Mage Data

Category: Blogs – BFSI

  • Reimagining Test Data: Secure-by-Design Database Virtualization

    Reimagining Test Data: Secure-by-Design Database Virtualization

    Enterprises today are operating in an era of unprecedented data velocity and complexity. The demand for rapid software delivery, continuous testing, and seamless data availability has never been greater. At the same time, organizations face growing scrutiny from regulators, customers, and auditors to safeguard sensitive data across every environment—production, test, or development.

    This dual mandate of speed and security is reshaping enterprise data strategies. As hybrid and multi-cloud infrastructures expand, teams struggle to provision synchronized, compliant, and cost-efficient test environments fast enough to keep up with DevOps cycles. The challenge lies not only in how fast data can move, but in how securely it can be replicated, masked, and managed.

    Database virtualization was designed to solve two of the biggest challenges in Test Data Management—time and cost. Instead of creating multiple full physical copies of production databases, virtualization allows teams to provision lightweight, reusable database instances that share a common data image. This drastically reduces storage requirements and accelerates environment creation, enabling developers and QA teams to work in parallel without waiting for lengthy data refresh cycles. By abstracting data from its underlying infrastructure, database virtualization improves agility, simplifies DevOps workflows, and enhances scalability across hybrid and multi-cloud environments. In short, it brings speed and efficiency to an otherwise resource-heavy process—freeing enterprises to innovate faster.

    Database virtualization was introduced to address inefficiencies in provisioning and environment management. It promised faster test data creation by abstracting databases from their underlying infrastructure. But for many enterprises, traditional approaches have failed to evolve alongside modern data governance and privacy demands.

    Typical pain points include:

    • Storage-Heavy Architectures: Conventional virtualization still relies on partial or full data copies, consuming vast amounts of storage.
    • Slow, Manual Refresh Cycles: Database provisioning often depends on DBAs, leading to delays, inconsistent refreshes, and limited automation.
    • Fragmented Data Privacy Controls: Sensitive data frequently leaves production unprotected, exposing organizations to compliance violations.
    • Limited Integration: Many solutions don’t integrate natively with CI/CD or hybrid infrastructures, making automated delivery pipelines cumbersome.
    • Rising Infrastructure Costs: With exponential data growth, managing physical and virtual copies across clouds and data centers drives up operational expenses.

    The result is an environment that might be faster than before—but still insecure, complex, and costly. To thrive in the AI and automation era, enterprises need secure-by-design virtualization that embeds compliance and efficiency at its core.

    Modern data-driven enterprises require database virtualization that does more than accelerate. It must automate security, enforce privacy, and scale seamlessly across any infrastructure—cloud, hybrid, or on-premises.

    This is where Mage Data’s Database Virtualization (DBV) sets a new benchmark. Unlike traditional tools that treat masking and governance as secondary layers, Mage Data Database Virtualization builds them directly into the virtualization process. Every virtual database created is masked, compliant, and policy-governed by default—ensuring that sensitive information never leaves production unprotected.

    Database Virtualization lightweight, flexible architecture enables teams to provision virtual databases in minutes, without duplicating full datasets or requiring specialized hardware. It’s a unified solution that accelerates innovation while maintaining uncompromising data privacy and compliance.

    1. Instant, Secure Provisioning
      Create lightweight, refreshable copies of production databases on demand. Developers and QA teams can access ready-to-use environments instantly, reducing cycle times from days to minutes.
    2. Built-In Data Privacy and Compliance
      Policy-driven masking ensures that sensitive data remains protected during every clone or refresh. Mage Data Database Virtualization is compliance-ready with frameworks like GDPR, HIPAA, and PCI-DSS, ensuring enterprises maintain regulatory integrity across all environments.
    3. Lightweight, Flexible Architecture
      With no proprietary dependencies or hardware requirements, Database Virtualization integrates effortlessly into existing IT ecosystems. It supports on-premises, cloud, and hybrid infrastructures, enabling consistent management across environments.
    4. CI/CD and DevOps Integration
      DBV integrates natively with Jenkins, GitHub Actions, and other automation tools, empowering continuous provisioning within DevOps pipelines.
    5. Cost and Operational Efficiency
      By eliminating full physical copies, enterprises achieve up to 99% storage savings and dramatically reduce infrastructure, cooling, and licensing costs. Automated refreshes and rollbacks further cut
      manual DBA effort.
    6. Time Travel and Branching (Planned)
      Upcoming capabilities will allow enterprises to rewind databases or create parallel branches, enabling faster debugging and parallel testing workflows.

    The AI-driven enterprise depends on speed—but the right kind of speed: one that doesn’t compromise security or compliance. Mage Data Database Virtualization delivers precisely that. By uniting instant provisioning, storage efficiency, and embedded privacy, it transforms database virtualization from a performance tool into a strategic enabler of governance, innovation, and trust.

    As enterprises evolve to meet the demands of accelerating development, they must modernize their entire approach to data handling—adapting for an AI era where agility, accountability, and assurance must coexist seamlessly.

    Mage Data’s Database Virtualization stands out as the foundation for secure digital transformation—enabling enterprises to accelerate innovation while ensuring privacy and compliance by design.

  • Building Trust in AI: Strengthening Data Protection with Mage Data

    Building Trust in AI: Strengthening Data Protection with Mage Data

    Artificial Intelligence is transforming how organizations analyze, process, and leverage data. Yet, with this transformation comes a new level of responsibility. AI systems depend on vast amounts of sensitive information — personal data, intellectual property, and proprietary business assets — all of which must be handled securely and ethically.

    Across industries, organizations are facing a growing challenge: how to innovate responsibly without compromising privacy or compliance. The European Commission’s General-Purpose AI Code of Practice (GPAI Code), developed under the EU AI Act, provides a structured framework for achieving this balance. It defines clear obligations for AI model providers under Articles 53 and 55, focusing on three key pillars — Safety and Security, Copyright Compliance, and Transparency.

    However, implementing these requirements within complex data ecosystems is not simple. Traditional compliance approaches often rely on manual audits, disjointed tools, and lengthy implementation cycles. Enterprises need a scalable, automated, and auditable framework that bridges the gap between regulatory expectations and real-world data management practices.

    Mage Data Solutions provides that bridge. Its unified data protection platform enables organizations to operate compliance efficiently — automating discovery, masking, monitoring, and lifecycle governance — while maintaining data utility and accelerating AI innovation.

    The GPAI Code establishes a practical model for aligning AI system development with responsible data governance. It is centered around three pillars that define how providers must build and manage AI systems.

    1. Safety and Security
      Organizations must assess and mitigate systemic risks, secure AI model parameters through encryption, protect against insider threats, and enforce multi-factor authentication across access points.
    2. Copyright Compliance
      Data sources used in AI training must respect intellectual property rights, including automated compliance with robots.txt directives and digital rights management. Systems must prevent the generation of copyrighted content.
    3. Transparency and Documentation
      Providers must document their data governance frameworks, model training methods, and decision-making logic. This transparency ensures accountability and allows regulators and stakeholders to verify compliance.

