Being a successful graduate of Belarusian State Economic University (BSEU), Maria has acquired competencies in economic and social studies. Given Maria’s previous research working experience, and desire to explore what's really shaping the future, the main research focus is placed on FinTech and Blockchain Technology.
Although banking and finance are usually slow technology adopters, both have to catch up with technological trends to survive. See what potential AI-powered tools have in the sphere and what obstacles get in the way of their wider adoption.
Long gone are the days when you had to wait in line or make an appointment to talk to a financially savvy consultant. Now you can have one in your pocket 24/7 for a fraction of the cost. Although most people are afraid of automation, it is not only inevitable but desirable. Humans are not able to make split-second decisions with the same accuracy as machines, and most specialists would not be happy with the pennies they would get from such transactions. The future of finance lies in AI.
Why Use AI-Powered Tools?
It’s only human to make errors, but it’s unacceptable from a money-handling perspective. AI systems have excellent accuracy, predictability and can ensure compliance without becoming tired or bored. A byproduct of them is even more data which can be used for training and calibration.
Furthermore, such systems generate significant cost cuts after the initial set-up of the system, which can be quite expensive. Yet, the 24/7 operating schedule, low maintenance cost and, in the case of AI, the possibility of self-improvement, can easily justify the investment.
Using robo-advisors brings scalability to the process. Once the initial set-up is in place, it only costs a fraction to add thousands of more users. It gives the adopting company a competitive edge. The same algorithm is replicable even in other situations, for example for detecting fraud risk for cards and prevent identity theft, which makes it very cost-effective.
For example, in the case of risk management, the AI looks for patterns in data, keeping in mind that people tend to have habits, like accessing from the same device, around the same time interval and usually from the same geographical area. If any of these variables is seen as an outlier, it will alert the user and ask for other verifications. The great gain for the bank is that it protects it from important loses and image damage. Even if the amounts are insured, the scandal following a security breach is more important.
Obstacles of Using Robo-Advisors
The primary challenge of AI systems is getting quality data to train them, because it’s a matter of garbage in, garbage out. Although all financial institutions have heaps of data going back a few years, these are not always ready to be used on even on a digital format, as compliance regulations required a lot of hard copies. These include information on clients, accounts, transactions, payments made and payments due, credit scores, default risk and more.
Even the data which is already in computers or servers are not entirely usable since it’s usually stuck in different isolated silos. To become a raw matter for AI training, it needs to be uploaded in the cloud, on a distributed file system, ready to be handled by Hadoop.
Not only getting the data online is a problem, next comes the quality. Of course, structured data is easy to handle, but it does not contain all the information a robo-advisor should offer like on the spot market variations or even panic-selling which could be detected easier.
Best Robo-Advisors so Far
The trend of offering robo-advisors is growing, and some institutions have already taken some important steps in this direction. Most are digital assistants or operate as chatbots replacing customer service assistants. Others deal with fraud prevention and work in the background. Some of the most interesting so far are:
- Wealthfront – investment advisor, offering some promotional incentives, but no large-balance discounts;
- FutureAdvisor – you can use this to invest your IRA, Roth or SEP, as long as it is over $10,000;
- Betterment – it comes with the hard to refuse offer of no minimum deposit and goal-oriented tools;
- Bank of America’s Erica – robo-advisor replacing customer service and personal finance consultants, available via voice and text for mobile banking;
- Smark Bank – talk to your robo advisor in natural language;
- Wealthsimple – if you care about socially responsible investing and if you want to choose companies which share your values;
- ICICI Bank – some employees’ worst nightmare it is a way of using AI to replace some back-office work, potentially putting some people out of their current jobs.
Where Is This All Heading to?
Although usually a slow technology adopter, banking and finance are catching up with technological trends. We can expect to see more robo advisors in different areas, from front-desk to back-office, from personal finances to high-frequency trading. This tendency is dictated by the new generations which are digital natives and are most comfortable with operating cloud-based apps instead of dealing with clerks.