Written by

Sumeshwar Pandey

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14 min read

Insurance Journeys: Consent for Underwriting, Wellness, and Marketing

How Indian insurers can turn consent into a cross-journey operating capability and select the right consent infrastructure for DPDP, IRDAI, RBI AA and TRAI TCCCPR.
Key takeaways
  • Consent is now a cross-journey operating capability for Indian insurers, shaped simultaneously by DPDP, IRDAI, RBI’s Account Aggregator framework, and TRAI’s TCCCPR.
  • Mapping consent events across underwriting, wellness, and marketing helps define where explicit consent is required and what evidence needs to be logged.
  • A unified consent fabric built around a central ledger, clear purpose taxonomy, and strong integrations is easier to audit and evolve than disconnected, channel-specific consents.
  • Procurement teams should evaluate consent-management options using structured criteria—regulatory alignment, integration readiness, governance, and hidden costs—rather than treating them as generic CX tools.
  • Platforms such as Digital Anumarti - Service can be assessed against the same scorecard as you design DPDP-ready consent journeys for complex insurance stacks.
Imagine your organisation is asked, within a week, to evidence how consent was taken for three different events: a term policy where underwriting relied on medical tests and a bank-statement pull through an Account Aggregator, a health insurance wellness reward issued based on fitness app data, and a cross-sell SMS campaign sent to the same customer base. The Data Protection Board wants to see whether DPDP consent conditions were met, IRDAI is reviewing whether wellness data was used in line with its guidelines, and TRAI is investigating an unsolicited communication complaint. If your only artefacts are scanned proposal forms, disjoint agent scripts, and CRM flags, it becomes a board-level risk rather than an operations issue.
Under the Digital Personal Data Protection Act 2023 and DPDP Rules 2025, insurers act as data fiduciaries for very sensitive financial and health data. Consent for non-obligatory processing must be specific, informed, unbundled by purpose, and as easy to withdraw as to give. Individuals have rights to access, correction, and withdrawal, and the Data Protection Board can test not just the wording of your consent but the systems, logs, and processes behind it. That turns consent from a text clause on a proposal form into an ongoing operating capability that must be designed, implemented, and monitored.[1]
At the same time, sectoral regulators are shaping how consent must work in practice. IRDAI circulars on electronic policies and wellness features govern how digital acceptances, medical disclosures, and wellness enrolments are captured and evidenced. RBI’s Account Aggregator framework defines a standard, revocable consent artefact for financial data sharing that insurers must honour when they act as financial information users. TRAI’s TCCCPR regime requires that your marketing consents and preferences line up with operator-side registers and templates. For procurement and sourcing leaders, this landscape means you are not just buying point tools; you are funding a consent fabric that has to span underwriting, wellness, and marketing journeys while staying auditable across all these regimes.[2]
Before comparing vendors, it helps to map where consent actually appears in your insurance lifecycle. For a typical Indian insurer, the journey runs from lead capture and quotation through proposal and KYC, underwriting and issuance, policy servicing and endorsements, wellness engagement, claims, renewal, and finally cross-sell or exit. At each stage, different types of personal data are collected, combined, and reused, and each use may rely on consent, on another lawful ground under DPDP, or on a sector-specific mandate. A defensible design starts with identifying these touchpoints and deciding which ones must be consent-based and which can be justified on other grounds, then ensuring that your systems can evidence those decisions.
In the lead and quotation phase, most processing is marketing-driven: capturing contact details from websites, aggregators, social campaigns, or call centres; enriching them; and running re-targeting or follow-up. Here the DPDP consent and TRAI TCCCPR regimes are most visible. Prospects should be told clearly whether they are giving details only to receive a quote or also to receive ongoing promotional communication, what channels will be used, and how they can opt out later. If tracking technologies, analytics, or cookies are involved in digital journeys, those consents also need to be captured in a way that can later be linked back to the customer record and policy if the prospect converts.
During proposal, KYC, and underwriting, the processing becomes more mixed. Some activities, such as complying with statutory KYC or anti-money-laundering requirements, may rely on legal obligation or other legitimate-use grounds rather than consent, while others—such as using medical reports from panel hospitals or drawing financial data via an Account Aggregator—are safer and more transparent if based on explicit consent. IRDAI’s stance on electronic proposals and digital signatures means that consent for contract formation and disclosures can be taken digitally, but only if you can prove that the right person saw the right terms at the right time. Once the policy is issued and moves into servicing, you may need fresh consents for new data uses, such as adding family members, porting policies, or enabling electronic servicing channels.
Post-issuance, new consent events arise around wellness programmes, claims, renewals, and cross-sell. Wellness features often involve continuous monitoring and behavioural nudges, which IRDAI expects to be voluntary and subject to confidentiality and purpose limitation, while claims handling can involve pulling sensitive records from hospitals, TPAs, and diagnostic networks. Some of that processing can be justified as necessary to fulfil the insurance contract or regulatory obligations, but reusing claims or wellness data for marketing, cross-sell, or future underwriting typically requires fresh, specific consent. Marketing consents then need to be maintained throughout the relationship and synchronised with TRAI-managed preferences, so that renewal reminders, upsell offers, and dormant-customer campaigns all stay within the boundaries originally agreed.[3]
