It would be an understatement to say that artificial intelligence (AI) and machine learning (ML) are transforming the world of finance. Although these technologies aren’t already innovations, the opportunities they are constantly unlocking drive the growing excitement. A few companies have deployed artificial intelligence in financial services, leaving a tremendous space for further innovation. While there are proven examples of successful implementations, many banks continue to consider AI only for experimentation, not moving forward with large-scale deployment. However, more investment in the area could bring successful outcomes for both banks and their customers.  

A recent survey conducted by Deloitte revealed that 86% of financial services AI adopters say that AI will be very or critically important to their business’s success in the next two years. AI can become the foundation of next-gen banking - more efficient, secure, and accessible.

Read also:

The Future of Banking (Part 1): Blockchain

The Future of Banking (Part 3): Robotic Process Automation

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AI enables the cognitive process automation of many information-intensive tasks and repeatable operations. It saves time, reduces costs, and ensures more accurate and faster data processing at each step of the banking experience. An excellent example of this is what JPMorgan Chase has implemented. While other financial companies were integrating AI into their communication with clients through the chatbots, JPMorgan made headlines with the bot COIN, which was never seen by customers. It analyzes the paperwork, legal documents, and contracts and does it at the level of accuracy and efficiency that the human is unlikely ever to achieve. The use of COIN has allowed JP Morgan to do in seconds what previously required 360,000 hours of annual work by lawyers and loan officers. 

Anti-money laundering

Anti-money laundering is another area where AI can be applied for greater effectiveness. With trillions of dollars moving via transactions a day and new laws coming into force to protect customer privacy, detecting anti-money laundering schemes becomes even more difficult. Despite that, banks do try to implement it as efficiently as possible with outdated rule-based software at hand. AI offers a significant improvement to the process, providing tools that exponentially grow, become more efficient, and learn from every experience. With its ability to process vast volumes of data, detect patterns and predict trends, AI can bring anti-money laundering programs to the next level.

Advanced security and fraud protection

Fraud protection is another area where AI can bring advancement. Current financial systems proactively respond to possible fraud threats, while there is most often no actual fraudulent activity. Completing money transactions in the new stores and locations when traveling causes a chain of fraud protection actions that sometimes feel excessive and can evoke customer dissatisfaction. At the same time, actual frauds aren’t sometimes detected timely because current financial software and protection algorithms are obsolete. AI can enable banks to deliver services using real-time customer data and insights. For clients, it means they receive recommendations of mixed services and solutions based on their real needs and financial activity before they approach the bank with these requests.

Enhanced customer experience

Like any other business, banks have limited resources and often can’t provide timely support to all their customers. Considering the overload of customer service departments, it might sometimes be difficult for human agents to provide an empathic and rapid response. It’s where cognitive AI chatbots come into action by assisting customers 24/7, leaving only the most complicated cases to be solved by bank employees. Using predictive analytics, AI can provide the clients with the right information at the right moment, even before they approach the bank to request it.

Effective decision-making

AI works using cognitive algorithms able to constantly learn, provide human-like responses, and personalized insights based on real-time data. They store a repository of expert information in a so-called knowledge database. Bank experts can later leverage these cognitive tools to make better-informed and more successful strategic decisions.

Risk management

Artificial intelligence can bring effectiveness and disruption into the process of underwriting for bank and automobile loans. With the help of AI, a commonly slow process will be made in minutes. It provides immediate assistance to lenders in assessing a credit risk portfolio by simultaneously analyzing thousands of data across different channels. It also allows tech-savvy financial companies to connect their products (e.g., loans, credit cards, etc.) to segmented risk profiles and suggest them to clients based on their data.

Reduced cost

Banks and financial institutions using AI can reduce the cost of service delivery by involving less human effort in the process. This approach provides multiple advantages for the financial industry and its customers, such as a higher speed of customer operations and a more efficient banking workflow with minimum human participation. Combining human and machine efforts, banks can offer a lower cost of financial services than traditional models.

Democratizing banking

AI-powered fintech empowers both customers and financial businesses by redistributing the monopoly of banks. It allows customers to access more personalized financial services and provides them with more efficient tools to manage their money at drastically lower overhead costs for businesses.

The future of AI banking doesn’t mean replacing bankers with data scientists but their collaboration on creating more accessible, inclusive, and efficient personal finance management tools. At Hennii, we believe that this cooperation can bring fruitful results to the financial sector benefiting all - customers with a better experience, banks with better ROIs, and tech innovators with opportunities to prove and implement their ideas. Developing a financial assistant based on conversational AI, we are going to make our contribution to a better financial future for everyone.

AI Use Cases in Banking
Infographics by Hennii


Read also:

The Future of Banking (Part 1): Blockchain

The Future of Banking (Part 3): Robotic Process Automation