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    HomeBusiness InsightsData Privacy, GRC Integration, and Impact of Emerging Technologies under India’s DPDP...

    Data Privacy, GRC Integration, and Impact of Emerging Technologies under India’s DPDP Act

    The Digital Personal Data Protection Act (DPDP) is a groundbreaking regulation that is expected to reshape India’s data privacy landscape. With its emphasis on consumer rights, lawful data processing, and stringent compliance requirements, the Act signals a new era for businesses operating in a globalized digital ecosystem. To explore the implications of the DPDP Act, the integration of Governance, Risk, and Compliance (GRC) frameworks, and the challenges posed by emerging technologies like Generative AI, Anuj Khurana, Co-Founder and CEO of Anaptyss, shares his insights. Through this interview, Khurana delves into strategies for organizations to align with the DPDP Act, leverage collaborative efforts between private and government entities, and balance customer trust, compliance, and innovation in a rapidly evolving data-driven world.

    TAM: How is the Digital Personal Data Protection Act (DPDP) reshaping data privacy practices in India, and what are its implications for businesses across sectors?

    Anuj Khurana: The DPDP Act of 2023 is a landmark development in the data protection regulatory landscape, mandating organizations—within and outside India— to safeguard the privacy and security of consumers’ personal data across its lifecycle. 

    The Law restricts the scope of personal data collection and processing to lawful purposes, imposing “non-negotiable” and sweeping conditions related to User Consent, Purpose Limitation, Data Minimization, Data Security, Transparency, and Fair and Reasonable Processing, Grievance Redressal, and others.

    For example, in most cases, organizations (Data Fiduciary) must obtain explicit consent from the individual (Data Principal) for each data processing request. The Law also empowers individuals to access, rectify, and erase their data anytime. 

    DPDP obligates organizations to set up discrete controls to maintain adherence by:

    • Seeking explicit permission 
    • Being clear and transparent with the purpose and duration 
    • Allowing withdrawal of consent anytime 
    • Setting up a system for users to access, correct, and erase their data
    • Maintaining auditable and up-to-date records 

    To preempt the risks of DPDP violation, organizations must consider reinforcing their enterprise risk management framework with “entity-level” control design and testing across the three lines of defense, including operational management, compliance and oversight, and internal audits.

    For example, Anaptyss had helped a US-based community bank to comply with the Gramm-Leach-Bliley Act (GLBA) by testing over 150 key GLBA and non-key controls for information technology and operations (ITO). In the global context, DPDA compliance necessitates a clear understanding of the obligations to comply with cross-border data sharing and processing. In the emerging realm, training the employees on data privacy regulatory standards is crucial.

    TAM: In the evolving regulatory landscape, how can organizations integrate Governance, Risk, and Compliance (GRC) frameworks to ensure seamless adherence to the DPDP while maintaining operational efficiency?

    Anuj Khurana: There are several types of GRC frameworks based on their focus. Be it COBIT, ISO 31000, COSO, BASEL, CMMC, or others, their effective integration with the DPDP ACT necessitates a strategic and long-term approach, starting with:

    1. A Compliance-Centric structure, wherein designated roles/accountabilities must be established to enable dedicated and ongoing focus. For example, companies can establish a Data Protection Officer role to drive continual integration of GRC standards/components such as ISO 27001, SOC 2 Type 1, PCI DSS, and others with data protection regulations such as DPDP.
    2. Proactive assessments through the “Data Protection Impact Assessment” exercise to audit data protection/processing systems and determine DPDP violation risks due to 3rd party/vendor operations, chain of custody leakages, cyberattacks, misuse, etc. 
    3. Data protection policy formulation and enforcement across the organization to drive compliance with DPDP provisions by enabling the Data Principal’s rights to access, rectify, and erase their data, monitoring cross-border data flow, etc.
    4. Cultural evolution and employee training are other key imperatives for sustained and effective integration of the GRC framework with the data protection law.

    Adopting GRC software and process automation tools is crucial to operational efficiency and scalability.

    TAM: With the advent of Generative AI and other emerging technologies, what new data privacy challenges are businesses in India facing, and how can they proactively address these issues?

    Anuj Khurana: Gen AI is about the underlying machine learning model’s ability to “generate” autonomously, and that requires extensive datasets to train and fine-tune the model. The perpetual need for data is in direct conflict with the data minimization provision in the DPDP, which mandates organizations to collect only the necessary data for specified purposes.

    Data exposure is another potential challenge, wherein a Gen AI model may not adequately anonymize the personal/confidential data or lead to exposure due to unintended data connections.

    Another challenge can be due to the extent or nature of data processing in cases where Gen AI tools are involved, resulting in transparency concerns. In such cases, the organization cannot take a definite stance regarding explaining its data processing practices, leading to potential DPDP violations.

    Similarly, a lack of human oversight for AI governance can result in other issues concerning user consent, cross-border data transfer, IP violations, and even deep fakes made by exploiting the protected data.

    One of the overarching steps to address these challenges is to bring Gen AI and any other autonomous agents into the purview of the organization’s data privacy policies. This measure translates into multiple imperatives:

    1. Auditing Gen AI workflows for deviations 
    2. Human oversight for checking explicit consent for all data requests 
    3. Systemic testing of the controls for data anonymization, data security, and lawful use of data.

    TAM: How can Indian organizations balance customer trust, compliance requirements, and technological innovation while safeguarding sensitive data in a globalized digital ecosystem?

    Anuj Khurana: ”Collaboration” is the overarching canvas that can balance the pillars of trust, compliance, and innovation. Beyond taking preemptive measures—be it adopting privacy-enhancing tools, setting up a data governance board, or fostering a “privacy by design” culture—organizations need to devise an approach that allows them to:

    1. Communicate effectively to customers about the need to collect data and its usage
    2. Work closely with policymakers and industry bodies in adopting the industry best practices
    3. Follow a proactive approach in line with the mandates laid down by the DPDP Law
    4. Adopt global standards that support cross-border data privacy compliance norms
    5. Ensure ethical use of AI and other technologies 

    TAM: What role do industry leaders see for collaborative efforts between private organizations and government bodies in strengthening India’s data privacy framework in the coming years?

    Anuj Khurana: There is substantial scope for collaboration, and it is expanding amid emerging regulations, threats to data privacy, and a globalized context. 

    1. Co-create innovation: Private enterprises in domains such as data encryption, identity and access management, firewalls, endpoint and cloud security, and intrusion detection and protection can work with government bodies to develop new solutions for the industry at large.
    2. General awareness: Companies can partner with government agencies to drive focused campaigns for public awareness of data privacy and users’ rights under laws such as DPDP.
    3. Skill development and knowledge management: Consistent industry-level skilling is crucial to ensure company’s employees have adequate competency in dealing with data privacy risks and standards. Additionally, organizations and regulatory bodies need to partner to ensure a long-term curation of the existing body of knowledge and capabilities for protecting data privacy. For example, Fluent – a digital knowledge management solution by Anaptyss – enables skilling through hands-on learning modules and knowledge libraries.
    4. Joint policymaking: Organizations, government, and academia can come together to exchange key insights into the industry, emerging technologies, cross-border data governance, global best practices, and other aspects to devise more robust and enforceable policies.

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