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The rise of AI is to knowledge work what assembly lines were to manufacturing work. The usage of this technology across industries is radically reshaping how work is accomplished, turning knowledge work (in our case, extracting meaningful insights from oceans of regulatory text) into a computational output, rather than one of human purview.

Driverless cars have quickly worked their way into the public consciousness, and we think they’re a fascinating way to explain the core functions of Ascent’s RegulationAI™. While it may seem strange to compare RegTech to robot cars, it’s not a stretch. In fact, they are both analytics-driven AI whose primary goal is taking over tedious activity so that humans can redirect their time towards more – well, human efforts. But the similarities don’t end there.

Crafting a Digital Person

“Car companies make cars, and that’s what they should do. Self-driving companies should make drivers.” —John Krafcik, CEO, Waymo

Machine learning is all about adaptation and self-improvement. The end goal for any Knowledge-as-a-Service (KaaS) company is to efficaciously and efficiently take over mundane human tasks. Driverless car companies are, at their core, trying to create the perfect AI driver. Ascent, by comparison, is transforming the compliance officer’s mindset to be one that’s digital-first.

SaaS aims to make our lives easier by giving us adaptable tools that are scalable. KaaS is certainly scalable, but the goal isn’t only delivery of a unit of service; it’s both delivery of a unit of service and the creation of activity as a result of that unit. We’re creating a scalable, learning-driven, adaptable, and functional compliance officer, that works relentlessly and at above-human accuracy. Speaking of accuracy:

Accuracy is the Hinge

“Society expects autonomous vehicles to be held to a higher standard than human drivers.” —Professor Amnon Shashua, MobilEye Chief Executive Officer

Both driverless cars and Ascent rely on a risk tolerance that requires almost ~100% accuracy. Certainly, this is required for driverless cars — how many of us would step into a vehicle that is only 88% safe? There’s a common misconception that driverless cars merely need to be statistically more accurate than the populace on average, when, in reality, they need to be almost 100% accurate. We see this trend reflected in surveys regarding consumer concerns.

The same is the case for RegTech. Brokers, on average, have to comply with 12 different regulatory bodies, while major financial firms are looking at as many as a hundred. Of course, anything that deals in compliance requires accuracy to navigate through this trench of regulatory oversight, especially considering the fines, personal liability, and gap risks associated with compliance failures.

These accuracy liabilities are what breathe life into KaaS as an industry. The better your machine learning processes and the more accurately you can pinpoint raw data, the more accurate and self-adapting your AI becomes.

AI Doesn’t Replace Your People, It Empowers Them

“Artificial intelligence is the new electricity.” —Andrew Ng

Driverless cars will replace a human role. This complete overtaking of human responsibility is in stark contrast to what drives Ascent — both in technical and philosophical terms.

Ascent is meant to be deployed in the areas of your business where you need critical support. One of the major hurdles that that financial firms face is that most services simply act as data aggregators that still require compliance officers to manually input data and build their compliance programs.

Ascent dynamically changes this process by creating a regulatory channel that’s automatically filled with rich data that is transformed into useful “products” within minutes —these include a firm’s specific obligations converted into tasks, compliance reports, WSPs, and more. By automating the most tedious and error-prone aspects of compliance, we free up people to focus on the critically human parts of the job, like working with the lines of business and proactively defending the firm from risk.


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