    These pillars form the foundation of the EU’s AI governance model. For enterprises, they serve as both a compliance obligation and a blueprint for building AI systems that are ethical, explainable, and secure.

    Mage Data’s platform directly maps its data protection capabilities to the GPAI Code’s requirements, allowing organizations to implement compliance controls across the full AI lifecycle — from data ingestion to production monitoring.

    GPAI Requirement

    Mage Data Capability

    Compliance Outcome

    Safety & Security (Article 53)

    Sensitive Data Discovery

    Automatically identifies and classifies sensitive information across structured and unstructured datasets, ensuring visibility into data sources before training begins.

    Safety & Security (Article 53)

    Static Data Masking (SDM)

    Anonymizes training data using over 60 proven masking techniques, ensuring AI models are trained on de-identified yet fully functional datasets.

    Safety & Security (Article 53)

    Dynamic Data Masking (DDM)

    Enforces real-time, role-based access controls in production systems, aligning with Zero Trust security principles and protecting live data during AI operations.

    Copyright Compliance (Article 55)

    Data Lifecycle Management

    Automates data retention, archival, and deletion processes, ensuring compliance with intellectual property and “right to be forgotten” requirements.

    Transparency & Documentation (Article 55)

    Database Activity Monitoring

    Tracks every access to sensitive data, generates audit-ready logs, and produces compliance reports for regulatory or internal review.

    Transparency & Accountability

    Unified Compliance Dashboard

    Provides centralized oversight for CISOs, compliance teams, and DPOs to manage policies, monitor controls, and evidence compliance in real time.

    By aligning these modules to the AI Code’s compliance pillars, Mage Data helps enterprises demonstrate accountability, ensure privacy, and maintain operational efficiency.

    Mage Data enables enterprises to transform data protection from a compliance requirement into a strategic capability. The platform’s architecture supports high-scale, multi-environment deployments while maintaining governance consistency across systems.

    Key advantages include:

    • Accelerated Compliance: Achieve AI Act alignment faster than traditional, fragmented methods.
    • Integrated Governance: Replace multiple point solutions with a unified, policy-driven platform.
    • Reduced Risk: Automated workflows minimize human error and prevent data exposure.
    • Proven Scalability: Secures over 2.5 billion data rows and processes millions of sensitive transactions daily.
    • Regulatory Readiness: Preconfigured for GDPR, CCPA, HIPAA, PCI-DSS, and EU AI Act compliance.

    This integrated approach enables security and compliance leaders to build AI systems that are both trustworthy and operationally efficient — ensuring every stage of the data lifecycle is protected and auditable.

    Mage Data provides a clear, step-by-step plan:

    This structured approach takes the guesswork out of compliance and ensures organizations are always audit-ready

    The deadlines for AI Act compliance are approaching quickly. Delaying compliance not only increases costs but also exposes organizations to risks such as:

    • Regulatory penalties that impact global revenue.
    • Data breaches harm brand trust.
    • Missed opportunities, as competitors who comply early gain a reputation for trustworthy, responsible AI.

    By starting today, enterprises can turn compliance from a burden into a competitive advantage.

    The General-Purpose AI Code of Practice sets high standards but meeting them doesn’t have to be slow or costly. With Mage Data’s proven platform, organizations can achieve compliance in weeks, not years — all while protecting sensitive data, reducing risks, and supporting innovation.

    AI is the future. With Mage Data, enterprises can embrace it responsibly, securely, and confidently.

    Ready to get started? Contact Mage Data for a free compliance assessment and see how we can help your organization stay ahead of the curve.

  • Protecting Sensitive Data in Indian Insurance with Mage Data

    Protecting Sensitive Data in Indian Insurance with Mage Data

    In today’s digital landscape, Indian insurance companies face unprecedented challenges in managing sensitive customer data. With increasing regulatory scrutiny, sophisticated cyber threats, and the digitization of insurance processes, protecting sensitive information has become both a compliance necessity and a competitive advantage. This blog explores the unique data security challenges facing the Indian insurance sector and how comprehensive solutions like Mage Data can help mitigate these risks while enabling business growth.

    The Data Security Landscape in Indian Insurance

    Indian insurance companies handle vast amounts of sensitive personal and financial information, including:

    • Personal identifiable information (PII) such as names, addresses, and contact details
    • Financial information including bank account details and payment histories
    • Health records containing sensitive medical information
    • Family information used for life insurance and beneficiary designations
    • Claims history and risk assessment data

    This wealth of sensitive data makes insurance companies prime targets for cybercriminals. Additionally, as the sector undergoes rapid digital transformation, traditional security controls are struggling to keep pace with new vulnerabilities introduced by mobile apps, cloud migrations, and digital customer interfaces

    Key Challenges in Insurance Data Security

    • Regulatory Compliance Pressures
      Similar to the banking sector, insurance companies in India face mounting regulatory requirements. The Personal Data Protection Bill, IRDAI guidelines, and global standards like GDPR (for international operations) require comprehensive data protection measures. According to Economic Times reporting, compliance costs are rising significantly, with operational expenses increasing by approximately 20% in recent fiscal periods.

    • Test Data Management Issues
      Insurance applications require extensive testing before deployment, but using real customer data in testing environments creates significant security risks. Without proper test data management, sensitive information can be exposed to developers, testers, and third-party vendors who don’t require access to actual customer data.

    • Cross-Border Data Sharing
      Many insurance companies operate globally or work with international reinsurers, requiring secure methods for sharing data across borders while complying with both Indian and international data regulations.

    • Legacy System Integration
      The insurance sector often relies on legacy systems that weren’t designed with modern security requirements in mind. Integrating these systems with newer technologies while maintaining data security presents significant challenges.

    • Third-Party Risk Management
      Insurance companies frequently share data with third parties including agents, brokers, healthcare providers, and service vendors, expanding the potential attack surface for data breaches.

    The Business Impact of Data Security Failures 

    The consequences of inadequate data security in insurance can be severe:

    • Regulatory Penalties: Non-compliance with data protection regulations can result in significant financial penalties.
    • Reputational Damage: Data breaches can severely damage customer trust in an industry where trust is paramount.
    • Operational Disruption: Security incidents can disrupt business operations and lead to significant recovery costs.
    • Competitive Disadvantage: Insurers who cannot demonstrate robust data security may lose business to more secure competitors.

    How Mage Data’s Solutions Address These Challenges

    Mage Data offers a comprehensive suite of data security solutions specifically designed to address the challenges facing Indian insurance companies:

    1. Automated Sensitive Data Discovery

    Mage Data’s AI-powered Sensitive Data Discovery solution can scan across all data sources in an insurance environment, identifying where sensitive information is stored, who has access to it, and how it’s being used. This eliminates the need for time-consuming manual data classification and provides a complete picture of the data security landscape.