Lifecycle view of consent events, data uses, and regulatory lenses for Indian insurers.
Lifecycle stage Key data and activities Typical consent or lawful basis focus Regulatory lenses most relevant
Lead capture and quotation Web forms, aggregator leads, call-centre enquiries, tracking and analytics, initial profiling. Marketing consent, cookie/analytics consent, legitimate interest where applicable and defensible. DPDP; TRAI TCCCPR for outbound contact; advertising and platform policies.
Proposal and KYC Detailed proposal data, identity and address proofs, income proofs, declarations, electronic signatures or OTP confirmations. Contract formation and legal obligation for core processing; explicit consent for optional profiling, analytics, or future marketing uses. DPDP; IRDAI circulars on electronic policies and proposal acceptance; KYC/AML regulations.[2]
Underwriting Medical examinations and reports, diagnostic results, financial data via Account Aggregators, external bureau checks, reinsurer referrals. Combination of contractual necessity, legal obligation, and explicit consent for sensitive health and financial data and non-essential reuse. DPDP; IRDAI product and underwriting norms; RBI Account Aggregator directions.[5]
Issuance and servicing Policy document issuance, e-policy delivery, contact and bank updates, endorsements, servicing via branches, agents, and digital channels. Contractual necessity and legal obligation for core servicing; specific consents for new products, channels, or data uses introduced mid-term. DPDP; IRDAI servicing and e-policy norms; TRAI for servicing SMS and calls where applicable.[2]
Wellness engagement Wearable data, app-based fitness and diet logs, teleconsultation records, gym and wellness partner data, reward and incentive tracking. Explicit, granular consent for collection and use of wellness data; clear separation of rewards, underwriting, and marketing purposes. DPDP; IRDAI Guidelines on Wellness and Preventive Features; contracts with wellness partners.[3]
Claims handling Hospital and TPA records, diagnostic and treatment information, financial details for payouts, fraud and investigative checks. Contractual necessity and legal obligation for core claim processing; additional consent where data is repurposed beyond claims and servicing. DPDP; IRDAI claims guidelines; sector-specific health-data confidentiality obligations.[1]
Renewal, cross-sell, and exit Renewal reminders, upgraded cover offers, cross-sell campaigns, win-back programmes, data retention and deletion at end of relationship. Ongoing marketing and profiling consents; respect for withdrawals and objections; retention limits and erasure for data no longer needed. DPDP for consent withdrawal and retention; TRAI TCCCPR for re-engagement communications; IRDAI norms for renewals and portability.[4]
Underwriting is where many insurers first feel the weight of DPDP-era consent, because it brings together proposal data, KYC information, medical records, and sometimes financial data from external sources. Each of these inputs may come with a different legal basis and a different set of regulatory expectations. From a procurement lens, the key question is whether your consent infrastructure can model this complexity and keep a clean, queryable trail of who authorised what, for which purpose, and for how long.
For proposal and health information, IRDAI already allows electronic proposal forms, OTP-based confirmation, and digital policy issuance, provided that specific customer consent and verifiable evidence are captured. Under DPDP, the associated notices must be in clear language, specify each purpose—for example, assessing insurability, sharing data with reinsurers, or using de-identified data for product analytics—and avoid bundling optional uses with mandatory processing for policy issuance. In practice, that means your agent apps, web portals, and call-centre scripts need to trigger consent events rather than just collecting signatures, and your consent platform must log details such as the policy or proposal reference, the lawful basis selected, the text or version of the notice shown, any OTP or digital-signature artefact, channel and device identifiers, and the identity of the intermediary involved.[2]
Third-party data intensifies the need for structured consent. When you order medical tests from empanelled hospitals or labs, or route cases through TPAs or reinsurers, customers should understand which entities will see what data and for which purpose. RBI’s Account Aggregator framework raises the bar further: AA consent artefacts specify data categories, frequency, duration, and the financial information users who will access them, and are explicitly revocable. If your underwriting model relies on bank-statement analysis obtained via an Account Aggregator, you need a system of record that can store that artefact, link it to the specific underwriting decision, and cease further pulls or reuse if the consent expires or is withdrawn.[5]
The high-risk pattern to avoid is treating all of this as a single tick-box at the end of a proposal form that simultaneously approves underwriting, wellness enrolment, cross-sell marketing, and sharing with unnamed third parties. From an audit perspective, that makes it hard to prove that consent was freely given for non-essential uses and almost impossible to respect withdrawal selectively. When drafting RFQs, it is worth asking vendors how their platforms keep core underwriting processing, legally required checks, and optional consents technically and logically separate while still presenting a coherent front-end experience to customers and intermediaries.

