoter Score (NPS) scale, there is a 3% increase in customer revenue. For banks, that may lead to an additional $15 million per year in profit.
- Improve decision-making and handle risk management – Risk assessment while giving loans and taking credit decisions is a complex process that requires both accuracy and confidentiality. Artificial intelligence can simplify this process by analyzing relevant data of the prospective borrower. It can combine and analyze the data related to the latest transactions, market trends, and the most recent financial activities to identify the potential risks in giving the loan. AI-based loan decision systems and machine learning algorithms can look at behaviors and repayment patterns to determine if a customer (with limited credit history) can make a good credit customer. It can also locate customers whose patterns might increase the likelihood of default. However, the possible challenge with using AI-based systems (for loan and credit decisions) is that they can suffer from bias-related issues similar to their human counterparts. This is due to the way in which loan decision-making AI models are trained. For that reason, banks planning to use machine learning need to factor in bias and ethics into their AI training processes to avoid these potential issues. This is particularly important in cases when using AI algorithms, such as deep learning approaches, that are inherently unexplainable.
- Use of Chatbots – AI in banking uses conversational assistants, or chatbots and other interactive voice response systems (which utilize Natural Language Processing) nowadays to increase the efficiency of services and to engage customers 24/7. A recent survey by LivePerson indicates that 67% of customers prefer interacting with chatbots that provide customer support, due to their fast and efficient problem-settling capability. Customers can avail the service from the comfort of their homes without having to visit branches. Chatbots handle many things regarding bank transactions, bank services and other tasks that don’t necessarily require human intervention.
For instance, the Bank of America introduced Erica – a virtual assistant to help with customer transactions – and that has shown significant improvement in their return on investment. In addition to fielding customer service inquiries and conversations about individual transactions, banks can use chatbots to make their customers aware of additional services and loan offerings.
- Cost effectiveness – By investing in AI, banks can effectively reduce the costs of hiring offshore or onshore employees, and also ensure excellent customer service. This makes the whole process more cost-effective as it can meet the rising demand for maintaining lean operations while delivering an exceptional experience to customers at a lower cost. For instance, adopting digital “Know Your Customer (KYC) can reduce turnaround time by up to 90%, reducing on-boarding costs by up to 70%. For many banks, these figures count to millions of dollars every year that could be rightly invested back into their innovation budgets.
- Robotic automation of processes – AI reviews transform processes by applying Robotic Process Automation (RPA). This feature enables automation of about 80% of repetitive work processes, allowing knowledge workforce to dedicate their time to value-added operations that require high level of human intervention.
Artificial intelligence (AI) can be considered one of the cutting-edge technologies that has the potential to bring revolutionary changes in the banking industry. AI can offer exceptional opportunities to accelerate numerous business processes and exclude time-consuming manual work. Error-free data entry services along with AI can streamline accounting, efficiently gather and consolidate data, significantly reduce the expenses from different business branches, enhance customer experience, and substantially reduce cyber fraud.