    2. Comprehensive Data Protection

    With both Static and Dynamic Data Masking capabilities, Mage Data provides a unified approach to protecting sensitive insurance data across production and non-production environments:

    • Static Data Masking: Creates safe, realistic test data by replacing sensitive information in non-production environments while maintaining referential integrity – crucial for accurate application testing.
    • Dynamic Data Masking: Enables real-time masking of sensitive data based on user roles and access rights, allowing different stakeholders to view only the data they need to perform their functions.
    3. Secure Test Data Management

    Mage Data’s Test Data Management 2.0 platform provides insurance companies with:

    • Self-service provisioning of anonymized test data
    • Intelligent subsetting to create smaller, more manageable test data sets
    • Maintenance of data relationships and referential integrity for accurate testing
    • Automated pipelines for refreshing test environments with protected data
    4. Cross-Border Data Protection

    Mage Data enables secure sharing of insurance data across borders through:

    • Format-preserving encryption and tokenization that protects data while maintaining its usability
    • Consistent application of data protection policies across all locations and systems
    • Secure file gateways that automatically protect sensitive files as they are shared
    5. Data Retirement

    The Data Retirement module helps insurance companies implement data minimization strategies, reducing the costs and risks associated with maintaining inactive sensitive data – particularly important as regulators focus more on data lifecycle management.

    6. Real-Time Monitoring and Alerts

    With Database Activity Monitoring, insurance companies can implement focused monitoring of sensitive data access, ensuring compliance with regulatory requirements while minimizing operational overhead.

    Key Differentiators of Mage Data’s Approach

    What sets Mage Data apart in addressing insurance data security challenges:

    1. Conversational User Interface

    Mage Data’s industry-first conversational interface enables faster adoption across the organization, allowing both technical and non-technical users to leverage data security capabilities without extensive training.

    2. Context-Preserving Protection

    Unlike basic security solutions, Mage Data maintains the context and relationships in protected data, ensuring that insurance-specific data patterns and relationships remain intact and usable for analytics, testing, and operations.

    3. Enterprise-Wide Coverage

    Mage Data protects sensitive information across the entire data lifecycle – at rest, in transit, and even when used in generative AI applications – providing comprehensive coverage across all insurance data environments.

    4. Secure File Gateways

    Automated monitoring of file repositories ensures that sensitive insurance documents are automatically detected and protected as they are created or moved between systems.

    5. Logs Masking

    Protects sensitive fields in application logs – crucial for securing diagnostic information while allowing IT teams to troubleshoot issues effectively.

    The ROI of Implementing Mage Data Solutions

    Implementing Mage Data’s solutions can deliver significant returns for insurance companies:

    • Reduced Compliance Costs: Automation of data security and compliance processes reduces manual effort and associated costs.
    • Enhanced Operational Efficiency: Self-service capabilities and automated pipelines accelerate development and testing cycles.
    • Minimized Breach Risk: Comprehensive protection reduces the likelihood and potential impact of data breaches.
    • Competitive Advantage: The ability to demonstrate robust data security can be a differentiator in the insurance market.

    Conclusion

    As Indian insurance companies navigate an increasingly complex data security landscape, comprehensive solutions like Mage Data offer a path forward that balances security, compliance, and operational efficiency. By implementing automated discovery, protection, and monitoring capabilities, insurers can not only mitigate risks but also position themselves for success in a digital future where data security is a foundation of customer trust.

    The time to act is now. With regulatory pressure continuing to mount and cyber threats becoming more sophisticated, insurance companies that proactively address data security challenges will be better positioned to thrive in a competitive market where customer trust is paramount.

    For more information on how Mage Data can help your insurance organization secure sensitive data while enabling innovation, contact [email protected].

    Source:
    The recent Economic Times article (https://ciso.economictimes.indiatimes.com/news/cybercrime-fraud/banks-unlikely-to-face-shocks-but-tech-cant-fix-all-the-cost-worries/116871849)
    highlights a growing challenge for Indian banks in 2025: escalating compliance costs amid tighter margins and regulatory changes.

  • Complying with DPDP: Mage Data for Indian Insurers

    Complying with DPDP: Mage Data for Indian Insurers

    In today’s digital landscape, safeguarding personal data is paramount, particularly for Indian insurance companies navigating the complexities of the Digital Personal Data Protection Act (DPDP). With stringent regulations now in place, these companies face the dual challenge of ensuring compliance while simultaneously managing vast amounts of sensitive data. The DPDP introduces specific provisions that significantly impact the insurance sector, demanding robust data protection solutions and meticulous attention to data security practices. Enter Mage Data, a trusted partner offering innovative solutions tailored to empower insurance companies in their journey towards DPDP compliance. In this post, we will delve into the challenges of sensitive data management within the insurance industry and explore how Mage Data’s expertise is pivotal in enhancing data security and maintaining regulatory adherence. For more insights, visit Mage Data’s DPDP page.

    Understanding DPDP Compliance for Insurers

    The Digital Personal Data Protection (DPDP) Act has introduced a new era of data governance in India, especially impacting the insurance sector. This section explores the core provisions of the DPDP Act that insurance companies need to understand and the challenges they face in managing personal data

    Key Provisions Impacting Insurance

    The DPDP Act requires insurance companies to adhere to several key provisions:

    • Data Fiduciary Obligations: Insurers must obtain explicit consent before data collection and ensure data is processed for stated purposes only.
    • Rights of Data Principals: Policyholders have enhanced rights to access, correct, and erase personal data, emphasizing the need for robust data management systems.
    • Enhanced Protection for Sensitive Data: Although not explicitly defined, sensitive data in insurance needs heightened protection, requiring insurers to implement stringent safeguards.

    Insurance companies must also comply with provisions regarding cross-border data transfers, which affect global operations and partnerships. Non-compliance could result in substantial financial penalties, underscoring the importance of adhering to DPDP standards.

    Challenges in Managing Personal Data

    Insurance companies face unique challenges, including handling massive volumes of sensitive data such as health records and financial information. This complexity is compounded by the involvement of multiple stakeholders across the insurance value chain, including agents, brokers, and third-party administrators.

    Legacy systems further complicate matters, as many insurers operate with outdated infrastructure that struggles to align with modern data protection standards. These systems often lack the security capabilities necessary to meet the DPDP requirements.

    The transition to digital platforms introduces additional layers of complexity, with insurers needing to balance legacy systems and new technologies while ensuring comprehensive data protection. The need for innovation in data management is critical in overcoming these challenges.

    Importance of Compliance for Insurers

    • Compliance with the DPDP Act is crucial for insurers not just to avoid penalties but to build customer trust and maintain competitive advantage. Demonstrating a commitment to data protection can enhance customer relationships and brand reputation.
    • Insurance companies must prioritize data protection as part of their broader risk management strategies. By aligning their operations with DPDP standards, insurers can mitigate the risks associated with data breaches and unauthorized access.
    • Ultimately, DPDP compliance represents an opportunity for insurers to differentiate themselves in a privacy-conscious market, positioning themselves as leaders in data protection and customer care.

    Mage Data’s Role in Compliance

    Mage Data provides solutions specifically tailored to help insurance companies achieve and maintain compliance with the DPDP Act. This section explores how Mage Data enhances security, manages sensitive data, and applies its solutions within the insurance industry.

