Securiti+Veeam Will Accelerate Safe Enterprise Al at Scale

View

Unlocking the Power of Financial Services Data: How Access Controls Enable Innovation

Listen to the content

Data plays a crucial role in the financial services industry, whether it's consumer-facing or commercial. It enables organizations to drive business insight and profitability through numerous activities such as cross selling, up-selling, new customer acquisition, and customer retention. As a result, the amount of data being collected in various data systems, including cloud data lakes and warehouses, is growing at an unprecedented pace. However, scattered throughout this data landscape is sensitive and personal information that must be carefully managed.

Most data security teams in financial services organizations wrestle with the challenge of protecting sensitive data while ensuring that it can be leveraged to drive innovation and business insights. It would be much simpler to keep the data safe by locking it down,  but that inhibits business opportunities and revenue through strategic use of that data. Yet if the data is too accessible, it leaves financial organizations vulnerable to sensitive data exposure, ransomware attacks, and regulatory censure. Putting the right controls in place to protect your data enables organizations to drive maximum value while limiting risk.

A key component to achieving this balance is having a complete understanding of what sensitive data exists, where it is located, who has access, and how to build guardrails to enforce data protection and regulatory compliance.

360 Degree View of Sensitive Data Access

One of the key challenges financial organizations face is the lack of visibility into the sensitive data contained within their vast number of systems and repositories and who can access that sensitive data. These organizations can have hundreds of data systems where identity access is managed, leading to millions of permutations and combinations of access scenarios. To effectively leverage access management tools, there is a need to understand the underlying sensitive data that a role or user has access to as well as the policies that control those permissions. Sensitive data intelligence paired with identity access management enables financial organizations to get a true 360-degree view of user and role access to sensitive data, including:

  • What systems contain sensitive data
  • What sensitive data exists within these systems
  • What users and roles have access to this sensitive data
  • Where geographically the data is located
  • What regulations apply to this data

Financial organizations need a solution that can provide automated insight into user and role access to data systems paired with sensitive data intelligence for those systems. This holistic view enables companies to create an accurate mapping of who has access to what sensitive data and provide best practice recommendations to strengthen security posture and adhere to compliance requirements.

Enabling Automated, Secure Data Sharing In Finance

The finance industry is striving for digital transformation, and looking to enable maximum use of data within corporate enterprises.  One of the key initiatives in finance, as part of digital transformation, is enabling data sharing both internally and externally with business partners to increase revenue, maximize margin, and drive business value. Gartner highlights that “Data and analytics leaders who share data externally generate three times more measurable economic benefit than those who do not.”

Though sharing data internally and externally can have huge financial benefits, privacy regulations and risk of breach make cybersecurity leaders extremely hesitant to share data that may include sensitive information. For example, if a user has not provided consent for their data to be used by a third party, companies must ensure that the user’s personal information is obfuscated. A key way to share data while protecting sensitive information is through data masking. This enables organizations to change the values of the sensitive data while using the same format. The goal is to create a version of data that users, such as data scientist, business and marketing analysts, can still get business value from while ensuring no risk of exposing personal or sensitive information contained within.

Sounds great, doesn’t it?

However, often the task of masking sensitive data is an arduous, manual process. Most financial companies are faced with the difficult and time consuming tasks of identifying specific sensitive data that should be masked,  then applying  masking at scale to specific columns,  across hundreds of thousands of tables. In today’s rapidly changing, multi-cloud environments, this process is not practical.

Organizations should look for a solution that automates data masking by:

  1. Automatically identify sensitive data within the enterprise
  2. Automatically tag sensitive data with metadata that indicates its type of sensitivity (i.e. SSN, DOB, PHI, etc.)
  3. Create policies that automatically mask sensitive data across broad data sets and repositories, integrating with native system capabilities as appropriate
  4. Dynamically mask data for specific users or roles, based on tags and labels on sensitive data

Put Access Guardrails Around Sensitive Data

Most financial organizations have limited ability to granularly control access to sensitive data, especially with today's rapidly evolving cloud environments. While identity access management systems help control access to various data systems, they do not have visibility into what sensitive data is inside these systems. In addition, controlling access to data is an extremely difficult, time consuming and error prone process. This makes it challenging for the financial industry as a whole, that increasingly has to deal with various regulations that govern what types of data can be accessed from what geographies by what types of users. Often organizations find that they have inadvertently allowed access too broadly.

