Securiti announces a $75M Series C Funding RoundView
In today's digital world, data is the lifeblood of any financial organization. It drives innovation, enables better decision-making, and creates value for the business. In financial services, organizations often wrestle with the challenge of protecting sensitive data while ensuring that it can be leveraged to drive innovation and business insights. The process of managing sensitive data holistically to achieve the best balance of usage and protection can be a daunting task, especially in a large organization. Valuable data may remain underutilized due to siloed management.
From creating a full inventory of data assets to meeting data obligations and enabling data consumers to innovate, the challenges are many. This blog post outlines the 6 key steps in creating value through unified data controls. By following these steps, financial organizations can meet their data obligations, foster innovation among data consumers and producers, and streamline their operations with minimal friction.
The first step of creating value with a unified data controls architecture is actually a three-part process:
To do that, administrators must gather and build a real-time catalog of all native and shadow assets, data, data types, and data locations. This effort typically relies on stitching together application monitoring, network monitoring, cloud and infrastructure engineering logs, or consulting confusing and overlapping asset lists by the line of business.
Once that full list is created, the data producers and stewards need to create an accurate assessment of all the sensitive data that needs to be protected and remediated. Today, this is often done through spreadsheets and informal declarations.
Locating all data and then establishing standard policies are critical components to unified data security, governance and privacy. Core capabilities, like dynamic data masking for specific user groups, help restrict unwanted sensitive data proliferation. Obtaining a comprehensive understanding of all corporate data assets, along with identifying and cataloging sensitive data, serves as the cornerstone for a robust security and data management framework within any financial organization's expansive data environment.
It is important for financial organizations to have a 360-degree view of:
Managing identity access across hundreds of data systems in most organizations results in millions of access scenarios with various permutations and combinations. To address this issue, organizations are re-evaluating all access controls through data transformation projects.
Manual processes are insufficient for financial organizations that require scalability; and therefore, automated insights that incorporate user and role access along with sensitive data awareness are necessary. By analyzing all role and permission settings, even across multiple systems, geographic regions, and clouds, and aligning them with data sensitivity, organizations can connect this information with real-world attributes such as user location, data location, and system, as well as data regulations.
It is essential for financial organizations to prioritize the sensitive data present in their environment to effectively manage limited resources and time across many lines of business. This can be achieved through a risk-based ranking that considers which data is most important (governance), what data is most critical to protect (security), and what regulations are tied to that data (privacy). By doing so, institutions can prioritize access controls and platform security for the most sensitive data.
Utilizing risk-scoring on data assets for remediation is a critical component in safeguarding sensitive data within financial organizations that have many lines of business and complex integrations. By prioritizing the most important data, financial institutions can ensure that their resources are used effectively to secure the environment. To manage and protect this crucial data, institutions should implement remediation steps that leverage workflows and data mapping, automating the process and keeping stakeholders informed.
A unified approach to categorizing and classifying sensitive data enables organizations to streamline efforts without compromising security, privacy, or innovation. To derive meaningful insights, financial organizations must be able to search and share all data, including sensitive data. Firms can achieve this by enhancing the metadata that describes the data in their enterprise.
Enhanced metadata can be added programmatically and includes key information such as who is the data steward, what line of business owns the data and the data’s original provenance and lineage. By making this data searchable by Subject Matter Experts (SMEs), organizations improve their ability to quickly and accurately find the data they need. Moreover, automated workflows should be utilized by SMEs to further enhance metadata in the data catalog, ensuring that business metadata is rich and always up to date.
Finding and cataloging all data provides rich business context to data scientists and business analysts so they can more easily create new models, queries and reports to drive innovation and new revenue opportunities. This same rich metadata can help privacy, security and governance teams better protect and manage enterprise data. By prioritizing metadata enhancement as a key component of a unified data controls strategy, financial organizations can gain a competitive edge by unlocking the full potential of their data.
In today's highly regulated financial landscape, transparent and efficient reporting about sensitive data is crucial for organizations to meet, and hopefully exceed, financial and internal regulatory requirements. Regulators and internal data standards teams want to know where all the data is and what, exactly, is the plan to manage it all. However, the increasing complexity of multi-cloud environments and the vast amounts of data in those environments make it impossible to do manually and in spreadsheets. Financial organizations must automate and standardize their reporting processes.
Siloed department's processes for responding to Matters Requiring Attention (MRAs) exacerbate the problem of managing regulator expectations. Silos cause confusing and inaccurate outcomes that damage the firm’s relationship with regulators. By implementing an automated reporting solution, financial organizations can demonstrate transparency and build trust with regulators. Continual reporting ensures that organizations remain compliant and well-prepared for future regulatory changes. Overall, an automated reporting process is vital for financial organizations looking to comply with government regulations and maintain the trust of their customers.
Data controls is an emerging field with many new technology offerings. It is easy to forget that financial organizations not only need to compete on data and meet regulatory requirements, but also ensure that their data management infrastructure and solutions are enterprise-grade.
One way to achieve this is by leveraging an API-driven and modular architecture. This allows it to be flexible at the enterprise scale. Any solution, to be enterprise-grade, must support a financial organization's move to a multi-cloud or hybrid cloud environment by including:
Securiti’s DataControls Cloud provides a holistic enterprise-grade solution to help financial organizations manage data, especially sensitive data, across their entire organization. This includes:
Securiti allows you to unleash the power of data by putting the appropriate controls in place to ensure that the data is always being managed responsibly.
At Securiti, our mission is to enable enterprises to safely harness the incredible power of data and the cloud by controlling the complex security, privacy and compliance risks.
Copyright © 2023 Securiti · Sitemap · XML Sitemap