Current trends in fintech and AI

Artificial intelligence (AI) in the fintech industry is not about replacing live employees with robots. Instead, it’s about using automation to carry out basic or routine tasks in order to let employees handle more complex issues. It’s a way of giving employees more responsibility and the chance to work closer with the customers who truly need live help. AI is also ensuring that each transaction is accurate and it’s making online transactions safer by automating regulatory compliance.

When basic customer tasks are automated, such as simplistic banking transactions like depositing money, checking account balances or cashing checks, employees can have the time and mental energy to handle high-value tasks and troubleshoot difficult problems. While online and mobile banking have been around for a while, fintech AI has taken self-service and automation further, helping customers in more advanced ways than before. Meanwhile, AI can handle back-end tasks for the employee, like updating data post-phone call; collect customer information mid-conversation; and collect, analyze and report on data.

Robotic Process Automation for Repeatable Tasks

Robotic Process Automation (RPA) is at the heart of fintech AI – it’s software that automates human processes. RPA utilizes the same processes a person would, but without any of the human inefficiencies. Even though the same tools and processes are used, RPA can accomplish the task much faster and without errors. The speed of RPA is only limited by how fast the tools it’s using are. RPA doesn’t get distracted or tired, and it never skips over a task because of a heavy workload.

Financial services use RPA for a number of simple and repetitive tasks, like entering customer data into a spreadsheet or CRM software, but the software has to be programmed first in order to take care of tasks in the right way for the specific business or department. This requires specialists who understand how RPA software works and also have a firm grasp on what the fintech company needs to accomplish. As goals and processes change, the software will have to be updated. When programmed correctly, the software improves efficiency without wasting any time.

Automation of Regulatory Functions

Financial companies that get on board with the latest technology, like self-service options, naturally collect an increasing amount of data. While this can deliver a better customer experience through customization — for example, by suggesting financial products the customer will like based on past purchases, as well as monitoring things like abandoned cart rates —  it’s also led to stronger regulations for keeping money and personal data secure. As technology advances, regulations have to change along with it.

Fintech companies have to follow numerous regulatory guidelines, which can cost billions of dollars every year. This can make it difficult for some fintech companies to even break into the industry. Regulatory tech, also called regtech, makes it less expensive and error-proof to follow regulatory guidelines. Regtech can handle tasks like compliance checks, risk management and regulatory reporting. Often, cloud-based software will also automatically update to keep up with the latest regulations.

Transactional Chatbots

One of the most common uses of AI is the chatbot. Transactional chatbots are used in fintech as well as several other industries. In the financial services industry, chatbots can be used to carry out simple banking transactions for customers. These chatbots aren’t simply following predetermined steps, though. They use natural language processing (NLP) to understand the true meaning of what the customer types or searches for. For example, a traditional chatbot may only be able to understand a straightforward, predetermined query like “check balance inquiry.” With NLP, though, the chatbot can understand more casual language like, “What’s my balance?” or “I want to see how much is in my account.”

Digital Advisors

Chatbots can move beyond carrying out simple transactional tasks to serving as robo-advisors or coaches for customers. They can be used by customers to make decisions about financial plans, savings, and spending habits. NLP is used here as well as with transactional automation, but there’s an extra layer of service: product recommendation.

The chatbot can recommend tools, products and services to the customer based on the customer-chatbot interaction. Additionally, customized notifications can be sent to the customer when it’s time for them to take action, like when insurance benefits are expiring, if they’re approaching a transaction limit, or when a check has been cashed.

As AI becomes smarter and more advanced, its applications in fintech will only grow. Instead of pushing fintech employees out of their jobs, though, this may open up new paths for growth. Employees will have time to dedicate to training and career advancement, and there will also be new ways for employees to work with AI to improve processes. The goal of AI is not to replace humans with robots; it’s to give customers a more efficient way of accomplishing routine tasks while also offering those same customers attentive, one-on-one support when it’s needed.

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