    How Mage Data Enhances Security

    Mage Data enhances insurance data security through AI-powered data discovery and classification tools. These tools automatically identify and classify sensitive data across various systems, ensuring comprehensive monitoring and protection.

    Format-preserving tokenization and context-preserving masking techniques are employed to secure personal data during processing, reducing the risk of unauthorized access. These methods maintain data utility while ensuring privacy.

    Mage Data’s solutions also integrate seamlessly with existing encryption solutions, providing an additional layer of security. This integration is crucial for insurers adopting new technologies and transitioning towards digital transformation.

    Solutions for Sensitive Data Management

    Managing sensitive data within the insurance sector is a formidable task, but Mage Data offers several solutions:

    • Test Data Management: By creating de-identified test data, insurers can safely develop and test applications without exposing actual customer information.
    • Privacy-Enhancing Techniques: These techniques protect sensitive data from breaches by applying advanced tokenization and masking strategies.
    • Access Governance: Mage Data implements database firewalls and dynamic data masking to restrict unauthorized access and ensure compliance with DPDP security safeguards.

    These solutions enable insurers to manage sensitive data efficiently while adhering to regulatory requirements.

    Benefits of Using Mage Data

    Beyond compliance, Mage Data’s solutions offer a range of benefits for insurance companies. This section outlines how risk mitigation strategies, effortless compliance, and strengthened data security can be achieved with Mage Data.

    Conclusion

    The DPDP Act represents a significant shift in India’s data protection landscape, introducing substantial compliance requirements for insurance companies processing personal data of Indian residents. Mage Data’s comprehensive Conversational Data Security Platform addresses these requirements through advanced discovery, classification, protection, and governance capabilities specifically tailored for the insurance industry.

    By implementing Mage Data’s solutions, insurance companies can achieve DPDP compliance while maintaining data utility, operational efficiency, and business continuity. The platform’s innovative approach to Test Data Management creates “Perfectly Useful, Entirely Useless” data that enables insurance operations to continue without risking non-compliance.

    As India’s data protection regime continues to evolve, Mage Data provides the flexibility and scalability needed to adapt to changing requirements, ensuring long-term compliance and data security for insurance companies of all sizes.

    Ready to learn how Mage Data can help your insurance organization achieve DPDP compliance? Contact us today for a personalized demonstration.

  • Navigating HSM Compliance in the Bharat BFSI Sector with Mage Data

    Navigating HSM Compliance in the Bharat BFSI Sector with Mage Data

    Introduction

    The Bharat BFSI sector is navigating a complex regulatory landscape, with stringent requirements for data protection and privacy. Hardware Security Modules (HSMs) are crucial for securing cryptographic keys and ensuring compliance, but they can be challenging to implement and integrate with existing systems. Mage Data offers a powerful solution that complements HSMs, simplifying compliance, enhancing security, and optimizing performance.

    Understanding HSMs and Their Role

    HSMs are specialized hardware devices that safeguard cryptographic keys and perform cryptographic operations within a secure, tamper-proof environment. They are essential for:

    • Key Generation & Storage: Generating strong keys and storing them securely.
    • Key Management: Managing the lifecycle of keys (generation, storage, distribution, and destruction).
    • Cryptographic Operations: Performing encryption, decryption, digital signatures, and authentication.
    • Access Control: Implementing strict access controls to prevent unauthorized use.

    Organizations often face a trio of challenges when implementing HSMs

    • Regulatory Complexity: Navigating the maze of data protection regulations can be daunting. GDPR, CCPA, HIPAA, PCI DSS, and various industry-specific mandates create a complex web of requirements. Data localization laws add another layer of complexity, often requiring keys to be stored within specific geographical boundaries. Keeping up with these evolving regulations and ensuring consistent compliance can be a major headache.
    • Integration Complexity: Many legacy systems weren’t designed with HSMs in mind. Integrating these older systems with modern HSMs can require complex API integrations, middleware solutions, and custom development. Compatibility issues with older cryptographic libraries further complicate the process, leading to increased costs and implementation timelines.




    • Performance Overhead: Cryptographic operations, while essential, can introduce latency. In high-volume environments, this can lead to performance bottlenecks, impacting application responsiveness and user experience. Real-time transaction signing, SSL/TLS encryption, and blockchain key management are just a few examples of workloads that can be affected by HSM latency.

    Mage Data: Enhancing HSMs with Advanced Capabilities

    Mage Data complements HSMs by adding a layer of advanced data security and management capabilities:

    Secure Tokenization and De-tokenization:

    • Mage Data leverages HSMs to protect the mapping between tokens and real data, ensuring that even if tokens are compromised, the original data remains secure.
    • It provides granular control over token usage and facilitates secure de-tokenization when authorized access to the real data is required.

    Controlled Access to Sensitive Data:

    • Mage Data’s masking capabilities, combined with HSM access controls, enable fine-grained control over who can access sensitive data and in what form (masked or original).
    • This allows for secure data sharing and collaboration while protecting sensitive information.

    Performance Optimization:

    • Mage Data can offload certain masking operations to the HSM, leveraging its cryptographic capabilities for enhanced performance, especially for high-volume data masking tasks.

    Centralized Platform:

    • Mage Data integrates with HSMs to provide a centralized platform for managing both masking policies and cryptographic keys, simplifying data security management across the organization.


    How Mage Data Complements HSMs (with Diagram):Benefits of the Integrated Solution:

    • Enhanced Security: Multi-layered protection through HSMs and Mage Data’s masking and tokenization.

    • Simplified Compliance: Meeting regulatory requirements for data protection and key management.

    • Optimized Performance: Efficient masking and cryptographic operations.

    • Centralized Management: Streamlined administration of data security policies and keys.

    • Reduced Risk: Minimizing the risk of data breaches and unauthorized access.

    Conclusion:

    Mage Data complements HSMs by providing advanced data security capabilities, simplifying compliance, and optimizing performance. This integrated approach enables organizations in the Bharat BFSI sector to protect their sensitive data, meet regulatory requirements, and unlock the full potential of their data assets.

  • Ensuring Consumer Data Privacy in Financial Services

    Ensuring Consumer Data Privacy in Financial Services

    It used to be—even just a few years ago—that consumer advocacy groups were complaining that legislation had not “caught up” with technology, and that huge data privacy gaps existed. But today, gaps in data privacy regulation are only half of the problem, as multiple legislative bodies have worked tirelessly to close the gaps. As financial services becomes an increasingly digital industry, finserv organizations now have to prepare for tomorrow’s regulatory landscape as well.

    In particular, finserv organizations are finding that consumers of financial services themselves are sensitive to the collection and processing of their information. Fortunately, financial services ties healthcare as the most-trusted sector for data privacy, according to research from McKinsey & Company. Less fortunately, the percentage of respondents who trust data privacy practices in the financial services industry is still only 44%.

