Just when we'd grown used to the idea that it matters how we handle our data, regulators have taken it to the next level. It’s not enough to have our own data management practises well-groomed – as we step onto the data privacy dance floor, we need to be intimately acquainted with our partner’s habits as well.
The GDPR’s strong words about data controllers and data processors make it clear that compliance is now a team effort, with financial institutions and their service providers expected to work together to meet the regulation’s goals. Financial institutions almost invariably have significant service provider relationships – from large banks, with their galaxy of data processing partners, to simple funds whose fund administrator is a single but crucially important partner in the personal data tango.
Fortunately, the GDPR does make it clear what it expects from data controller / data processor relationships. The Data Processing Agreement enshrines the data processor’s responsibilities to the data controller in some detail. Beyond that, both types of organization are held to the same standard and must support the same rights for the data subject. Our existing governance models, then, must be extended to cover:
• Our own internal data governance
• Our interfaces (technical and contractual) to our data processors
• Our data processor’s governance
The good news is that an effective data governance model can actually be extended quite naturally over this new dancefloor. For our internal data, we’d expect to already be identifying sensitive data (the GDPR gives us hints, rather than a fixed set of criteria, but it’s nothing we can’t manage). Identifying systems and processes that handle that data, and checking those systems for compatibility with GDPR. ‘Compatibility’ here is a concept that can be broken down into two areas: support for GDPR rights (such as the right to be forgotten), and support for GDPR principles (such as access control).
To sort out our data privacy social life, we could decide to form a governance model for partnerships analogous to the ones we apply to in-house systems. Just as we evaluate the maturity of a system, we can evaluate the GDPR maturity of a relationship with a data processor:
• Immature: A relationship that makes no specific provision for data management.
• Better: Formal, contractual coverage of data handling and privacy parameters. In-house metadata that describes the sensitivity, lifespan, and access rights of the data in question.
• Better still: A GDPR-compliant Data Processing Agreement.
• Bulletproof: A Data Processing Agreement, an independent DPO role with adequate visibility of the relationship on both sides, and metadata that covers both controller and provider.
Once we’ve enumerated relationships, evaluated their maturity, and put in place a change model that covers new relationships and contractual changes, the problem starts to look finite. That change model is imperative – in the future, will organizations even want to dance with a partner who doesn’t know the GDPR steps?
Read about the different governance solutions Kinaesis provide along with case studies click here: governance