Automation is the key to the future in many industries, finance being no different. For starters, it simply cuts costs. An Artificial Intelligence chatbot can work 24/7, 365 days a year, and it will never be slowed down by illness, fatigue, or family emergencies.
But efficiency and cost-effectiveness are not the only advantages of automation. Financial institutions are hoping technology will help them to detect and prevent fraud better – after all, the industry loses billions of dollars to fraudulent activities each year.
Read to find out how the world of finance is changing and what challenges lie ahead.
Battling Fraud with AI
Fraud is one of the biggest challenges that financial institutions face today. With the advent of Artificial Intelligence (AI), however, hope is finally on the horizon.
AI can be trained to develop an effective predictive analytics algorithm. What that means is that data scientists would label a high volume of transactions as fraudulent or legitimate, and then run this data through the machine learning model. This allows AI to recognize fraud and develop more sophisticated models as it learns more. AI then scans all transactions and ranks them on a scale of fraud-risk.
A system like that can be used to detect fraud across all channels: from native banking apps to multi-channel payment processing, such as eCommerce payments.
Improving Customer Experience
Nowadays, customers are used to instant gratification. Waiting longer than a couple of seconds is considered too long and expectations for customer experience are soaring. AI chatbots can help banks and financial institutions catch up with modern standards.
Chatbots have improved significantly in the last decade. In 2010, they were a simple digital tool that could pull answers for common queries but had to direct the customer to a human advisor for anything more complex. In 2019, they are a full-fledged digital assistant that can perform multiple tasks on its own and provide real-time insights on decision making. In other words, chatbots are now in a position to replace human advisors.
Meet Your Robo-Advisor
With AI technology so advanced, the potential reaches far beyond the chatbot box. Now customers can also hire their own Robo-advisor for investment services with little to no human supervision. Robo-advisors are capable of handling sophisticated tasks, such as tax-loss harvesting, investment selection, and retirement planning.
The Robo-advisor industry is seeing lightning-fast growth. Client assets managed by Robo-advisors were at $60 billion at year-end 2015. By 2020, they are projected to hit US$2 trillion and $7 trillion worldwide by 2025, showing a huge shift in wealth management.
The main selling point of Robo-advisors is, of course, the price. Most human financial planners charge a rate of 1% to 2% of the client’s total account balance, with potential for commission-based fees as well. Robo-advisors typically charge an annual flat fee of 0.2% to 0.5%. Clients also need significantly less capital to get started, with some Robo-advisors having no minimum assets threshold at all.
On the flip side, critics warn that Robo-advisors, advanced as they are, cannot provide the same level of sophisticated insights as a human financial planner. They might be better fitted as an entry-level tool for people with smaller resources and limited investment experience, especially given the lower cost of services. They are also ill-equipped to deal with extraordinary financial situations.
Challenges for Banking Automation
With robust technology behind it, the fintech revolution in banking and finance might seem unstoppable. In fact, however, those very technologies come with some serious limitations.
Using AI, for example, creates serious problems for compliance. That’s because AI is a black box technology – the algorithms that machine learning develops become more and more sophisticated with time until they are way too advanced for us to understand. Accounting for models and figures that AI supplies can be impossible. Naturally, this lack of transparency raises concerns both from the regulatory bodies and the customers.
And that’s not the only difficulty. AI can only be trained properly with a sufficient quantity and quality of data. Storing these quantities of data in-house is so costly and logistically challenging that banks will need to find new solutions to accomplish this task. Building a cloud computing infrastructure could be an answer, although it implies a significant investment as well.
Perhaps the most serious challenge facing technological disruption in finance today is cybersecurity. 71 percent of the world’s largest banks and asset management firms have said cybersecurity is the biggest risk associated with working with FinTech firms, according to a survey. Lack of sufficient security measures curbs the speed of technological transformation across the sector.
Stepping up cybersecurity in the finance sector is not as simple as educating customers to choose strong passwords or use a secure VPN for online banking. What the industry needs is an ever-evolving strategy, always ready for the latest challenge from cybercrime. Building foolproof security is a multi-million or perhaps even multi-billion effort.
The financial sector transformation is here. We already see it in improved mobile banking apps, seamlessly contactless payments, and novel security measures such as biometric locks. At the same time, the transformation is nowhere near complete. Banking automation can take customer experience and fraud detection to a whole other level. But first, it needs to fight some serious battles on cybersecurity and compliance fronts.