A flat consent setup works for a single-product startup. For a multi-product enterprise, it lets consent bleed across businesses in ways the DPDPA does not allow.
June 2026 · 7 min read
Most consent management setups assume a single product, a single user base, and one set of purposes. For a startup with one product, that model works fine. For an enterprise running multiple products, business units or brands — each with its own data flows and its own relationship with users — a flat, undifferentiated consent setup creates more problems than it solves.
Take a fintech group running a payments app, a credit card product and a wealth-management platform under one entity. From a DPDPA standpoint, that is three separate compliance obligations sitting inside one legal entity, not one obligation covering three products. A user's consent to personalised marketing on the payments app should not silently extend to cross-selling on the wealth platform. A collection point on the credit card application should not be visible to a DPO whose remit only covers the payments business.
The useful mental model here is to treat each product, application, business unit or service line as its own top-level "asset" — a self-contained unit holding everything tied to that product's compliance posture: its collection points, its purposes, its Data Principal records, its consent history, its audit trail. For the fintech example above, that would look roughly like this:
A Data Principal's marketing consent on the payments product stays scoped to that asset. It does not automatically extend to the credit or wealth product. Cross-selling across products needs its own, separately scoped consent flow. This is the only configuration that genuinely satisfies Section 6's specificity requirement once an enterprise runs more than one product.
A DPO can be granted visibility into one or more specific assets, rather than the whole platform by default. The payments DPO sees payments data; the wealth DPO sees wealth data; a central privacy office retains the unified view across everything. That mirrors how compliance responsibility is actually structured inside most large organisations.
A deletion request filed against the payments app should not trigger deletion of someone's credit card data. Segregating by asset keeps rights workflows executing against the correct scope of data, rather than sweeping across the whole enterprise by default.
If the Data Protection Board audits a specific product, or a sector regulator like the RBI or SEBI requests documentation for credit or wealth specifically, you need an audit trail scoped to that exact product. Asset-based structuring produces product-specific evidence as the default output, not something assembled under time pressure after the request lands.
Any automated compliance checks — justification adequacy, data minimisation, purpose bundling and the rest — can be run and reviewed per asset, so each product effectively carries its own compliance scorecard rather than one blended number across the whole enterprise.
One consequence worth being explicit about: a single person who holds both a payments account and a credit card with the same group is, functionally, two separate Data Principals in a properly segregated consent setup — one under each asset. Their consent records stay independent, their rights requests get handled separately, and their data maps stay scoped to the respective product. That is not a limitation of the model — it is the compliance architecture actually working as intended.
Segregating consent by business line is an architecture decision, not a configuration toggle — our consent architecture design service is built around exactly this kind of multi-product structuring.
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