“Low-code solutions allow a single company to create hundreds of applications”

JAXenter: Where do low-code/no-code solutions fit into the future of business?

Alan Young: Low-code solutions allow a single company to create hundreds of applications to accomplish various tasks; even better, they enable non-programmers and, more likely, subject matter experts to create these applications. This helps speed up digital transformation efforts for organizations and makes them more agile to respond to competitive markets and changing regulations.

JAXenter: We often hear about the positives of low-code/no-code, but what are some of the downsides?

Alan Young: Today’s low-code markets have many different platforms and technologies, some are data-centric, and some are process-centric. Further, some solutions focus on helping non-technical users, and some focus on technical users; however, none currently achieve all of this. There are also some natural shortcomings of a low code application in terms of its enterprise scalability and readiness such as extensible security models that may need to tightly integrate with the rest of the enterprise. We continue to see companies increase their offerings and go into tangent markets; however, we are not there yet.

Depending on which solution an organization uses, it will have missing elements. As a result, some organizations use multiple technologies and platforms; this creates issues with governance and how to manage the technologies and platforms and the employees and how they use them.

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JAXenter: Looking at the current ecosystem of automation and workflows, what needs to change in order for businesses to become more modern?

Alan Young: Digital transformation is still the name of the game when it comes to making businesses more modern. Organizations need to modernize their legacy systems to compete in today’s markets and comply with ever-changing regulations. Low-code platforms that allow organizations to build applications and automate decisions, processes and more will be crucial.

These applications need to get better on two key fronts. First, they need to get better at capturing, configuring, processing and maintaining data. Second, they also need to improve using AI/ML to make and explain predictions that enhance their applications. In doing so, organizations will have a complete low-code strategy.

JAXenter: How is AI used in highly regulated industries? How can AI meet compliance standards?

Alan Young: AI is not used exceptionally well in highly regulated industries today because things are just getting going. However, AI is being used for various applications, such as government and financial fraud detection, lending, customer churn and loan default risk. In these applications, machine learning algorithms predict the likelihood of these events happening based on the data patterns and trends.

However, these AI predictions don’t tell you why a prediction occurred, nor does it tell you how to act upon those predictions. For example, in the use case of financial lending, a machine learning model doesn’t tell you why a person is a bad risk; it just recommends not lending.

With explainable AI, these predictions are not just made; they detail the weights of every contributing factor that went into the prediction so the end-user can make better judgments with full visibility of the why and full transparency. As a result, explainable AI can make lending and fraud detection practices fairer and even expand the company’s business.

JAXenter: What is decision automation? What are its use cases and how can it benefit both businesses and customers?

Alan Young: Decision automation allows users to write, manage and execute decision logic that powers businesses- without code. Decision automation is typically used in highly regulated industries, where the decision logic that powers a business often changes and is highly complex.

So, for example, the decision logic used to power a mortgage lending operation changes frequently based on current regulations and lending rates. As a result, businesses will need to update their logic to remain compliant and competitive with fellow lenders. Decision automation allows these businesses to update their logic without code in minutes rather than days or weeks.

Moreover, decision automation enables these lenders to execute billions of rules a day, allowing them to handle high volumes of loan applicants. Linking back to the low code question above, managing business logic outside a low code decision platform becomes a daunting and complex proposition for many low code platforms.

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JAXenter: Do you have any predictions for how automation will affect businesses in the next five to ten years?

Alan Young: Organizations will continue to automate more and more of their business. This will impact both business and the workforce. Companies will take on more and expand their business as more and more repetitive tasks are automated.

However, humans will still be needed. Except, instead of, for example, processing a healthcare claim manually, the employee will need to handle data errors and inconsistencies in automated claims. These errors will typically consist of minor issues such as the wrong healthcare code number being used for a procedure, where the employee must correct the error so that the claim can be automated and processed properly. Employees will be required to handle the tasks that require more intelligent thinking.