So how do organizations strike the balance of protecting their most sensitive data while also not inhibiting the innovative use of it?  To effectively control access to an organization’s data, it must have policies in place that surgically restrict user access to sensitive content to align with various regulations and requirements, while continuing to enable broad access as appropriate to enable productivity. With this approach, organizations can effectively put in place guardrails around sensitive data without impeding on its ability to drive revenue and business innovation.

How Can Securiti Help?

Securiti’s Data Access Intelligence and Governance solution provides a holistic solution to help financial organizations manage access to sensitive data. This includes:

  • Establishing sensitive data intelligence across your data landscape
  • Gaining granular insights into which users and roles have access to sensitive data
  • Discovering the geographic location of data and the appropriate regulations that apply
  • Dynamically masking sensitive data based on a wide range of criteria
  • Enforcing policies to selectively restrict access to sensitive data

Securiti allows you to unleash the power of data by putting the appropriate surgical controls in place to ensure that the data is always being managed responsibly.

Analyze this article with AI

Prompts open in third-party AI tools.
Join Our Newsletter

Get all the latest information, law updates and more delivered to your inbox


Share

More Stories that May Interest You
Videos
View More
Mitigating OWASP Top 10 for LLM Applications 2025
Generative AI (GenAI) has transformed how enterprises operate, scale, and grow. There’s an AI application for every purpose, from increasing employee productivity to streamlining...
View More
Top 6 DSPM Use Cases
With the advent of Generative AI (GenAI), data has become more dynamic. New data is generated faster than ever, transmitted to various systems, applications,...
View More
Colorado Privacy Act (CPA)
What is the Colorado Privacy Act? The CPA is a comprehensive privacy law signed on July 7, 2021. It established new standards for personal...
View More
Securiti for Copilot in SaaS
Accelerate Copilot Adoption Securely & Confidently Organizations are eager to adopt Microsoft 365 Copilot for increased productivity and efficiency. However, security concerns like data...
View More
Top 10 Considerations for Safely Using Unstructured Data with GenAI
A staggering 90% of an organization's data is unstructured. This data is rapidly being used to fuel GenAI applications like chatbots and AI search....
View More
Gencore AI: Building Safe, Enterprise-grade AI Systems in Minutes
As enterprises adopt generative AI, data and AI teams face numerous hurdles: securely connecting unstructured and structured data sources, maintaining proper controls and governance,...
View More
Navigating CPRA: Key Insights for Businesses
What is CPRA? The California Privacy Rights Act (CPRA) is California's state legislation aimed at protecting residents' digital privacy. It became effective on January...
View More
Navigating the Shift: Transitioning to PCI DSS v4.0
What is PCI DSS? PCI DSS (Payment Card Industry Data Security Standard) is a set of security standards to ensure safe processing, storage, and...
View More
Securing Data+AI : Playbook for Trust, Risk, and Security Management (TRiSM)
AI's growing security risks have 48% of global CISOs alarmed. Join this keynote to learn about a practical playbook for enabling AI Trust, Risk,...
AWS Startup Showcase Cybersecurity Governance With Generative AI View More
AWS Startup Showcase Cybersecurity Governance With Generative AI
Balancing Innovation and Governance with Generative AI Generative AI has the potential to disrupt all aspects of business, with powerful new capabilities. However, with...

