AI and Financial Compliance: What is Possible When the Two Meet (David Benigson) PlatoBlockchain Data Intelligence. Vertical Search. Ai.

AI and Financial Compliance: What is Possible When the Two Meet (David Benigson)

The financial compliance world always seems to be perpetually speeding up. But with the last three years precipitating a digital transformation push like the world has never seen, the perpetually influx compliance industry has become even more hectic than
usual.

Financial businesses today simply do not function the way that they used to. And while the compliance field has done an admirable job of making incremental shifts to plug the gaps that inevitably open up as change comes to pass, the field has reached a watershed
moment in its approach to modernization, especially when it comes to risk.

The modern business world consists of a vast network of priorities and emerging challenges that simply can not be managed using traditional research methods and legwork alone. This is why more and more compliance teams are beginning to eye AI as a potential
solution.

With that in mind, here are a few reasons why AI is being adapted at a greater frequency throughout the industry and how it is helping to empower compliance professionals.

Network Expansion and Social Consumerism

From crypto to embargoes stemming from the Russia-Ukraine crisis, there is no shortage of disruptive forces that are shaping the financial compliance space today. Combine this with the fact that partner networks and supply chains continue to become more
intricate and diversified in the wake of the COVID-19 pandemic, and the compliance space has gone from unwieldy – at best – to virtually unmanageable. Moreover, beyond just the financial and operational impacts of falling afoul of regulation, any sort of ethical
misstep today comes with significantly higher reputational risks due to the prevailing rise of social consumerism. This confluence of factors has caused the compliance community to realize that they simply don’t have the tools they need to effectively sniff
out emerging threats to their business environment let alone snuff them out before they become full blown problems. With that, the compliance community has quietly begun to experiment more with emerging technology like AI, quantum computing and other sophisticated
data science so that they can get the visibility and forewarning that they need.

Proactivity Becomes a Must

Years ago simply saying that you had a technology support infrastructure in place was enough to keep regulators happy when it came to compliance. That dynamic has changed significantly though as technology has become more mainstream and being proactive vs.
reactive has gone from being more of a strong suggestion to an expectation among regulators. This has resulted in a broader shift among compliance teams to try and be more agile and forward-thinking. And simply put, despite their best efforts, compliance teams
simply cannot be as proactive as they need to be without technology – especially when the rest of the world is using automation and they are not. In addition, as reporting requirements become more stringent and exacting, having technology in place that can
provide the needed amount of transparency and accountability has become essential.

Data-Driven Decision-Making Becomes Institutionalized

Whether it is logistics or finance, data has become central to making business decisions today. And as other departments have become more data-centric and efficient, not only are compliance teams looking to get in on the act, but they are facing pressure
from leadership that is keen to replicate existing data success throughout their organizations. This has resulted in not just compliance teams becoming more data savvy, but also in whole new metrics driven approaches being built. For example, compliance departments
are now implementing a variety of metrics and analytics strategies to manage and bolster their success. This includes everything from using predictive modeling to detect anomalies and connect the dots between potential opportunities for fraud, to unlocking
opportunities that exist in unstructured data and non-traditional data sources like news articles to identify red flags early on.

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The financial compliance world is changing. However, just because it feels like space is in a period of operational revolutional, it doesn’t have to be overwhelming. By keeping these key considerations in mind, compliance teams can reduce the amount of adoption
headaches they face and build sustainable AI and data driven infrastructures for years to come.

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