    Financial institutions can keep pace with these simultaneous rises in digital banking activity and data privacy legislation by taking proactive measures:

    • Commit to learning what’s protected under all relevant consumer data privacy laws.
    • Consider how advances in digital banking and online payments will affect privacy concerns going forward.
    • Give customers transparency regarding data collection, protection, sharing, and use.
    • Implement data security and data privacy throughout the entire data lifecycle.
    • Appoint chief privacy officers and give them the resources required to develop thorough privacy practices.

      The nature of the financial services industry makes the stakes particularly high, but a commitment to best practices instills confidence and competence

    What to Know About Data Privacy in Financial Services

    Individuals divulge a great deal of personal information during online transactions. This is necessary because financial services organizations must have identity proofing to tie every transaction to a valid entity. Failure to collect, confirm, and store the appropriate data increases the likelihood of fraud. The need to collect, handle, and store data creates tension, as doing so means that financial institutions absorb responsibility for data privacy and data security.

    The Current State of Financial Privacy Regulation

    The uncertainty around data privacy for financial services is highlighted by the sheer volume of the applicable legislation. Instead of one universal law, financial institutions are accountable to numerous regulations, especially when they operate internationally. The following are several of the most common data privacy regulations impacting the financial services industry:

    • Gramm-Leach-Bliley Act (GLBA)
    • Payment Card Industry Data Security Standard (PCI DSS)
    • Sarbanes-Oxley Act (SOX)
    • California Consumer Protection Act (CCPA)
    • Payment Services Directive (PSD2)
    • General Data Protection Regulation (GDPR)
    • Financial Privacy Rule from the Federal Trade Commission (FTC)
    • Regulations from the New York State Department of Financial Services (NYDFS)
    • Consumer Data Right (Australia)
    • Monetary Authority of Singapore (MAS)

    The list above is a lot to absorb, but it isn’t even exhaustive. Organizations like the NYDFS and FTC work continuously to regulate financial services and products as threats and best practices evolve.

    When Financial Privacy Regulations Collide

    At times, consumer privacy laws seem to contradict each other. For example, the CCPA gives individuals the right to delete (or request deletion of) some of their information, but there are exceptions. One such exception occurs when financial institutions need the information in question to operate. Reconciling consumer privacy regulations and finance-specific privacy regulations—especially when one regulation supersedes another—requires constant diligence and a comprehensive data protection strategy.

    Evolving Data Privacy Responsibilities in the Finance Industry

    Data protection strategies must be works in progress if they’re not to become outdated. The current state of data privacy for financial services organizations doesn’t stay current for very long. Legislative bodies are creating and modifying regulations, which is far from the only concern. Data breaches, technological adoption, and data privacy best practices are evolving every bit as quickly.

    4 Steps Toward Data Privacy for Financial Services Organizations

    Pressing data security challenges in the financial services industry include third-party risks, data transfers, and compliance issues. A comprehensive strategy allows financial institutions to prepare, implement, and maintain an integrated data privacy platform:

    PrepareImplementMaintain
    1. Sensitive Data Discovery and Classification
    2. Appoint a chief privacy officer or work with a third-party organization to keep up with changing regulations
    1. Static Data Masking
    2. Dynamic Data Masking
    3. Additional Privacy Enhancing Technologies
    1. Database Activity Monitoring
    2. Data Subject Access Rights Requests
    3. Database Visualization
    4. Database Firewall
    1. Sensitive Data Discovery

    By definition, a privacy plan can only be comprehensive when it covers all information throughout the enterprise or institution. Data discovery is a vital first step. Diligent data discovery brings hidden or forgotten information into the light.

    Accurate data discovery and thoughtful data classification make privacy plans more intentional. The process answers some of the most pressing data protection questions:

    • Which data is necessary, and which is best disposed of?
    • Which individuals, applications, and third parties need access to data?
    • How sensitive is the information retained?
    • What do applications and analysts need to get from the data to operate as intended?

      Answers to these questions provide the visibility required to protect data as efficiently as possible.
    2. Data Protection

    It’s often necessary to retain sensitive information. The financial institution absorbs responsibility for data privacy and security in these cases. Techniques like encryption, tokenization, and masking anonymize data in various states and environments. Dynamic data masking, for example, protects data in use without slowing down the analytics team. Static data masking is a common choice for data at rest, or whenever it’s best to permanently replace sensitive data without the potential for re-identification (also known as de-anonymization).

    To close the loop, Privacy enhancing technologies (PETs) facilitate analysis of the privacy plan itself: with data sensitivity scorecards, incremental data scanning, and audit-ready reporting. Interconnected and interdependent networks of PETs allow financial services institutions to meet their various data privacy goals and expectations.

    After selecting PETs or other data protection techniques to meet all privacy requirements, it’s time to bring everything into a manageable hub.

    3. Integrating Data Security and Data Privacy

    Beyond well-integrated, a data security platform must be scalable enough to protect all data sources, production, and non-production environments. Bringing data privacy into a central hub makes it more difficult for anything to fall through the cracks. Such a platform ties preparation, implementation, and maintenance together.

    Increased visibility, manageable breach notifications, and adequate compliance reporting take the guesswork out of data privacy. Scalable solutions and excellent knowledge of the current state of an organization’s data privacy efforts make it easier to evolve. Adapting to changing regulations doesn’t have to mean starting over.

    Finally, integrated data security and data privacy platforms keep the burden of database activity monitoring to a minimum. Data subject access rights requests, alerts, and notifications appear in one central location. From there, it’s easier to add database visualization tools to help spend less time identifying priorities and more time working on them.

    4. Data Privacy and Consumer Consent

    Collecting and using personal data is generally prohibited unless the subject consents or the data processing is expressly allowed by regulation. Even when a financial organization has every right to collect information, it may be required to provide privacy notices. Under the GLBA, for example, organizations are required to provide notice of how they collect and use information. An organization must provide notice to the data subject even when the data processing does not require the subject’s consent.

    Data Privacy Technology for the Finance Industry

    Regulatory technology, or RegTech, is working behind the scenes to help financial services firms regain customer trust. Financial institutions that navigate the customer trust landscape gain competitive advantages by protecting their reputations.

    Societal factors like social distancing forced banks to accelerate digital transformation plans, and RegTech offers a much-needed boost. Consumer insights and regulatory compliance are twin differentiators. Legislative bodies and individual users are most satisfied when financial institutions go above and beyond minimum requirements and invest proactively in data protection solutions.

    Getting Started With Data Privacy for Financial Services

    The rising legislative and market-driven demand for data privacy separates financial institutions with stringent data protection plans. A demonstrable commitment to data privacy helps organizations win trust to increase their user base, and avoid fines to protect profits. Comprehensive programs address privacy, security, and data risks as interconnected and interdependent issues. To see how data security and data privacy for financial services combine, contact Mage Data for a demo.

  • Data Privacy Regulatory Compliance: A Primer

    Data Privacy Regulatory Compliance: A Primer

    Businesses can get into serious legal trouble if they don’t take care of customer data. But, that’s not the only reason that data privacy is important. Improper access to data and data breaches can have profoundly negative consequences on your employees and your users. Handling personal data correctly not only protects your business, but also shows that you’re treating your customers and employees ethically—and ensures that their data is safe from prying eyes.

