There’s a lot going on in the FinTech space right now. We’ve synthesized a few of the technologies that are being used to make it all happen.
Also known as artificial intelligence (AI), machine learning has been around for decades, but has started to really seep into the financial services industry more recently.
“At first, AI may be deployed more intensely in back-end technology settings to power large-scale decisioning in lending, trading and financial analysis, but it could eventually be a technology that expands how everybody interacts with financial services firms.” – Taylor Davidson, Managing Director of Unstructured Ventures
One of the most obvious and popular applications of machine learning is synthesizing big data sets, drawing “conclusions” (connections, correlations, behavioral attributes, etc) and, in some cases, predicting future data sets. Additional application in algorithm building is a clear follow-on.
From there, predictions are being made that focus on the “human” side of machine learning… could it be used as a beefed up robo-advisor or customer service representative? Maybe. My “personal assistant” right now is AI-based, and she’s awesome. Of course she just schedules meetings for me at the moment, so we’ll see how this works for money management.
The popularity of python as a coding language in FinTech can be seen easily by the large numbers of industry job postings seeking python developers. An opensource stack programming language, it’s viewed as general-purpose, clear and concise (no frills, highly efficient), and great for solving quantitative problems.
“[Python is used] to perform our builds (through our own tools built on Scons) and also for prototyping, testing, deployment automation, in fact, lots of things. What’s nice about that is that there is no secret sauce for any part of the work we do, most developers can reach a high degree of comfort and familiarity with both the system itself as well as the ecosystem surrounding it.”
Near-field communication, or NFC, has large possible implications for the payments space. Earlier forms of mobile payments handled transactions using a scanning system (usually of a barcode). But with almost all new models of smartphones coming out with NFC built in (15 billion phones will be equipped with the technology this year), the possibilities to dominate are high.
NFC, a protocol that allows two devices to connect via radio communication when they come within about 4 inches of each other, has gained further legitimacy within FinTech because of the aggressive focus on security measures (we talked recently about trust issues that consumers have with mobile wallets). NFC can exchange any type of data (including personal information), and vulnerabilities in its security that compromise that data have been highlighted the past several years.
But, since the launch of Apple Pay, experts are stating that most other contactless payments options on the market right now “cannot touch mobile NFC in the security field.” It’s a bold statement, but telling of where this technology could go.
It’s an underlying protocol that’s most well known at the moment for powering the bitcoin network, and its strength lies in the decentralized mining network that verifies each transaction. We’ll save you the long explanation here, as we wrote all about blockchain last week.