Wellness programmes: compliant use of health and behavioural data

Wellness and preventive programmes are attractive for health insurers because they promise better risk outcomes and customer engagement, but they also concentrate some of the most sensitive data an insurer will ever hold: step counts, sleep scores, diet logs, geolocation trails, and telemedicine transcripts. IRDAI’s Guidelines on Wellness and Preventive Features require that such programmes be transparently filed, that rewards and conditions be disclosed, and that data confidentiality and purpose limitation be respected, especially where third-party service providers are involved.[3]
In design terms, the safest pattern is to treat wellness enrolment as separate from both underwriting and marketing. A customer should be able to consent to the collection and use of wellness data to calculate programme rewards without automatically agreeing that the same data will be used to increase or decrease premiums, or to target them with offers unrelated to the underlying policy. Where you do intend to use aggregated wellness scores for underwriting or for cross-sell, those purposes should be clearly named and separately consented, with appropriate alternatives if the customer declines. Each data flow from wearables, fitness apps, gyms, teleconsultation partners, or nutrition services should be tagged with the purposes authorised and with the specific partner agreement that governs its processing, so that responsibility is clear when IRDAI or the Data Protection Board asks who had access to what.
For procurement teams, wellness programmes often reveal hidden costs in the consent fabric. Every wellness partner is, in effect, another data processor or co-fiduciary, with its own APIs, changes, and outage patterns. Your consent solution therefore needs not only to present clean customer-facing choices but also to control and monitor these integrations: stopping data ingestion when consent is withdrawn, ensuring that wellness partners delete or archive data when instructed, and providing a consolidated view of which partners are active for each policyholder. RFQs should probe how vendors handle multi-partner ecosystems, what evidence they can provide that consent withdrawals cascade downstream, and how configuration or onboarding of new partners is billed and supported.