    To meet those lofty goals, businesses need a comprehensive approach to data privacy grounded in modern best practices.

    What is Data Privacy?

    Before diving into the mechanics of data privacy, it’s important to understand the field’s evolution and how we got to where we are today.

    A History of Data Privacy

    The Privacy Act of 1974 is arguably the first data privacy act passed anywhere in the world. Given the rise of electronic databases across government agencies and the ease of sharing data between them, there were new avenues for potential abuse of private information. In passing the law, the US government established four principles that have heavily influenced subsequent data privacy laws.

    First, it requires government agencies to show individuals a copy of any records it keeps on them. This is very similar to the “Right to Access” that appears in later laws. Second, it outlined “fair information practices,” which were designed to better manage how government employees collected and used personal data. Third, it restricts how agencies should share personal data with individuals and other agencies, though law enforcement was generally exempted from this practice. Fourth, it allowed people to sue the government for mishandling the data, establishing that data privacy was important and deserved a legal remedy when it was violated.

    The next major data privacy law came in 1998, with the Health Information Portability and Accountability Act, or HIPPA. One of the critical innovations of this approach to data privacy was the acknowledgment that some kinds of personal data were more sensitive than others and required greater safeguards. In this instance, medical information was put in the spotlight. While it has transformed how the medical industry handles personal information, it was only a glimpse of things to come.

    While the Privacy Act of 1974 and HIPPA focused on governmental and medical records, recent laws have focused on personal information of nearly every type and across all industries. The General Data Protection Regulation, which went into effect in the EU in 2018, heavily restricted how companies could use data, required consent for data use, and created a “right of deletion” for personal data held by companies. Likewise, the California Consumer Protection Act, which went into effect in 2020, places a strong emphasis on consent when processing personal data and allows for legal remedies in the case of a data breach.

    Why Do Companies Retain Records, Anyway?

    Given the headache of managing data in the modern regulatory environment, it’s fair to wonder why companies do it. Here are the core reasons companies collect, store, and manage data as a part of their regular business.

    Provide Core Business Services

    The first and most important reason companies collect and store information is to provide their core business services. Imagine that you’re a retail company trying to fulfill an online order without the customer’s name, address, or credit card information. It would be impossible! Nearly all businesses need some customer information to run their business. However, for many organizations, the complexity of the data collected is much higher.

    For example, a mortgage company may need detailed information about employment and pay and one or multiple credit reports. And it may need to hold onto them for a while, or request updates, as the customer in question shops for a home during a changing economic environment. Or a medical company may hold extensive information about a patient’s health and healthcare, with records that date back years. Doctors need that information to provide the right care to their patients.
    Your company may differ from those listed above. However, the fact remains that there are likely fundamental business processes that you would be unable to run without collecting and using customer data.

    Analyze and Project Business Performance

    Customer data may also be needed to analyze and project business performance. Historical reporting often tangentially or directly requires customer data. Without it, there would be holes in the report and gaps in the business’ understanding of how it was doing. However, historical reporting is only part of the equation. Businesses need to innovate to remain competitive and want to find ways to increase their sales and revenue. Data, especially customer data, may hold the secrets to unlock these advances.

    Meet Regulatory Requirements

    Sometimes, organizations must hold on to personal data for a certain period to meet regulatory requirements. This is more common when the organization or the information it keeps are related to finance, medicine, or education—but it can happen in any industry. It’s important to ensure that your business complies with these laws, as failing to do so can result in severe fines and a significant hit to your company’s public reputation.

    Learn More About Data Privacy Regulatory Compliance

    Handing data is a core part of just about any business operation today. Given that it’s so central to what businesses do, it’s important that they both manage data as efficiently as possible and comply with the privacy laws worldwide that dictate what they can’t and must do with their data.

  • SOX Compliance and Data Privacy: What Companies Need to Know

    SOX Compliance and Data Privacy: What Companies Need to Know

    The Sarbanes-Oxley Act (SOX) was passed by the United States Congress in 2002 to protect the public from fraud by business entities such as corporations. The purpose of this act is to increase transparency in financial reporting with a formal system of checks and balances. SOX brings a legal obligation to what was already good business practice. Financial security controls implemented for SOX compliance have a lot in common with the best practices for data protection, which helps prevent data theft. Prioritizing cybersecurity reduces the risk of data breaches, whether by insider theft or cyberattacks.


    Which Companies Need SOX Compliance?

    The Sarbanes-Oxley Act applies to all publicly traded companies in the United States. It also applies to publicly traded foreign companies or wholly-owned subsidiaries that do business in the United States. Tangentially, SOX also applies to auditors and accounting firms that audit SOX-regulated entities. Finally, any private company planning an IPO should be SOX compliant before going public.
    Private organizations (including companies and nonprofits) are not required to be fully SOX compliant, though they may be affected in some cases. For example, the Sarbanes-Oxley Act contains language about penalizing any organization that knowingly falsifies or destroys financial data.


    Data Retention vs. Data Protection

    The requirement to retain some financial data can create problems. In many applications, best practices dictate that sensitive data be deleted when no longer needed: Companies should only retain the minimum amount of sensitive data, and for the absolute minimum amount of time possible. However, data cannot be erased or destroyed if it is required to prove SOX compliance, which is where the tension occurs.


    This may seem like a catch-22, but data privacy laws do account for instances when data retention is mandated by other reporting requirements. SOX does not normally contradict GDPR, CCPA, and other data privacy regulations, for example. All of these regulations exist to encourage greater accountability on the part of companies, and (despite potential challenges) policies are not drafted to create impossible situations.


    Exceptions: When SOX and Data Privacy Regulations Collide


    SOX typically applies to the company’s financial data, not to any individual’s personal data. However, there are areas where a company’s financial data overlaps slightly with an individual’s data. For example, companies have to retain customer invoices for five years, tax returns for seven years, and payroll records forever. This is financial data related to the company, but it is also likely to include sensitive information related to individuals.


    Can Data Be Safe and Useful?


    A data privacy strategy is tested in these kinds of situations, where data must be retained, but also kept completely secure. There are numerous steps to a comprehensive data protection solution. First, it is important to identify and locate all sensitive data throughout the entire enterprise. From there, a plan should be put in place for all sensitive data discovered.

    At this point, it is crucial to understand the difference between data encryption, tokenization, and masking. Encryption is an excellent solution for data that will be stored for the long term. Tokenization is ideal for data that must be moved or migrated. Masking is a great way to protect sensitive data while preserving its utility. Depending on an organization’s specific needs, there are applications where all three techniques are useful (both in the context of SOX compliance as well as the broader data privacy strategy).


    Benefits of SOX Compliance


    Ensuring SOX compliance creates benefits that ripple across an entire organization. It leads to more consistent financial reporting, which appeals to shareholders. Beyond the benefits of superior financial reporting, compliance with SOX also reduces exposure to data breaches. Preventing cyberattacks helps reduce costs and protect the brand. Finally, SOX compliance makes it easier to navigate an audit and avoid penalties.


