Data risk management framework, assessment, and best practices

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“Working with Trava has been an extremely impactful decision for Encamp. It would have been next to impossible for us to create a robust, enterprise-ready security process and tech stack without their assistance, particularly on the accelerated timeline that we needed. For a growth startup, time is one of the most valuable assets. Trava made it possible for us to break into the enterprise space at least six months quicker than we could have by ourselves — the ROI was extremely clear.”

Luke Jacobs

CEO & Co-Founder of Encamp
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Data Risk Management

The internet has transformed the way many companies do business. Technology has made things easier. Digital technology has made it more efficient for businesses to store data, share data, and complete their daily business operations. At the same time, this places additional responsibility on businesses to make sure they take care of their data. Who hasn’t seen a headline or two about major data breaches that have taken place over the past several years? For example, Equifax suffered one of the biggest data breaches in history in 2017, placing the confidential data of millions of people at risk. For this reason, data risk management is critical.

If you’re left wondering, “What is data risk?,” Deloitte explains: Data risk is the exposure to loss of value or reputation caused by issues or limitations of an organization's ability to acquire, store, transform, move, and use its data assets. Businesses can assume many risks with data management, which is why it’s important for businesses to conduct risk assessment and employ data management practices on a regular basis. When it comes to database risk management, some of the most common missteps businesses make include:

  • Poor Data Governance: This represents the inability of an organization to ensure that its data maintains high quality throughout its lifecycle.
  • Data Mismanagement: This refers to a weak process for storing, acquiring, protecting, validating, and processing data on behalf of its users.
  • Poor Data Security: This issue arises in organizations having difficulty in protecting their digital data from unwanted access. This might include disgruntled employees, hackers, or other cyber criminals. Poor data security can lead to a major data breach. 

For business owners, it’s important to talk about data risk management and how organizations can protect their confidential information from harm. Data risk management is a controlled process. An organization follows this process when they acquire, store, and use their data at every step. The goal is to reduce data risk to as minimal of an issue as possible. All organizations should have a clear plan when it comes to data collection risk management so that they can protect not only their data but the confidential information of their business partners and clients as well.


Data Risk Management Framework

There are several important tasks that should be included in a data risk management framework. With an increasing number of data risks and controls, there is no single optimal model for every business. In reality, businesses need to adjust their plans and frameworks often in order to keep up with best practices and to incorporate new technology that can keep their data better protected.

One key step in building a data risk framework is to develop a data risk taxonomy. This is one of the most important tools in risk management data collection. Data risk taxonomy refers to the process of categorizing risk types. For example, when looking at data risk management, some threats come from hackers and criminals; however, natural disasters must also be considered as part of a data risk management strategy. By taking a closer look at these data risks, your company’s enterprise data risk management can become more effective.

In general, data risk management frameworks should include:

  • Identification and Assessment: The first step is to identify and categorize all of the possible risks that an organization might face when it comes to its data. This includes access control issues, vulnerability problems, potential cybersecurity threats, and natural disasters that could pose a threat to the business. 
  • Mitigation: What are some of the steps that the company can take to mitigate this data risk? Are there new devices that can be deployed? Are there new training measures that can be implemented? That should be answered as part of the data framework as well.
  • Reporting and Monitoring: If there is an issue with the data, to whom should it be reported? Is there a standard form that should be completed and submitted? Is the information technology department responsible for auditing data security on a regular basis? These are key questions that must be answered.
  • Governance: Next, it is important to divide up the responsibilities when it comes to data protection. For example, the IT department might be responsible for monitoring the network; however, employees are also going to play a role in protecting the data from harm by storing it properly.

Data Risk Assessment

Companies should carry out data risk assessments on a regular basis. For some companies, this could be monthly or even more often. A data risk assessment, a way for companies to take stock of the risks that threaten their data, is a crucial component of any data security plan. With a regular risk assessment, companies can pivot and respond appropriately to threats as they happen—and there’s less of a chance that cyber criminals will obtain confidential information. 

Every company should come up with their own custom data risk assessment that touches on the tools, workflows, and software of their employees and clients. If you’re looking for data risk assessment examples, the National Institute of Standards and Technology (NIST) offers a robust list of resources, while other cyber risk management companies like Trava offer vulnerability and data risk assessments.

According to NIST, steps that companies should take when building a data risk assessment template or a data risk assessment checklist include:

  • Define the scope of the company’s risk analysis based on current technology and infrastructure
  • Identify and define the risks and threats that are currently posed to the company’s data 
  • Assess the likelihood of each of these risks coming true 
  • Evaluate the quality of existing cybersecurity and data protection infrastructure 
  • Determine the appropriate responses they should take to each of these risks
  • Develop, test, and deploy plans for data risk management, in addition to providing ongoing monitoring and feedback of these systems

By completing a data risk assessment pre-screening questionnaire on a regular basis, along with a data risk assessment questionnaire, companies can ensure that they are prepared for just about anything.


Data Security Risks

The number of data security risks is nearly endless as technology and cyber criminals become more advanced. Only by making data risk management a top priority can businesses be prepared to respond appropriately. Some of the biggest threats include:

  • Phishing Attack: Without a doubt, this is one of the biggest data security risks. Phishing attacks are designed to target company employees, tricking them into surrendering their login credentials virtually. Then, hackers can log into the network and steal data. 
  • Ransomware: This is another one of the biggest data security risks today. Ransomware is a specific type of malware that is designed to encrypt all of the company's data, rendering it unusable. Then, the hackers will demand a ransom in exchange for releasing the data. The longer the company is down, the more money it will lose. According to Becker’s Hospital Review, the first known ransomware attack occurred in 1989 and targeted the healthcare industry, which remains a key target of ransomware attacks.
  • Distributed-Denial-of-Service (DDoS) Attack: This is an attack that is designed to completely overload the company's systems. By attacking the company network with a flood of service requests from disparate sources, the attacker renders the network unable to respond to any requests, which often takes down the network.
  • Man-in-the-Middle Attack: A man-in-the-middle attack is a serious threat. Data is often encrypted when it leaves one device and arrives at another device, but it might not be encrypted in between points A and B. A man-in-the-middle attack is designed to get in the middle of these data packets and intercept them, stealing vital data.

Data risk management has to be able to cope with all of these risks. Data risk analysis should include these threats so that companies can be prepared to deal with them appropriately.


Enterprise Risk Management

Data governance risk and controls are usually tailored to meet the individual needs of an organization, particularly for enterprise-level risk management. When looking at data governance and data governance risks, enterprise risk management is different in a number of ways. Some of the key differences include:

  • Types of Risks Considered: When it comes to enterprise data risk management, this is an approach that is integrated into every department in the company. It takes a closer look at how each of these risks relates to the daily operations of a business. Instead of looking at one, narrow area, enterprise risk management will look at financial risk, operational risk, and ethical risk faced by businesses.
  • Distributed Protection for All Departments: Enterprise risk management is also going to be distributed across a larger geographic area. Whereas small- and medium-sized businesses might be focused only on localized issues, enterprise risk management will seek to get all branches of the business on the same page so that they can act as one cohesive unit. This includes data risk management in financial services.
  • Performance Metrics: Finally, enterprise risk management is going to focus on results-based performance measurements across the entire organization. The goal is to minimize the adverse effects of not only data security but also missed opportunities and losses. This will maximize the opportunities that the business has for growth while minimizing residual uncertainty that might be present in the enterprise.

These are just a few of the biggest ways that enterprise risk management differs from traditional SMB data risk management. All parts of the enterprise must work together to effectively handle risk management.