Marketing, re-engagement, and customer preferences under DPDP and TRAI

Marketing and re-engagement are where consent becomes most visible to customers and most tightly scrutinised by TRAI. Under DPDP, using personal data for direct marketing will typically be consent-based, with individuals retaining the right to withdraw consent or object to processing. TRAI’s TCCCPR framework adds further conditions for SMS, calls, and similar channels: headers and templates must be registered on distributed ledger platforms, consents must be recorded in operator-managed registers, and unsolicited commercial communication complaints can trigger investigations. An insurer’s internal marketing-permission flags therefore need to stay in sync with external telecom-side records, or campaigns that look permitted in the CRM can still be treated as violations.[4]
A pragmatic target state is a central preference and consent service that covers all outbound channels—SMS, voice, email, WhatsApp, in-app messages—and links each marketing use back to a defined purpose and lawful basis. Customers should be able to view and change these settings through multiple touchpoints, including portals, mobile apps, branches, and call centres, with the assurance that a change made in one place takes effect across all. Behind the scenes, this requires integrations with your DLT provider, campaign tools, and CRM, as well as a data model that distinguishes clearly between transactional communications required for servicing or regulatory reasons and optional marketing or cross-sell. Where consent is withdrawn, the system should be able to stop future campaigns while still allowing mandatory notices such as policy servicing reminders or claim updates.
In practice, the operational bottleneck is rarely collecting the first consent; it is propagating revocations and preference changes fast enough to be meaningful. Some consent-management deployments in other regulated sectors have used server-side preference centres, event-driven synchronisation, and webhooks to update CRM and campaign platforms instantly when a customer opts out, automatically halting pending WhatsApp or email workflows. When assessing vendors for insurance use cases, it is worth asking whether they can support similar event-driven architectures, how they reconcile internal consent states with TRAI’s consent and preference registries, and what dashboards are available for compliance teams to monitor campaigns against consent scope.
Another commercial wrinkle is joint marketing with bancassurance partners, digital marketplaces, and wellness providers. Each partner may maintain its own view of marketing permissions, yet DPDP and TRAI will look to the entity sending the message and the underlying data fiduciary to honour withdrawals. Hidden costs appear when consent has to be re-collected or normalised at every interface, or when legacy partner contracts do not recognise DPDP-era obligations. It is therefore useful to build into your RFQ a requirement that consent platforms help you tag marketing permissions by origin and partner, provide exportable logs suitable for TRAI dispute resolution, and support clean decommissioning of partner campaigns if the consent basis is challenged.
A unified consent fabric is less a single system than an agreed way of handling consent across journeys, channels, and business lines. In most insurers it consists of a central consent ledger and API layer, integrated into policy administration, distributor tools, mobile and web apps, wellness platforms, CRM, marketing automation, and Account Aggregator connectors. The fabric ensures that there is one source of truth for what a customer has agreed to for underwriting, wellness, and marketing; that this truth is available in real time wherever decisions are made; and that the organisation can reconstruct that truth for regulators and courts years later.
From a design perspective, three elements usually determine whether this fabric is effective. The first is the data model: you need a manageable taxonomy of purposes and processing activities, mapped to DPDP obligations and sectoral rules, so that every consent artefact or legitimate-use decision can be expressed in structured form. The second is event logging: each grant, update, withdrawal, or expiry should be captured with fields such as customer identifiers, policy or proposal references, purposes covered, lawful basis, notice template and language, channel and device information, timestamps, and links to any third-party processors or Account Aggregator consent artefacts. The third is governance: role-based access controls, dashboards for the DPO and compliance teams, workflows for handling rights requests, and version control so that you can show which wording and settings were live at any point in time.[1]
Procurement teams can translate these design points into a vendor scorecard by grouping requirements into a few evaluation dimensions. Under regulatory alignment, you can ask vendors to demonstrate how their data model supports DPDP consent conditions, IRDAI wellness rules, RBI’s AA consent artefacts, and TRAI TCCCPR, and to walk through example insurance journeys showing how core processing and optional consents are separated. Under integration readiness, request details on APIs and SDKs for web, mobile, call centres, and agent tools; support for offline or assisted capture; connectors or patterns for policy administration, CRM, DLT providers, and AA networks; and performance benchmarks at realistic transaction volumes. Under operations and governance, probe auditability, reporting, change-management workflows for updating notice text or adding purposes, training and documentation, and the extent to which configuration can be managed by your own teams rather than custom code. Finally, under commercial and risk, consider vendor financial stability, track record in regulated sectors, data residency posture, and the contractual commitments they are prepared to make around support, incident handling, and regulatory cooperation, without assuming standardised SLAs until they are negotiated.
A structured scorecard also helps you surface hidden costs early. Integration effort can dominate total cost of ownership, especially where legacy policy systems lack modern APIs or distributor portals are run by third parties. Migrating historic consents from paper, PDFs, or fragmented CRMs into a DPDP-ready model often requires data-cleanup projects and may reveal that some legacy consents are not valid for new uses. Change management—writing new notices, retraining agents, updating scripts, and adjusting incentives—tends to be underestimated, yet will determine whether front-line staff actually use the new flows. When considering a build option, the same factors apply: your internal teams will still have to design a consent taxonomy, create audit-grade logging, maintain connectors to AA and DLT ecosystems, and track regulatory change. An explicit discussion with technology, legal, and business owners about ongoing ownership, funding, and metrics can prevent the consent fabric from becoming another under-resourced compliance project.
