Artificial Intelligence and Its Regulatory Applications

Current artificial intelligence implementations, such as smart bots, or assistive secretaries make use of deep learning: a computing method that leverages Artificial Neural Networks (ANN). ANNs are grounded on the same principles in which a brain receives, sorts and processes information, allowing these networks to evolve and learn – just as a brain does.

A Compliment to Human Capabilities

A wide range of industries are turning to AI to both complement human work and replace redundant tasks. A great example of this is the neural-network based algorithms that diagnose medical conditions with more success than its human counterparts. In the finance sector, natural-language-processing (NLP), a technology that builds upon ANNs, has allowed companies to scour news sources, process articles and ultimately provide actionable data. In the automotive industry, machine learning has led to semi-autonomous cars with a lower crash and fatality rate than human-driven cars. These adoptions across various industries show the immense strength of the technology in specialized applications.

AI-based RegTech and its Efficiencies

Furthermore, the regulatory industry is adopting various technologies to combat the increase in regulations. For instance, the FDA has turned to AI to reduce backlog and increase application screening. This technology led to a decrease of 5,200 hours and over $500,000 a year.

Using the same neural-network-based NLP techniques, regulatory information can be analyzed and synthesized for actionable outcomes. RegASK is at the forefront of applying this technology to alleviate the regulatory obstacles FMCG and cosmetics companies face. The various services offered use NLP to decrease the time spent reviewing claims and ingredients limits, and to preemptively notify users of upcoming regulatory changes.

While the field of artificial intelligence has enabled efficiencies in many processes, it is still decades away from becoming “ultra-intelligent”. However, the current technology enables companies to reduce redundant tasks, allowing people to use their skills in a more applied and analytical manner. Quintessentially, RegASK is applying natural-language processing as a labor-aiding technology, thus decreasing backlog and alleviating the regulatory burdens that FMCG companies encounter.