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Can knowledge graphs help untangle the RegTech data management puzzle

Can knowledge graphs help untangle there gtech data management puzzle

Knowledge Graph-based Technology Enables Companies in the Financial Sector to Quickly and Efficiently Integrate and Analyze the Explosion of Disparate Data from Regulators

Over the past decade, the advance of digital innovation combined with the growing number of regulatory guidelines in all jurisdictions has sped up the rise of Regulatory Technology, or RegTech for short. Originally, its main application was to enhance regulatory processes in the Financial sector, but nowadays it is expanding more and more in to any regulated business. A good sign that this technology is steadily going mainstream is also the fact that more and more regulatory bodies are supporting RegTech development and implementation.

According to a September 2019 report from Juniper Research, the value of global spending on RegTech is expected to jump to more than US $127 billion by 2024, up from US$25 billion spent in 2019. Automation in Know Your Customer (KYC) processes and background checks are set to be some of the key drivers for the expected surge in RegTech expenditures, foresees Juniper Research.

Even despite the ongoing global economic and business challenges, posed by the COVID-19 pandemic, the overall investment in RegTech is still robust, Accenture said in a post in April 2020. Although the current situation has impacted venture capital funding and investments negatively, it has also raised operational and regulatory risks, compelling regulatory bodies to work on adding further rules and guidelines.

AI-based Technologies to the Rescue

In this constantly evolving regulatory landscape, more and more financial institutions are on the lookout for innovative technologies that can help them keep tabs on the new regulations continually coming through.

This is where AI-based technologies can enable financial services companies to quickly and efficiently integrate and analyze the large volumes of heterogeneous data coming from regulators.

“AI is ideally suited to regulatory space, as it can dynamically reduce false positive and false negative rates; leading to significant time, resource and ultimately cost savings for compliance monitoring processes,” Juniper Research experts say.

One such technology is the knowledgegraph–a dynamic and flexible collection of interlinked descriptions of real-world facts and concepts such as people, places and events. Knowledge graphs provide a powerful way to integrate diverse data from disparate sources and to further enrich this data via automatic reasoning. This makes the resulting knowledge much more than its constituent parts and helps reveal less obvious correlations for deeper insights.

Knowledge Graphs for Smart Compliance

With their scalable structure and expressive context awareness, knowledge graphs help RegTech make sense of the disparate and complex data, piling up daily from laws, rules, regulations and guidelines coming from various regulators in all applicable jurisdictions. By combining information from legislation and regulations available to the public with enterprise-specific policies and procedures, they provide a more structured and holistic picture of the regulatory landscape. This makes it easier to adopt newer more complex sets of rules as well as to act on these regulations within the set timeframes.

Another benefit is that knowledge graphs can describe regulatory information in a way that is based on the shared meaning of each concept throughout the financial institution. In this way, the legislative jargon of regulatory authorities is “translated” into the language of the company, based on the way it runs its internal processes. Now this terminology becomes machine-processable information that maps identical concepts in different sources and can be indexed for easier knowledge discovery and analytics. This enables businesses to adapt to the constant regulatory changes quickly and at a lower cost.

The Takeaway

By replacing the traditional time-consuming and costly regulatory processing with smart data integration of external and proprietary sources, organizations using KG-based RegTech save significant resources. They also find value in using these technologies to gain deeper insights, which improves their compliance with regulations and makes regular reporting a lot easier.

There are various solutions based on knowledge graphs, that help the financial services sector overcome the data challenge and obtain richer insights. In a nutshell, KG-based RegTech leads to minimizing risks and maximizing opportunities for boosting business performance and revenue.

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