Illustrative vendor scorecard dimensions for evaluating consent-management solutions in insurance.
Evaluation dimension Insurance-specific focus Sample RFQ question or evidence request
Regulatory alignment Ability to express DPDP consent conditions and sectoral requirements (IRDAI, RBI AA, TRAI TCCCPR) in a structured purpose and lawful-basis model across underwriting, wellness, and marketing. “Show how your data model represents an underwriting journey that uses AA data, medical reports, and reinsurer sharing, and how optional marketing or wellness uses are kept separate from core processing.”
Integration readiness Connectivity to policy admin systems, AA connectors, distributor and agency tools, wellness platforms, CRM, DLT providers, portals, and mobile apps, including assisted and offline journeys. “Provide API and SDK documentation for integrating consent capture into agent apps, web journeys, and call-centre flows, and evidence of performance at our expected daily proposal volume.”
Operations and governance Audit trails, dashboards for DPO and compliance, workflows for updating notices and purposes, handling rights requests, and controlling who can change consent logic in production. “Demonstrate how our DPO could search for all consents relating to a given customer and policy, including withdrawals, and export an audit-ready report without custom development.”
Commercials and risk Total cost of ownership, vendor resilience, data residency and subcontracting posture, and support for regulator interactions, incident response, and change management over time. “Describe the services included in standard support, any additional fees for new integrations or regulatory changes, and how you assist clients responding to regulator or audit queries.”
To make the consent fabric tangible for procurement, it helps to structure the work as a sequence of decisions and evidence requests rather than a single tooling choice.
  1. Map journeys, data uses, and regulators
    Start by aligning business, legal, and technology teams on where consent appears today and where it should appear across underwriting, wellness, and marketing journeys.
    • List key lifecycle stages and associated data sources (policy admin, labs, TPAs, AA connectors, CRM, wellness partners).
    • Classify each processing activity by proposed lawful basis and identify where explicit consent is mandatory or strategically desirable.
    • Note which sectoral regimes are most relevant per stage so RFQ questions can reference the right regulators.
  2. Define your consent taxonomy and evidence standard
    Agree on a common set of purposes, processing activities, and log fields that any solution must support, before looking at vendor feature lists.
    • Draft a purpose hierarchy that separates core servicing and underwriting from optional analytics, wellness, and marketing uses.
    • Specify the minimum consent-log fields your DPO and internal audit will require when reconstructing a decision or customer journey.
    • Translate these requirements into non-negotiable RFQ criteria rather than optional features.
  3. Decide where to centralise and how to integrate
    Determine the scope of the central consent ledger and how it should connect to existing policy, CRM, AA, and DLT components.
    • Identify which systems will call the consent service in real time and which will sync in batch mode.
    • Clarify non-functional requirements such as latency, throughput, and resilience for high-volume proposal or claims periods.
    • Document ownership of each integration so ongoing changes do not stall on unclear responsibilities.
  4. Run a structured RFQ and vendor evaluation
    Use the scorecard to request concrete artefacts rather than generic assurances, and compare build and buy options on the same basis.
    • Ask for walkthroughs of underwriting, wellness, and marketing journeys in a demo environment with consent logs exposed.
    • Request sample implementation plans and partner-integration patterns relevant to your distribution and wellness ecosystems.
    • Seek clarity on configuration versus custom code so you can estimate internal skill requirements and change lead times.
  5. Surface hidden costs and plan a phased rollout
    Treat migration, partner alignment, and training as first-class workstreams, not afterthoughts, and sequence rollout accordingly.
    • Budget separately for legacy consent migration, especially from paper and fragmented CRMs, and confirm how vendors support data quality checks.
    • Review partner contracts and plan how wellness providers, TPAs, and distributors will consume and honour the new consent fabric.
    • Prioritise high-impact journeys—such as electronic proposals and marketing preferences—before extending to complex wellness ecosystems.
Once a consent fabric is live, a few recurring issues tend to surface. Addressing them early reduces regulatory and operational surprises.
  • Audit requests highlight gaps between consent logs and actual decisions. Tighten your evidence standard, make logs append-only or tamper-evident, and ensure proposal or policy identifiers are consistently captured across systems so journeys can be reconstructed quickly.
  • TRAI DLT records and internal marketing flags diverge. Treat the central consent service as the source of truth, implement automated reconciliations with DLT and operator registries, and pause campaigns where discrepancies appear until they are resolved.
  • Agents or branches bypass digital flows using ad-hoc paper forms. Provide assisted digital capture options that work in low-connectivity environments, link incentives to proper use of standard flows, and make non-compliant capture methods clearly out of bounds in procedures and training.
  • Consent withdrawals do not reliably reach downstream processors such as labs, TPAs, or wellness partners. Build event-driven notifications from the consent ledger to partner systems, require technical kill switches in processor integrations, and ensure contracts reflect obligations to delete or restrict processing on withdrawal.
  • Legacy consents and marketing permissions remain inconsistent after migration. Segment migrated records by confidence level, refresh consent for high-risk or high-value cohorts using clear campaigns, and avoid reusing ambiguous legacy permissions for new products or channels.

