Data privacy and security is one of the most important areas for companies to focus on as they digitize their customer-facing functions. According to research from Ponemon Institute, companies with mature data protection programs are more likely than their peers to have more satisfied customers and higher profits. The threat landscape has evolved dramatically since the introduction of GDPR in May 2018 and now includes new regulations that require organizations to protect privacy and personally identifiable information globally at all times by default. Organizations must also determine how much risk they’re willing to accept based on how much value is derived from using certain types of data for specific purposes like AI or machine learning applications.
The first thing to know: Data Risks now come in many shapes and forms
The risks facing today’s organizations are no longer limited to the operational realm. The C-Suite is facing a host of new challenges that have arisen from the rise of digital and cloud technologies, including changing customer expectations, the proliferation of cloud data centers and services, increased focus on AI to minimize business disruption and automate internal assessments.
In 2023, these risks will continue to grow in significance as organizations scramble to keep up with market demands for new services, products and solutions—with many falling short due to lack of attention paid towards Data Risk Management (DRM).
Data Risks are now a C-Suite Level Executive Challenge
This is why data risks have become a C-Suite level challenge for executives. To effectively manage these risks, C-Suite executives need to understand the risks their company faces and be able to make informed decisions about data risk management strategies. The need to understand data risks and what to do about them is increasing as more businesses realize that they have valuable data that needs protection against a variety of threats. Companies need to start proactively planning for all kinds of data risk in order to be prepared when they face them, which can help reduce the damage caused by an incident or security breach. Being prepared will allow companies to respond effectively when they face a data threat. That responsibility will always ultimately lie with the C-Suite, so what should executives be aware of heading into 2023?
More Changes in Regulatory Landscape in response to More Data Breaches
You may have heard that data protection laws are changing in different countries. The EU’s General Data Protection Regulation (GDPR) is a good example of this type of regulation, affecting all companies, regardless of size or location. These regulations expand the scope of data protection and require businesses to comply with them when they collect, store or process personal information about their customers or employees. This means not only must you make sure you are adhering to the rules wherever your business operates; but also that you are able to demonstrate compliance with applicable laws if requested by regulators.
As companies become more dependent on technology and their customers’ personal data grows exponentially in volume, there is a greater risk of cyberattack — and as cybercriminals become more sophisticated, so do their methods for hacking into these systems. The number of data breaches is rising year-on-year with 2022 becoming the worst year on record. Cyberattacks can have serious impacts on business operations as well as customer trust.
Changing Customer Expectations
Customers are demanding more transparency and control over their personal data. They want to be able to see what information is being collected about them, and they want a say in how it’s used—or not used. Businesses that can meet these needs will gain a competitive edge in 2023.
The shift to a more transparent and personal data-driven economy will create new challenges for businesses. For example, customers may stop using certain products that collect their data because of privacy concerns or for other reasons. Businesses will have to develop strategies that balance the benefits of collecting and using customer data with potential downsides such as losing customers.
Companies will have to make sure that their products meet customers’ privacy expectations. They may need to develop new data-management strategies or processes, and they may have to invest in new technologies and talent.
Proliferation of Cloud Data Centers and Services Presents Opportunities and Data Privacy Risks
As cloud data centers and services expand and become more accessible to organizations of all sizes, they present opportunities for the storage, processing, and analysis of data. However, these services also come with data privacy risks that should be considered before using them in your organization’s operations. Integrating large amounts of valuable data that may include sensitive information into central platforms provides a clear point of attack for cybercriminals. 2023 will almost certainly see an increase in breaches of cloud data services and stores deployed by enterprises. At the same time, there are steps that can be taken to help mitigate these risks.
The volume of data being generated by organizations is growing exponentially. In fact, according to IDC, the amount of digital data created will reach 163 zettabytes (ZB) in 2020, which is an increase of 32 ZB from 2018 levels. This presents huge opportunities for businesses who can leverage this data to become more efficient and competitive. But it also comes with the challenge of managing that data effectively.
In addition to the volume of data, there is also a growing need for companies to analyze and use that data in their operations. In fact, according to Statista, the global big data analytics market will grow from $42.3 billion in 2018 to $55.2 billion by 2022 at a compound annual growth rate (CAGR) of 6.82%. The ability to process and analyze data helps organizations gain insights into their customers, products and services that can be used for decision making.
