Current Trends in FinTech Turn Focus to Integration and Verification
Technology is ever evolving, and currently, the pace is exceeding our ability to adapt to it. As changes come along, they’re implemented first and thought about second. While this attitude has served society acceptably for a time, cracks are beginning to show in the foundation. The recent (seemingly endless) data breaches are coming head-to-head with outdated financial practices. As privacy is threatened, the ability to collect and analyze increasingly larger sets of data is becoming the norm.
Finances are uniquely tied to a person’s identity not to mention the ability to thrive in modern society. Increasingly technological advances are forcing the financial sector to confront the upcoming trends in automation and data collection. As the industry adapts, it will be forced to reconcile its own interests with the need to maintain consumer privacy. In particular financial tech is poised to either elevate itself over the next decade, or to crash, burn, and lose the faith of the public. Let’s take a look at a few of the key trends playing out.
As with everything else, automation is creeping into the financial tech sector. There are already institutionalized fixtures in place — ATM stands for “automatic teller machine,” after all — but the next decade promises even greater advancements as artificial intelligence becomes more refined.
Currently, it’s more common to hear someone complaining about automated customer service than extolling its virtues. Systems as they are leave customers frustrated at not being understood, not being able to find the option they want, and not being able to reach a real person when they need to explain the nuances of their issue. With artificially intelligent systems, consumers will find that even more complicated requests can be distilled down to concise code, offering an experience more like talking to Alexa than pressing 3 to be transferred to billing.
Internet of Things
Having Alexa or some version of a smart home device is just the beginning of the network of the future. As the internet of things (IoT) comes into existence, anything with an on/off switch can be connected to a “consciousness” of devices. Not only will you be able to order Amazon items by asking Alexa, but your refrigerator will notice that you’re down to your last gallon of milk and place a grocery delivery order (along with your weekly vegetable staples) with the local grocer. Since your refrigerator is interfaced with your personal network, it’ll be set up to pay with your credit card of choice and log the transaction in your budget. Eventually, it may become as sophisticated as planning your weekly meals in an online tool, having your refrigerator inventory your stock, and placing an order for all your needed items. Good bye, days of manually making lists!
Putting bills on autopay may not seem revolutionary — after all, it’s common to have several fixed bills on autopay so you don’t have to worry about missing a payment. As convenient as this currently is, it’s poised to get a lot more so. As budgeting software learns more and starts to integrate with bank accounts and log transactions in real time, it’s going to be possible to set payment windows on categories and put nearly everything on autopay. Remember your fridge ordering the milk? Now you’ll be prompted if ordering more milk will put you over your budget for the month, as well as offering money from categories you chronically underspend in. As methods for keeping track of your cash flow become more proactively integrated, traditional bank accounts may become a thing of the past.
Machine Learning and Big Data
Since computers were capable of holding large data sets, technology has been helping the financial sector to make more informed choices. Now, as machine learning becomes more refined and elegant, the possible applications of data analysis are growing.
Historically, fraud prevention has relied on geographic cues and abnormally large purchases to detect sinister charge attempts. Now, with the power of machine learning behind fraud detection, programs can make more educated assertions about which transactions are legitimate based on your spending trends. You may even be alerted automatically when the bank is questioning one of your transactions, and you could stop fraudulent payments from processing in real time.
Computers have always aided in storing large data sets, particularly those related to investments and their financial outcomes. With the addition of machine learning, well-designed programs are able to detect long-term patterns in the data that humans can’t see, and make predictions based on current data and future extrapolation. However, though machine learning may be smart and ever evolving, this tool will still require management by trained financial analysts who can understand social needs, political climates, and relevant historical events that may explain trends cold data cannot. The human element of financial advising will likely never go away entirely; it will simply require more sophisticated and diversified training.
Having a larger, better incorporated data set surrounding a person’s credit history and financial portfolio will overhaul the way we assess loan viability. With more accounts linked together, as well as having a longer history of cash flow and debt repayment, traditional FICO credit scores will become a thing of the past. Instead, lenders may rely more heavily on debt-to-income ratio, spending habits, and cash flow models that have traditionally only been applied to businesses.
The biggest issue with all of the above is security. If your financial information is not only linked to your refrigerator, but held in multiple profiles that analyze your cash flow and debt ratios, the risk of breach are much larger. While there are ways to stay secure, the more points of entry there are, the more possibilities there are for malicious action.
Financial institutions are exploring biometric identification as an option to combat vulnerabilities. Technology is advancing and it’s becoming more realistic to have fingerprint identification or unique identifiers personally available. Currently, reliance on passwords, encryption, and multi-factor identification have all proven their ability to be manipulated. While no solution will be perfect, biologic factors take more creativity to circumvent and will increase security in the interim.
The Future of Financial Tech
Much of the future of financial technology is wrapped up in how quickly technical capabilities advance. The above applications stand poised to upend day-to-day processes that have been in place for decades. As society reacts and adapts to the changing world of finance, there will be a period of uncertain transition. Change is inevitable, and while the convenience on the horizon is mind-boggling, it must be approached with caution and sensibility to avoid compromising the privacy and stability of current financial practices.