Where Digital Anumarti fits in an insurer’s consent fabric

Digital Anumarti - Service positions itself as a DPDP Act–oriented consent management platform for Indian organisations, with an API-first architecture, audit trails, and dashboards aimed at regulated sectors such as BFSI and healthcare. In healthcare deployments, for example, it has been used to generate hashed consent receipts alongside diagnostic reports, to tie consent events to specific processor agreements in multi-party lab networks, and to automate the movement of records into restricted storage when consent is withdrawn. For insurers, these patterns translate into requirements such as evidencing consent for underwriting inputs, managing complex webs of wellness partners and TPAs, and keeping marketing preferences synchronised across CRM and communication systems.[6]
From a procurement standpoint, Digital Anumarti - Service can be evaluated as one candidate implementation of the consent fabric described above. You can use the same scorecard you apply to other solutions—covering regulatory alignment, integration fit with your policy and Account Aggregator stacks, operational support, and commercial terms—and ask the team behind it to walk you through insurance-specific reference architectures and sample audit logs. If you want to explore whether this approach fits your environment, it is reasonable to request a technical discovery session via the information provided on digitalanumati.com.

Selected deployment patterns from Digital Anumarti - Service

Digital Anumarti - Service

1

Hashed consent receipts in diagnostic lab deployments

Digital Anumarti - Brand reports diagnostic lab implementations where Digital Anumarti - Service generates secure, hashed consent receipts that are provided alongside final pathology reports to demonstrate that patient data was processed on a lawful basis.

Why it matters for you

Insurers can apply a similar pattern to underwriting, claims, or wellness journeys so that every high-risk data use has a verifiable consent artefact that can be produced quickly for audits or disputes.

2

Linking consent to specific processor agreements

In multi-party diagnostic networks, Digital Anumarti - Brand describes how Digital Anumarti - Service links each patient’s consent directly to the relevant data processor agreements in place with third-party testing facilities.

Why it matters for you

For insurers operating with TPAs, labs, reinsurers, and wellness partners, this linkage can help disentangle data fiduciary and processor responsibilities and show regulators which parties were authorised to access which data.

