Fifty-seven percent of executives list risk and global compliance as their two largest barriers to success, and a mere six percent of board members feel their company is adequately prepared to manage risk. In today’s hyper-complex risk landscape, compliance is the single greatest threat to productivity and liquidity.
Even though noncompliance costs twice as much as building compliance frameworks, most organizations have difficulty integrating compliance into their day-to-day business model.
It’s not easy.
Even when you look at data privacy — one tiny fish in the compliance ocean — you’ll see an overwhelming number of guidelines. To date, there are over 110 sprawling bills dealing directly with data privacy. When you collide this tsunami of global requirements with local ordinances, state-wide mandates, and federal requirements, it’s easy to get lost in the madness.
The average business deals with a staggering amount of data and documents, which are difficult to track, hard to identify, and incredibly challenging to granularly tackle with policies. Worse yet, the pure scale of unstructured data coming out of communication apps (think email, Slack, Teams, internal portals, newsletters, etc.) creates a monsoon of confusion for data analysis and internal “policy police.”
How do your employees know which information is sensitive in today’s collaborative ecosystem? Answering this question is especially challenging when you look at the cross-border composition of the average enterprise.
A Glance at The Regulatory Landscape in 2020
To understand the scale of compliance, you must uncover the regulatory monsters hiding under beds across your organization. There are data privacy laws (e.g., GDPR, CCPA, LGPD, etc.), industry-specific requirements (e.g., RCPA, FCPA, Basel III, Solvency II, etc.), baseline compliance needs (e.g., OSHA, labor laws, etc.) and a wide variety of other laws converging on the average business.
So, is it surprising that 69 percent of execs don’t feel confident in the way they handle risk?
Things get even more complicated for massive, cross-border companies like financial institutions. Seventy-nine percent of financial institutions rank “enhancing the quality, availability, and timeliness of risk data” as their number one risk-related priority. In fact, it outweighs the need for better compliance architectures and investments. To put it simply, you can invest in a world of technology and innovate all you want, but unless you understand what data is sensitive, you can’t formulate a coherent game plan to tackle the risk associated with those endeavors.
But how do you discover risk-sensitive data and information in a world where everyone is communicating rapidly across languages and platforms? Already, the swarm of laws and regulatory requirements are overwhelming. Trying to apply them against a literal ocean of unstructured, language-driven data may seem impossible.
The Language Problem
The mere act of cross-border communication creates multiple risk vectors for your organization. SaaS-based communication apps create shadow IT issues, uncontrolled collaboration can violate NDAs, and the release of private data across digital channels plagued by language barriers opens threat vectors that are difficult to control, identify, and remediate.
To be clear, communication is the single greatest threat to risk and security. Slack channels and Microsoft Teams are filled with unstructured data. Already, that presents challenges to IT — who are often bogged down by a hyper-complex IT architecture with deep data lakes and confusing data frameworks spread across S3 buckets and SaaS apps.
How do you effectively apply policy to all this unstructured data? Better yet, how do you pour through this data to identify risk vectors?
As an example, do you have a way to quickly identify when an employee speaking another language accidentally posts private data on a messaging app? Do you have effective multilingual guidelines for policies and procedures? And can you instantly translate incoming communications for analysis against existing compliance solutions?
It’s difficult! But it gets worse. What happens when you must wrangle that communication data across multiple languages, regions, and tools — all at the same time?
The solution can be in a great machine translation solution, respectful of languages AND global compliance !