Financial analytics is one of many tools that when integrated on a single platform, enables organizations like yours to identify, prevent, and respond to data security threats quickly. And let’s face it—with ongoing threats against data security, you need to leverage all the robust technologies available that make sense for your business.
By optimizing financial analytics and data security best practices, you can strengthen your security posture. You’ll also be able to better protect sensitive data, assess risk, and identify possible threats quickly. Here are some more benefits of supporting your data security strategy with financial analytics.
Boost data security
Applying financial analytics to data security processes delivers far-reaching benefits. For example, analytical insights help with all facets of data security, including protecting against threats, creating a detailed data security strategy, assessing risk, predicting security issues, and more.
Here are seven ways that financial analytics can support data security:
Monitor data access and user behavior
Data must be secure from both external and internal threats. Financial analytics can be expanded beyond providing insights into the financial well-being of the organization to also monitor who is accessing financial systems. This alerts you if there’s unauthorized access. You can also analyze user behaviors within financial systems. This helps you identify any unusual logins, any attempts to access data from unfamiliar accounts, downloads of sensitive data, or other issues that could indicate a security problem.
Automate analytics processes to alert stakeholders
Automating processes such as data pipelines and data analytics can accelerate insights and reduce the chances of human error. Fully automating data pipelines to bring financial and other data into a data warehouse or any other type of data management system lets you analyze fully integrated data. Financial analytics can identify patterns in the data or data usage—such as a spike in data downloads or data transfers outside the organization—that could point to potential security issues. Alerts can be automatically sent to stakeholders so they can take action.
Identify potential security weaknesses
Your organization is probably already performing risk assessments to identify and mitigate a range of possible security problems. You can take these assessments to the next level by analyzing data from any previous breaches or security incidents. Financial analysis of issues occurring in financial systems can help identify any weak points, allowing you to mitigate risk by enhancing security. This also helps ensure better end-to-end data protection.
Proactively predict and prevent fraud
Financial fraud, identity theft, and cybercrimes are becoming more common, more costly, and more sophisticated. Sensitive data that’s breached or even accidentally leaked can lead to significant issues. A comprehensive approach and advanced technologies are needed to identify and prevent data-related crimes. Financial and predictive analytics can identify trends, patterns, and anomalies that let you identify and even predict data security issues. The ability to anticipate problems is extremely helpful—the more time you have to prepare your systems, the more you can beef up your security to prevent current and emerging security threats.
Utilize compliance processes to safeguard data
Depending on your industry, you may have strict compliance requirements. Financial analytics helps you comply with various regulatory mandates and reporting. The analytics that identify non-compliance issues can also be applied to data security. Compliance processes offer a structured framework that ensures sensitive data is protected, which supports data security strategies. Likewise, compliance requirements may mandate a secure network infrastructure with firewalls, intrusion detection systems, and other security protocols that help keep data safe.
Understand risk to protect sensitive data
You will always have some degree of risk with your data. That risk may now be higher than in previous years due to remote or hybrid work environments that see more data being transmitted and shared to more locations. Data-driven risk management is needed to identify, assess, and reduce risk. Financial analytics supports risk management by delivering insights into the potential risks related to sensitive financial data and other information.
Data security and governance best practices
Data governance and data management lend themselves to keeping data secure. Financial analytics, along with other types of analysis, can improve governance, management, and security by offering insights into the levels of data security that you have in place. You can use these insights to determine if the proper levels of security are implemented or if additional measures are needed. Data governance best practices also support security policies by offering data access controls, managing data across its lifecycle, and identifying roles and responsibilities for data management and security.
Modernize your data security strategy
Making financial analytics part of your data security arsenal improves your ability to protect data and uncover threats. A comprehensive strategy that incorporates financial analytics offers data protection against unauthorized access and data misuse. Keeping large volumes of data secure for analytics and other uses requires a data platform that’s easy to use and delivers powerful insights you can trust. The Actian Data Platform does this and more by simplifying how you connect, manage, and analyze data, giving you trustworthy results. More than 10,000 customers around the world trust us with their data, and you can too.