3

Server-side preference centre with event-driven syncing

Digital Anumarti - Brand highlights a deployment where Digital Anumarti - Service provides a server-side preference centre that uses event-driven syncing and webhooks so that when a person rejects marketing cookies or opts out, downstream WhatsApp and email campaigns are halted immediately.

Why it matters for you

A similar architecture can help insurers keep TRAI-governed marketing campaigns aligned with real-time consent state, reducing the risk of unsolicited communication complaints.

4

API-driven consent ledger integrated with core systems

In one specialised clinic, Digital Anumarti - Brand reports that Digital Anumarti - Service’s API-driven consent ledger was integrated directly with the Electronic Health Records system to digitise consent capture and mapping.

Why it matters for you

For insurers, equivalent integrations with policy administration and claims systems are critical so that underwriting and servicing decisions always reference the same authoritative consent ledger.

5

Automated handling of consent revocation

Digital Anumarti - Brand describes deployments where, on consent revocation, Digital Anumarti - Service triggers a cascading update that moves records from active operational databases into encrypted cold-storage retention logs, removing them from active processing while preserving them for legal obligations.

Why it matters for you

This pattern is directly relevant to DPDP withdrawal rights in insurance, where policy and claims data may need to be restricted for new uses without breaching sectoral retention duties.

6

Breach-readiness and consent-linked cohort isolation

According to Digital Anumarti - Brand, one clinic deployment of Digital Anumarti - Service includes data-flow mapping tied to the consent ledger to support 72-hour breach readiness by enabling rapid isolation of affected user cohorts.

Why it matters for you

For insurers handling high volumes of sensitive health and financial data, similar consent-linked cohort views can help the DPO respond faster and more precisely to incidents involving only certain products, partners, or consent scopes.

Evidence Healthcare case study – diagnostic labs
Once the idea of a consent fabric is on the table, stakeholder questions tend to cluster around scope, sequencing, and ownership. Business teams may ask whether every data use now needs explicit consent and whether the added friction will hurt conversion. Compliance and legal teams may worry about reconciling DPDP with existing IRDAI guidelines, TRAI obligations, and contractual commitments to partners. Technology leaders often want clarity on whether consent should be embedded into each channel or centralised as a shared service, and how to handle legacy consents that pre-date DPDP.
In practice, the most sustainable answers balance regulatory expectations with operational pragmatism. Not every processing activity requires consent if it is clearly covered by contractual necessity or legal obligation, but those that do require consent must be treated rigorously, with a clear separation between core and optional uses. A central consent fabric with well-designed APIs usually gives you more flexibility than embedding bespoke consent logic in every channel, because it lets you update notices, purposes, and templates once and propagate them consistently. Many insurers therefore start by rationalising marketing permissions and electronic proposal journeys, then extend the same infrastructure to wellness and complex underwriting data sources as patterns mature. The remaining questions—about legacy data, partner ecosystems, and internal accountability—are best handled through a multi-disciplinary working group supported by procurement’s structured evaluation of solution options.
FAQs

DPDP distinguishes between consent and certain legitimate uses, such as processing necessary for the performance of a contract or to comply with law. Many core underwriting activities—collecting information the proposer volunteers in the proposal form, obtaining KYC documents where required, or evaluating risk to price the policy—may be justifiable on those grounds, provided customers are clearly informed. However, optional uses such as enriching profiles from external sources, using data for future cross-sell, or feeding detailed health or financial information into analytics beyond underwriting usually require specific consent. A practical approach is to work with legal and compliance teams to classify each underwriting data item by lawful basis, then configure your consent platform so that these bases are captured and logged alongside the data, rather than defaulting to consent for everything.

A defensible consent log lets you reconstruct, for any given customer and decision, what was known and agreed at the time. At a minimum, that usually includes identifiers for the individual and, where applicable, the proposal or policy; the purposes covered and their lawful bases; the full text or version identifier of the notice presented; timestamps with time zone; the channel and device or system through which consent was captured; any authentication artefacts such as OTPs, digital signatures, or account log-ins; references to the staff member, intermediary, or distributor involved; links to any third-party processors or Account Aggregator consent artefacts; and subsequent events such as updates, withdrawals, or expiries. For auditability, it helps if this log is append-only or otherwise tamper-evident, and if you can export coherent views for regulators, internal audit, and partner due diligence without bespoke data work each time.