    Penalties of SOX Non-Compliance


    The penalties for SOX non-compliance can be severe, and may occur in a number of categories. There may be fines, invalidation of directors and officers (D&O) liability Insurance, and removal from public stock exchanges. Individual executives, especially CEOs and CFOs or any others who intentionally submit incorrect information during a SOX audit, may be faced with millions of dollars of fines and lengthy prison sentences.


    Preparing for a SOX Compliance Audit


    As with any other type of audit, the best way to prepare is to stay prepared. In the case of SOX compliance, that means conducting a thorough discovery of all sensitive data, then protecting that data appropriately. When a company is audited for SOX compliance, they must prove they’re using the relevant controls to ensure appropriate data protection and accurate financial reporting.


    Key Sox Compliance Requirements


    There should be no need to scramble to prepare for an audit, because the strategy should already be established and maintained. That said, there are six especially important areas to consider before a looming SOX compliance audit:

    1. Section 302 – Corporate Responsibility for Financial Reports – This section states that the CEO and CFO are responsible for the accuracy, documentation, and submission of financial reports and the internal control structure to the SEC. These two executives must also establish and maintain SOX controls and validate their internal controls during the 90 days prior to their report.
    2. Section 404 – Management Assessment of Internal Controls – This is considered to be among the most complicated parts of SOX compliance, and is therefore among the most expensive. All annual financial reports must include an Internal Control Report confirming that management is responsible for an adequate internal control structure, and must include management’s assessment of the effectiveness of their own control structure. This report must include any shortcomings, and the accuracy of the report must be validated by an independent auditor.
    3. Section 409 – Real-Time Issuer Disclosures – Companies must immediately disclose any material changes in operations or financial condition, in order to protect investors and the general public.
    4. Section 802 – Criminal Penalties for Altering Documents – Unsurprisingly, it is illegal to tamper with investigations in any way. There are penalties for any employees, accountants, or auditors who willfully violate normal procedures to influence investigations.
    5. Section 806 – Employees who disclose corporate fraud are protected. Any retaliation over whistleblower complaints can lead to criminal charges.
    6. Section 906 – Certifying a fraudulent or otherwise misleading financial report can carry a criminal penalty of upwards of $5 million in fines and 20 years in prison.
      The commonality between these six sections is that honesty and transparency are of utmost importance for SOX compliance. When a company has a robust security strategy and other necessary controls in place, the only thing to do for a SOX audit is to let the auditors do their jobs while you accurately report the appropriate information. The focus should be on maintaining SOX compliance at all times, rather than preparing for an upcoming or potential audit.

    Data Protection for SOX Compliance and Beyond


    The same capabilities a SOX auditor will look into are part of a good data protection plan anyway. Areas to consider include, but are not limited to, the following:

    • Access – Is there a least permissive access model in place, such that every user has the minimum access required to do their jobs? Access should be controlled with physical controls (such as doors, badges, locking file storage) as well as technological controls (login policies, permission audits, and least privileged access).
    • Change Management – Are there defined processes to install new software, add new users, modify databases, or change applications that relate to finance?
    • Data Backup – Are all financial records backed up off-site in a SOX-compliant manner?
    • Security – Can you demonstrate that you are protected against data breaches?

    SOX provides organizations with a framework to help them manage their financial records. It is the legal minimum, however, and is not intended to be a full replacement for a thoughtful data protection plan.

    The Sarbanes-Oxley Act lays out measures every company must take, and it falls upon individual business leaders to take additional steps based on their specific situations. Contact a cybersecurity partner to learn more about Data Governance, or schedule a demo to see specifically how a cybersecurity plan contributes to SOX compliance.

  • Data Retention vs. Data Privacy: What Should Employers Do?

    Data Retention vs. Data Privacy: What Should Employers Do?

    Imagine this scenario: An ex-employee comes to your organization and demands that you delete certain sensitive information from the company database. The head of HR politely explains that, due to certain laws in the U.S., those records need to be kept for three years. The ex-employee threatens to take legal action to have the records deleted, citing current data privacy laws.

    This is not a far-fetched scenario at all. There has always been a tension in the law between requirements for data retention—that is, how long records need to be kept to stay within compliance—and data privacy.

    But the tension has been on people’s minds recently because of “The Great Resignation.” More workers now are leaving their current jobs than at any other time over the past two decades. The U.S. Department of Labor, for example, has been reporting record-high resignation numbers for months, with the latest record of a 3.0% quit rate happening in September 2021.

    Let’s leave aside, for the moment, why people are quitting and how companies are responding. The glaring issue here is that companies now have record numbers of ex-employees. And this is bringing the issue of retaining sensitive employee information to the fore. Combine this with stricter privacy laws and penalties for over-retention, and it’s no wonder data retention has become one of the biggest topics when it comes to data security and data privacy.

    Here at Mage Data, we are not legal experts and do not pretend to give legal advice. But we can say something about the ways in which data should be protected, and how access should be carefully controlled, to satisfy both data retention needs and privacy concerns.

    What Counts as Private Employee Data?

    The first thing to be clear on is that there is no one universal definition, legal or otherwise, for what counts as private or sensitive employee data. But there are clearly some things that everyone agrees fall under this category:

    • Employee addresses/places of residence
    • Social Security numbers
    • Dates of birth
    • Salary information
    • Insurance information
    • Medical records
    • Bank account information

    In general, sensitive data includes anything that an employee would have a “reasonable expectation” would be kept confidential and used only for the employee’s benefit. Thus, it includes the types of information that are regularly gathered by employers to process payroll, manage employee benefit plans, etc.

    The Tension Between Data Privacy and Records Keeping

    Data privacy runs into an issue when it comes to data retention and records keeping. For example, under the U.S. Fair Labor Standards Act (FLSA), employers above a certain size must keep payroll records for at least three years, even after an employee has subsequently left a company.

    Now imagine what needs to happen for a company to be in compliance with, say, the European Union’s GDPR (which is any company doing business in the EU, regardless of whether they have an EU location). Under the GDPR, employees must be informed about:

    • What data of theirs is collected
    • Who owns or controls that data
    • Any third parties that receive their data (such as payroll providers or benefits providers)
    • Their rights and protections under the GDPR

    Because records must be kept for three years, some companies will have a significant amount of sensitive data relating to ex-employees. Thus, these ex-employees will have to be informed about their data and its use, too.

    The GDPR also comes with something called “The Right to Be Forgotten.” In plain English, this amounts to the right to request that personal information be removed from a system. Thus, a former employee can request of a company that any personal data collected during their employment tenure be removed.

    It gets worse. What happens if a company wants to run analytics on, say, benefits use? This will require company data on current and past employees. But the company may very well want to outsource these analytics to a third party. Passing the actual data to an analytics company would trigger a series of steps to stay in compliance with privacy laws—and never mind the hornet’s nest that data stirs up crossing international borders.

    Best Practices for Data Privacy of Ex-Employees

    So can an employee really come and demand that you erase their data? Yes and no.