Spotlight Talks

Spotlight 50:52
From Data to Deployment: Safeguarding Enterprise AI with Security and Governance
Watch Now View
Spotlight 11:29
Not Hype — Dye & Durham’s Analytics Head Shows What AI at Work Really Looks Like
Not Hype — Dye & Durham’s Analytics Head Shows What AI at Work Really Looks Like
Watch Now View
Spotlight 11:18
Rewiring Real Estate Finance — How Walker & Dunlop Is Giving Its $135B Portfolio a Data-First Refresh
Watch Now View
Spotlight 13:38
Accelerating Miracles — How Sanofi is Embedding AI to Significantly Reduce Drug Development Timelines
Sanofi Thumbnail
Watch Now View
Spotlight 10:35
There’s Been a Material Shift in the Data Center of Gravity
Watch Now View
Spotlight 14:21
AI Governance Is Much More than Technology Risk Mitigation
AI Governance Is Much More than Technology Risk Mitigation
Watch Now View
Spotlight 12:!3
You Can’t Build Pipelines, Warehouses, or AI Platforms Without Business Knowledge
Watch Now View
Spotlight 47:42
Cybersecurity – Where Leaders are Buying, Building, and Partnering
Rehan Jalil
Watch Now View
Spotlight 27:29
Building Safe AI with Databricks and Gencore
Rehan Jalil
Watch Now View
Spotlight 46:02
Building Safe Enterprise AI: A Practical Roadmap
Watch Now View
Latest
View More
Securiti+Veeam Will Accelerate Safe Enterprise Al at Scale
We started Securiti Al with the strong conviction that in the Information Age, the Information aka Data, is the life blood of businesses and a unified platform was needed to provide all essential controls and deep intelligence around...
View More
DataAI Security for Financial Services: Turn Risk Into competitive Advantage
Financial services run on sensitive data. AI is now in fraud detection, underwriting, risk modelling, and customer service, raising both upside and risk. Institutions...
View More
Navigating China’s AI Regulatory Landscape in 2025: What Businesses Need to Know
A 2025 guide to China’s AI rules - generative-AI measures, algorithm & deep-synthesis filings, PIPL data exports, CAC security reviews with a practical compliance...
View More
All You Need to Know About Ontario’s Personal Health Information Protection Act 2004
Here’s what you need to know about Ontario’s Personal Health Information Protection Act of 2004 to ensure effective compliance with it.
The 5 Tenets of Modern DSPM for Financial Services View More
The 5 Tenets of Modern DSPM for Financial Services
Learn the 5 tenets of modern DSPM for financial services: continuous discovery, access governance, real-time risk visibility, automated remediation, and continuous compliance.
Maryland Online Data Privacy Act (MODPA) View More
Maryland Online Data Privacy Act (MODPA): Compliance Requirements Beginning October 1, 2025
Access the whitepaper to discover the compliance requirements under the Maryland Online Data Privacy Act (MODPA). Learn how Securiti helps ensure swift compliance.
DSPM vs Legacy Security Tools: Filling the Data Security Gap View More
DSPM vs Legacy Security Tools: Filling the Data Security Gap
The infographic discusses why and where legacy security tools fall short, and how a DSPM tool can make organizations’ investments smarter and more secure.
Operationalizing DSPM: 12 Must-Dos for Data & AI Security View More
Operationalizing DSPM: 12 Must-Dos for Data & AI Security
A practical checklist to operationalize DSPM—12 must-dos covering discovery, classification, lineage, least-privilege, DLP, encryption/keys, policy-as-code, monitoring, and automated remediation.
The DSPM Architect’s Handbook View More
The DSPM Architect’s Handbook: Building an Enterprise-Ready Data+AI Security Program
Get certified in DSPM. Learn to architect a DSPM solution, operationalize data and AI security, apply enterprise best practices, and enable secure AI adoption...
Gencore AI and Amazon Bedrock View More
Building Enterprise-Grade AI with Gencore AI and Amazon Bedrock
Learn how to build secure enterprise AI copilots with Amazon Bedrock models, protect AI interactions with LLM Firewalls, and apply OWASP Top 10 LLM...
What's
New