This is why it’s important for businesses to have a data privacy and security framework in place to support their data integration strategy by minimizing the risk of data breaches. Data integration is the process of combining different types of data from various sources into one single source. This allows companies to analyze and use that data more effectively, as well as make better business decisions. One key way that leading companies are minimizing the risks associated with cloud data integrations is by leveraging technologies that can automate data privacy assessments and processes.
Increased Focus on AI to Minimize Business Disruption and Automate Internal Assessments
As AI becomes more sophisticated, it will be used to automate internal assessments and minimize business disruption. The goal of this automation is to minimize data risks that can occur during sensitive data transactions.
AI is already being used in many industries as an internal risk management tool. For example, AI provided by data platforms like Alex Solutions can be used to identify suspicious transactions or access requests and trigger an alert if there is a high probability that fraudulent activity has occurred. This technology also helps determine whether a company should approve or reject a request based on its likelihood for fraud or non-compliance with regulations and policies. Essentially, AI gives companies the ability to make decisions about whether certain activities are allowable based on their level of compliance with policies already established by the organization itself (such as strong passwords and access restrictions).
In addition to helping make decisions about individual data risk assessments, AI will also help determine which employees have access rights within an organization’s system architecture at any given point in time. Ideally, automation such as Alex Automated Cross-System Data Lineage can be leveraged to report compliance directly to regulators.
The future of data security is on its way, and it will be here before we know it. With the help of AI technology, companies can better manage their risk by using a variety of internal tools to identify potential threats and reduce the number or severity of breaches that occur. However, while AI can help companies better manage their risk of a data breach, it cannot solve the problem entirely. In order for organizations to effectively protect themselves from cybersecurity threats, they must also implement strong security measures on both an internal and external level.
As companies in every industry digitize their customer-facing functions and internal operations, managing data privacy and security becomes a strategic priority.
Data privacy and security has become a strategic priority for many companies as they move to digital and therefore more direct customer interactions and internal operations. Naturally, managing data privacy and security will continue to become a greater strategic priority.
The goal is to protect consumer data by implementing comprehensive policies across the enterprise that address both technical and operational requirements of data protection legislation such as GDPR (the General Data Protection Regulation) or CCPA (California Consumer Privacy Act). Companies need to ensure:
they’re aware of risks around sensitive information, including personally identifiable information (PII), credit card numbers and bank account details (PCI);
be able to demonstrate compliance with regulations like GDPR through strong governance procedures;
implement robust mechanisms for monitoring systems for indicators of compromise (IOCs);
have appropriate access controls in place;
encrypt sensitive data wherever it resides;
perform regular vulnerability scans against third party services being used with minimal impact on performance;
perform regular penetration tests against applications running in production environments;
audit logs regularly so issues can be identified quickly if they do occur before any harm is done;
train employees on how the company handles PII so there are no misunderstandings about what type of information can be accessed or shared internally among teams responsible for different parts of an organization’s infrastructure where consumers may interact directly with employees through call centers or websites using their personal information when making purchases.
In summary, consider these four steps to prevent costly data risks in 2023.
Create a data risk management framework. Data risk management is the cornerstone of any enterprise security program, and the first step to protecting it is creating a roadmap for your organization’s data risks. A data risk framework can be used to identify critical assets and prioritize methods for securing them. This includes creating a list of all relevant stakeholders who will have input into developing policies, procedures, and standards around how your company handles its customer data. It may seem basic, but a surprising amount of companies still rely on mostly informal data risk management processes.
Monitor and report on internal controls related to privacy impact assessments (PIA). In 2023, companies will be required to conduct PIAs in order to demonstrate compliance with GDPR and other requirements that are expected by regulators worldwide in order to avoid fines or reputational damage. To do this effectively requires an understanding of what makes sense when it comes time for conducting these assessments—and how much time they’ll take up in the future! Leveraging automative technology will be critical in creating sustainable compliance operations.
Understand which pieces of information pose greater risks than others based on their critical nature index scores (CRI). An effective way for firms large enough to not only develop but maintain compliance efforts with GDPR-style regulations moving forward would involve reviewing current practices related specifically towards protecting “critical” data elements within each business unit responsible for collecting such information through various channels.