The cost of data breaches has never been higher. Globally, according to IBM, the average data breach costs its victim $3.92 million in lost business and cleanup costs — a number that’s increased by an eye-watering 12% over the last five years. In the United States, the number is higher still: the average company that’s hit by a data breach loses $8.2 million, making cyberattacks a major risk factor for even the biggest businesses.
And of course, getting hacked is only part of the problem. In the wake of the European Union’s General Data Protection Regulation and California’s California Consumer Privacy Act (CCPA), companies now face major costs relating to compliance, too. In fact, the GDPR leaves companies liable to fines of up to 4% of their annual revenues, while under the CCPA companies can be fined $7,500 per violation — and for companies dealing with large numbers of consumers and large amounts of data, it’s easy to rack up huge total fines.
To fend off cyberattacks and simultaneously comply with proliferating legal and regulatory frameworks, organizations are pouring ever-greater resources into their data security infrastructure. Large companies are spending $9 billion to adapt to GDPR requirements, for instance, while globally cybersecurity budgets last year totaled $124 billion — and those numbers are rising fast.
For many companies, this looks unsustainable. Worse still, with companies dealing with ever-increasing volumes of data, the cost of both security and compliance will inevitably skyrocket still further in coming years. At best, companies will spend huge sums to secure their data; at worst, they’ll spend that money only to get hacked or find themselves in breach of one or more regulatory rules. No matter what happens next for companies large and small, the result is the same: a major strain on the balance sheet.
Fortunately, automation reached maturity right before this issue became a stumbling point. With the rise of AI technologies, companies finally have a way to simultaneously make cybersecurity more efficient and more effective. In fact, according to Gartner’s 2019 Hype Cycle for Privacy report: “Security and risk management leaders need to include artificial intelligence applications for rapid, inclusive and consistent support for compliance insight, vast and continuous data discovery, subject’s rights management, etc.”
At Dathena, we believe that automated data privacy isn’t just possible — it’s already within reach. We have pioneered a suite of data-privacy solutions that aren’t just best-in-class — they’re reinventing our understanding of how data privacy works for large organizations. Using groundbreaking AI and machine-learning, we’ve created tools that are smart enough to independently scour massive data-sets for a host of issues related to privacy, compliance, and disaster prevention, and identify risks, vulnerabilities, and potential regulatory violations.
That’s making it far easier for companies to create records of processing activities, handle data subject requests, perform data protection impact assessments, and radically improve their data governance. And because we’ve automated this process, tasks that used to take 10,000 man-hours can now be completed in a single hour of automated work, making it possible for companies to keep pace with the vast volumes of data they’re now handling.
Dathena’s solutions bring enormous benefits for both your bottom line and your peace of mind. In the wake of new regulations, increasing consumer expectations, exploding data volumes, and determined hackers, data privacy looked like an admirable but impossible goal. Now, with the aid of AI, effective, compliant data privacy proves to be both more achievable and more affordable than anyone expected.
Learn why that matters now more than ever in Dathena’s newsletter, created with research and insights from Gartner: https://www.dathena.io/how-the-dpo-journey-drives-dathenas-data-privacy-framework.
Gartner Inc., Hype Cycle for Privacy, 2019, 11 July 2019, G00369460