    The GDPR, for example, clearly states that there are circumstances where an employer can refuse to comply with a request to be forgotten—for example, where that data or its processing is required to be retained by law, or is needed for an ongoing legal case. So, if there is a clear law requiring data retention, this should be followed.

    Things get trickier if the data is beyond the window where retention is required by law. For this reason, many companies are turning to automated solutions for destroying data records according to a pre-ordained schedule (such as our own Data Minimization, part of the Mage Data Minimization suite).

    And for data that is within the retention window, care still needs to be taken. Take the analytics example given above. The transfer of data to third parties is a sensitive undertaking, and the risk of a data breach is much higher. Instead of transmitting sensitive data, it makes more sense to send masked data using a tool that preserves the relationships between data items. This allows third parties to provide useful analytics without having direct access to personal information.

    Finally, it pays to do a regular audit of your data to discover where sensitive employee data lives. Chances are good that a significant amount of employee data “lives” in places that might be missed by routine records deletion. This can create a problem in terms of data privacy. By doing sensitive data discovery, an organization can “plug the holes” when it comes to data privacy laws, either deleting the information or masking it (if it is part of current business processes).

    For more on how Mage Data can help strike a balance between data retention and data privacy, see:

    Dynamic Data Masking with Mage Data
    Sensitive Data Discovery with Mage Data
    Data Minimization with Mage Data

  • Data Security Challenges in Financial Service Industry

    Data Security Challenges in Financial Service Industry

    The industry most targeted by cybercriminals is the financial services industry. Because of the sheer volume of sensitive financial data carried by this industry, it serves as a hotspot for cyberattacks. 47.5% of financial institutions were breached in the past year, while 58.5% have experienced an advanced attack or seen signs of suspicious behavior in their infrastructure.

    There are also quite a few regulations that govern this industry in specific, such as the PCI-DSS (Payment Card Industry Data Security Standard), GLBA (Gramm-Leach-Bliley Act, aka the Financial Services Modernization Act), and BCBS 239 (Basel Committee on Banking Supervision’s regulation number 239). Although the industry is heavily regulated, it has a significantly high data breach cost at $5.86 million2. So, data falling into unauthorized hands not only results in non-compliance for the organization but also puts it at financial risk due to the high cost of data breaches

    Challenges

    Third-party risks

    The use of third-party vendors is one of the major forces behind the cybersecurity risk that threatens financial institutions3. Most organizations work with hundreds or even thousands of third parties, creating new risks that must be actively handled. The financial sector has massive third-party networks that pose new weak spots in cyber defense. In the next two years, we can expect to see an exponential rise in attacks on customers, partners, and vendors4. Without continuous monitoring and reporting, along with the use of critical tools to do so, organizations are vulnerable to data breaches and other consequences.


    Data transfers (cross-border data exchanges)


    The most fundamental challenge is to keep your private data private. Given that the financial sector produces and utilizes a massive amount of sensitive data, and is highly regulated, cybersecurity becomes paramount. Adequate measures are needed to protect data at rest, in use, and in motion.
    Security concerns
    Problems arise with data security when employees, security officials, and others tasked with protecting sensitive information fail to provide adequate security protocols. They may become careless about leaving their credentials around at home or in public places. Other issues arise when networks and web applications provided by institutions don’t have enough safeguards to keep out hackers looking to steal data.
    According to SQN Banking Systems, the five biggest threats to a bank’s cybersecurity include:
    • Unencrypted data
    • Malware
    • Non-secure third-party services
    • Manipulated data
    • Spoofing

    Evolution of technology and the threat landscape

    Technology evolves daily; what we’re using now might be obsolete in the coming year. At the same time, cybercriminals are also equipping themselves to face technological advancements head-on. Looking at the alarming number of cybercrimes in the past year, they are much advanced than the technology we are using. In such a scenario where criminals are always one step ahead of the organization, blocking threats becomes a difficult task.

    Evolving customer needs and organizations

    Just as technology evolves, so do organizations and the way they function. Customer needs are ever-increasing, and they want quick solutions. What customers might not realize is that appealing technology comes with its set of risks. Moreover, there probably isn’t a financial institution today that hasn’t explored digital and mobile platforms. As they continue to keep expanding and using these platforms to cater to their consumers, they’re incidentally open to cyber risk exposure. Retaining customer confidence while meeting their growing needs to newer technologies becomes a complicated process.
    Remaining compliant
    Alongside dealing with the challenges mentioned above, it is imperative that financial institutions also put in the effort to stay compliant with laws such as the GDPR and CCPA to avoid hefty fines and other concerns such as revenue loss, customer loss, reputation loss, and the like.


    Solutions

    • Monitor user activity for all actions performed on sensitive data in your enterprise.
    • Choose from different methods or select a combination of techniques such as encryption, tokenization, static, and dynamic data masking to secure your data, whether it’s at rest, in use, or in motion.
    • Before this step, sensitive data discovery is a must, because if you don’t know where your data is, how will you protect it?
    • Deploy consistent and flexible data security approaches that protect sensitive data in high-risk applications without compromising the application architecture.
    • Your data security platform should be scalable and well-integrated, which is consistent across all data sources and span both production and non-production environments.
    • Finally, ensure the technology you’re implementing is well integrated with existing data protection tools for efficient compliance reporting and breach notifications.


    Conclusion


    If financial institutions think they can dodge cyberattacks with the help of mediocre data security strategies, recent heists would’ve proved them wrong. And despite prevention and authentication efforts, many make the mistake of thinking anomalous and unauthorized activity will cease to occur, which is unfortunately not the case. While cyber-risk is inevitable, by implementing the right tools, and a well-defined approach to cybersecurity, financial institutions can be more prepared as threats evolve.

    About Mage Data


    Our data and application security platform is a single integrated platform that protects sensitive data across its lifecycle, with modules for sensitive data discovery, static and dynamic data anonymization, data monitoring, and data minimization. Our solutions in data security are certified, tested, and deployed across a range of customers all over the globe. We have successfully implemented our solution in many large financial institutions – top private bank in the Dominican Republic, one of the largest Swiss Banks, a global financial services software manufacturer, the world’s largest credit rating agency, and a top commercial bank in the United Arab Emirates.

    How a Swiss Bank is effectively handling data security?

    A top Swiss Bank was looking to optimize costs by offshoring IT application development while ensuring compliance without compromising on sensitive data controls. This posed a need for sensitive data discovery and masking both production and non-production environments. In a highly regulated environment, they were able to deploy our product suite, a sophisticated solution that met their needs and was able to successfully achieve secure cross-border data sharing and sensitive data assessment for cloud migration and compliance.

    You can download the case study here: Mage Customer Success Stories – Comprehensive Security Solution for a Top Swiss Bank

    References


    1) Bitdefender – Top security challenges for the Financial Services Industry in 2018
    2) Ponemon Institute – Cost of a Data Breach Report, 2019
    3) PwC report – Financial services technology 2020 and beyond: Embracing disruption
    4) Protiviti – The Cybersecurity Imperative: Managing Cyber Risks in a World of Rapid Digital Change
    5) NGDATA: The Ultimate Data Privacy Guide for Banks and Financial Institutions