Legacy consents captured before the DPDP Act and Rules may not meet today’s standards for clarity, specificity, and ease of withdrawal, especially where broad marketing or data-sharing clauses were inserted into generic terms. Rather than assuming they remain valid for all purposes, many organisations take a risk-based approach: continuing to rely on them for core contractual processing where there is no reasonable doubt, but not for optional uses such as cross-sell or expanded analytics until refreshed consent is obtained. Operationally, that means inventorying where and how past consents are stored, mapping them into your new consent fabric, flagging those that fall short for marketing or wellness purposes, and planning customer-friendly re-permissioning campaigns. Your RFQ can ask prospective vendors how they support this migration, including tools for mapping, quality checks, and customer communication.

Because consent touches every journey, clear internal ownership matters as much as tooling. In many insurers, policy and regulatory interpretation sit with the Data Protection Officer and compliance function, while responsibility for practical implementation is shared between technology, digital, distribution, product, and marketing teams. One workable model is to designate a senior business sponsor for the consent fabric—often in operations, digital, or customer experience—supported by a steering group that includes the DPO, CIO or CTO, and representatives from underwriting and marketing. Procurement’s role is then to ensure that vendor contracts, service descriptions, and governance forums reflect this shared ownership, so that changes in law, product design, or channels can be translated into updated consent flows without ad hoc projects.

A phased rollout reduces risk and helps build internal confidence. Many insurers start where the regulatory and reputational stakes are highest and the journeys are relatively contained, for example by harmonising marketing consents and TRAI DLT registrations and by standardising electronic proposal and acceptance flows. The next phase often addresses complex underwriting data sources—labs, TPAs, Account Aggregators, and reinsurers—using the same consent data model and ledger. Wellness programmes, with their rich partner ecosystems and continuous data, are sometimes tackled once the core fabric is stable, so that each new partner can plug into existing patterns. Throughout, it is important not to overlook agency and branch channels; your consent infrastructure should support assisted capture from the beginning so that offline journeys do not lag behind digital ones.

Sources
  1. The Digital Personal Data Protection Act, 2023 - Government of India – India Code
  2. IRDAI Guidelines on Wellness and Preventive Features - TaxGuru (reproducing IRDAI circular)
  3. Regulatory framework for account aggregators - Bank for International Settlements / Reserve Bank of India
  4. DPDP norms nudge insurance firms to boost tech systems, consent frameworks - Business Standard
  5. TRAI curbs unwanted commercial calls, mandates subscribers' consent - Business Standard / IANS
  6. Promotion page

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 Updated At May 31, 2026

Consent Token vs JWT: Designing Permission-Aware Systems

For Indian B2B engineering leaders: a practical comparison of consent tokens vs JWT claims, and how to design DPDP-aligned, permission-aware architectures with revocation, purpose limitation, and auditability.

 Updated At May 18, 2026

What Evidence Do You Need to Defend Consent before the DPB?

Executive guide for Indian leadership teams on evidence needed to prove valid consent under the DPDP Act before the Data Protection Board and how to embed it into operations.

 Updated At May 18, 2026

What Counts as a Reasonable Security Safeguard under DPDP?

A strategic guide for Indian CXOs on how DPDP’s “reasonable security safeguards” duty translates into concrete controls, governance, vendor oversight, and audit-ready evidence.

 Updated At May 24, 2026

Webhooks for Consent Withdrawal and Downstream Sync

Technical guide for Indian engineering leaders on webhook-based consent withdrawal and downstream sync under the DPDP Act, covering architecture, reliability, security, and auditability.

 Updated At Apr 18, 2026

How to Map Data Flows Before Implementing a Consent Platform

A business-style technical guide for technical evaluators that covers how to map data flows before implementing a consent platform, implementation details, and