12 Banking Buzzwords You Need to Know In a Digital Financial World
If you're a banker, or you work in finance, then you've probably heard at least half of these buzzwords. But do you know what they mean? Learn the meanings of these common and not-so-common keywords that banking and finance professionals need to know.
In the alphabet soup of BI, AI, and SaaS, not to mention the more familiar HMDA, CRA, TILA and RESPA, you may be looking for a little more clarification on just what those acronyms mean!
As a banking or finance professional in a digital world, you should know these 12 tech-y buzzwords.
Let's jump right in! We're starting with 12, but as we discover more, this list will grow to include even more. We'll start with one of the most familiar:
1. Business Intelligence (BI)
Business Intelligence, sometimes shortened to BI, refers to analysis of business-related data to gain important insights. This may refer to strategies or technologies that help you and your company analyze quantitative and qualitative data about your business, and in most cases includes past, present, and even future views of business operations. The point of all of this strategic data analysis is to help make better decisions!
Most BI softwares have the same or similar components. TRUPOINT Analytics is a BI software, so we will use it to illustrate some of the key elements of a BI technology:
- Database: This is all the data used in the analysis. It can include many different data sources; in Analytics, this is private financial institution data and publicly available data from sources like the Census Bureau and the annual HMDA LAR.
- Portal: This is the interface through which users and administrators can access and analyze the data. As a TRUPOINT Analytics customer, your digital experience happens entirely within the portal.
- Dashboard(s) and/or Report(s): These are the tables, charts, maps, graphics, and reports that help you understand the story your data tells. A BI software doesn't need to be interactive, but TRUPOINT Analytics is. We tend to refer more to "dashboards" than "reports" - we feel that "reports" implies a static, paper analysis, while "dashboards" helps express the multi-dimensional and interactive nature of Analytics better.
- Users: Every BI software needs users, often a combination of internal and external users. All Analytics customers are users, but so is your Customer Success Team!
You may have heard us use the phrase "data discovery" in connection with BI - this refers to the act of analyzing data from multiple sources from multiple angle to discover more sophisticated insights.
In combining the census data with public and proprietary data sets in TRUPOINT Analytics, and then looking at it from many different perspectives (for Fair Lending, those perspectives include underwriting and pricing), we are helping you with data discovery. The dashboards and graphics you see in Analytics are designed to help with the data discovery process.
FinTech is a portmanteau that stands for Financial Technology. FinTech refers to a sector of the financial and technology industries that is focused on providing financial services through technology. It's a fast-growing industry, in North America particularly.
Today, FinTech can refer to any new financial technology, for anything from education to retail banking. It also includes innovations like cryptocurrency, which we will discuss in a little more detail later.
RegTech is another blended word, this time combining "regulatory" and "technology." RegTech refers to any technologies that help companies comply with regulations. It very frequently refers to software that helps financial companies comply with financial regulations, even though it doesn't necessarily have to refer to that.
Fair Lending, HMDA, CRA and Redlining Analytics are all examples of FinTech, but more specifically, RegTech software.
Note: We have also started hearing the phrase "BankTech," but usage is limited. In general, BankTech refers to technology used in banking. The practical meaning of this term is still evolving (i.e. does it refer to technologies used to facilitate banking by end-consumers? Does it refer to operational technologies used by traditional banks? Can non-traditional banks be considered BankTech?) We will keep an eye on that trend, and update this post as needed.
4. Cryptocurrency & Blockchain
This is another portmanteau of "cryptographic" and "currency." It's used to refer to digital currency that are secured and decentralized; that is, it doesn't have a central bank or anything like that. The way it is controlled is that every single data point and change in the digital ledgers have to be verified by every other member of the network - it requires an "absolute consensus" in the network.
The technology that enables this "absolute consensus" is called "blockchain." We talked about what blockchain could mean for banks in this post a few weeks ago.
"Neobank" is an term used to describe a new type of banking institution that is more common abroad, but might be emerging in the US. Neobanks are a type of "challenger" bank, that is a new type of financial institution that challenges the traditional banking market.
Neobanks are totally digital financial institutions that provide bank-licensed products through relationships with partner banking institutions, but don't themselves have a banking license.
One great example is Yolt, an app offered by ING Bank to UK customers. It allows users to view their financial information for all of their UK-based banks in one app, track spending, and transfer money.
We will be talking more about other types of challenger banks in the future, so stay tuned!
6. Artificial Intelligence (AI)
Artificial Intelligence (AI), sometimes called Machine Intelligence (MI), is defined by Stanford professor John McCarthy as the "science and engineering of making intelligent machines, especially intelligent computer programs." He subsequently defines "intelligence" as the computational part of the ability to achieve goals.
AI often refers to ability of machines to make decisions after "learning." It doesn't necessarily mean creating machines that can think, learn, or make decisions like humans, but it often does.
We also talked about what AI could mean for banking in that blog post we mentioned above (re-linked here).
IBM's Watson is a good example of an AI computer, but Cortana and Siri are both versions of AI that you may interact with in daily life.
SaaS is an acronym that stands for Software-as-a-Service. It refers to the act of providing a centrally hosted software or application via the internet as a service. Because they're online, they're available 24/7. Most SaaS tools are subscription-based, meaning that users pay monthly or annually for access to the service.
SaaS tools may be described as web-based or on-demand, so you may have heard those words before.
With a SaaS tool, you don't have any hardware or installation to manage, and the service provider handles things like security.
Microsoft Office 365 is a great example of a SaaS product.
TRUPOINT Analytics definitely qualifies as a SaaS tool. The fact that access to the platform is bundled with guided service qualifies it as the next acronym, too...
TES stands for Technology-Enabled Service. It refers to a type of product or company that leverages technology with service to provide value to customers. The success of the customer is closely related, if not intrinsic to, the success of the product or the company.
In essence, TES is focused on the delivery of software, and making it as human and helpful as possible.
9. Data Stewardship
Data Stewardship is the responsibility a company, product, or person has for the data quality and security in an organization. Data Stewardship is, in some ways, an emerging field, as companies hire dedicated Data Stewards.
For example, a bank has the responsibility to be a good steward of their customers' data, and TRUPOINT is responsible for being a good steward of financial institutions' data.
10. Location-Based Authorization
Location-based authorization is a type of security feature, primarily for software and applications, that controls access based on location.
As a financial institution, you may restrict account access, or have additional layers of security, if a user tries to access their account outside of their usual locations.
Datafication is the overall trend towards using data to make decisions, guide behavior, build strategy, and more. It also describes the movement toward quantification of behavior, desires, and trends in data. Your business may be in the process of datafication, as you move towards a more data-centric strategy.
In your personal life, you may also be "datafying." Do you use a FitBit or other wearable technology to determine if you're getting enough exercise? This is one common example of datafication.
If your financial institution is datafying actively, you may want to consider hiring a "Data Steward" to help you manage the process and ensure data quality, security, and accessibility throughout the organization.
12. Predictive Analytics
Predictive Analytics describes the field of analysis focused on using current and past data to estimate, or predict, the future state. It can be especially helpful in identifying opportunities and risk.
In banking, predictive analytics is already being used for credit risk assessment, fraud detection, among others.
Combined with AI, predictive analytics has the potential to create self-learning predictive analytics that constantly enhance the available predictions and understanding of your processes.
TRUPOINT Viewpoint: As a banking professional, it's important to stay aware of the emerging trends in the industry. Hopefully, spending a little time with these buzzwords will help you do just that!
If you have questions, or would like to learn more about any of the topics listed here, feel free to get in touch!