Not Another Buzzword: Top Technology Terms You Need to Know

by Monitor Staff Vol. 48 No. 1 2021

Let’s face it, to the uninitiated, conversations about technology can sometimes sound like a long string of buzzwords. But understanding certain terms and implementing them will be vital to the continued success of equipment finance. With the help of our guest editors and several service providers, Monitor assembled a primer of essential technology terms.

Rita E. Garwood,
Editor in Chief,
Monitor

AI (Artificial Intelligence): The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making and translation between languages. Data-driven AI will accelerate the speed of online lending. Lenders benefit from algorithms to assess risk and borrowers can benefit from AI that matches them to the right lenders.

API (Application Program Interface): A set of functions and procedures allowing the creation of applications that access the features or data of an operating system, application or other service.

Automation: The process of having systems perform routine tasks automatically within given parameters. Robotic process automation (RPA) and intelligent automation (IA) are examples of supporting technology used to achieve the efficiency gains of automation.

Cloud Computing: Ubiquitous, convenient, on-demand access to a shared pool of configurable resources (networks, servers, storage, applications and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.

Cloud First: Solutions built natively on cloud technologies as opposed to those originating in non-cloud environments and just hosted on a cloud. Cloud first solutions automatically take advantage of the breadth of unique architectures, security approaches, technologies and elastic performance of a cloud environment and allow for easier upgrades over time.

Deep Learning: Deep learning is machine learning at a massive scale. Deep learning has been the primary driver of many of the most exciting advances in artificial intelligence. Deep learning models can be used to automate tasks that are impossible to do with hand-coded software, such as recognizing objects, “understanding” human languages, driving cars and flying drones. The advances that are being made to efficiently solve those problems are carrying over to help other industries, including equipment finance, to apply machine learning at scale.

Digital Agility: “Digital” means personalized and adaptable with rapidly configurable technology and availability on any device, anytime, anywhere; not just “it’s on the cloud” or “it’s viewable on a phone.” “Digital agility” is the ability to move quickly and easily by applying and leveraging digital enabling technologies to create new personalized experiences and new customer solutions.

Digital First: Approaching any new opportunity, or problem, with the assumption that the solution should be as digital as possible. Adopting digital first working practices will help to redress any bias that exists toward traditional channels and processes. Making the shift to digital first often requires changing the mindset of a company.

Digital Only: A digital-only business provides products and services exclusively through digital platforms, such as mobile, tablets and the internet. It offers basic services in a simplified manner with the help of electronic documentation, real-time data and automated processes.

Low-code/no-code: A new way to build business applications, generally on a platform such as Microsoft Dynamics or Appian or Zoho, with visual representation of processes instead of a coding language. Low-code is a way for developers to design applications quickly and with minimum hand-coding by dragging and dropping visual blocks of existing code into a workflow to create applications. No-code is the same thing but is made for business people who will visually use pre-defined functions to build simple business process “apps.” Low-code/no-code is significantly faster than building traditional software applications and often of higher quality.

Machine Learning: Algorithms and statistical models that find patterns in data and leverage them to take action. Machine learning can find data patterns quickly and automate many decisions that would be difficult to automate with traditional software approaches.

Platform: An integrated set of cloud-based business applications from a single (major) vendor that offers standard tools for sales, customer service, accounting, ERP and other advanced technology such as business intelligence, artificial intelligence and more. This could be from the likes of Microsoft, Google or Amazon. The benefit of a platform (as opposed to traditional single-application software from independent vendors) is that all these tools are pre-integrated, the infrastructure is managed automatically and advanced tools are available to build customer-specific customizations extremely quickly. Data is guaranteed to be resilient. Technology is updated daily. The latest tools are always just a click away.

Software-as-a-Service (SaaS): Gaining access to functionality through a cloud delivered application in which the technology vendor is responsible for the underlying IT infrastructure and application management.

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