Data Clean Rooms for Financial Services Brands

Financial services marketers are facing a tidal wave of challenges. Not only are consumer expectations continually on the rise, but we are truly at a historic crossroads for the advertising ecosystem. As LiveRamp’s CEO Scott Howe recently shared, “We are on the verge of rebuilding the digital advertising ecosystem from one built around the third-party cookie to one that puts consumer privacy and transparency at the forefront.” So how can financial services companies streamline compliance and improve the customer experience? Industry-leading solutions to maximize consumer interaction opportunities leverage neutral, regulatory-conscious, privacy-centric data clean rooms. 

What is a data clean room for financial services?

Before we dig into a few of the potential, powerful use cases for clean rooms, let’s make sure we are speaking the same language. So what are data clean rooms?

Simply put, data clean rooms are safe and neutral spaces for collaboration and partnerships to exist without either party (or parties) having direct access to each other’s customers’ directly identifiable personal data. 

A data clean room grounded in a deterministic data approach helps you:

• Facilitate a safe and secure environment to unite disparate data sets
• Focus on organizing, analyzing and measuring data
• Provide privacy controls and data encryption
• Ensure data never leaves the data owner’s control
• Enable the sharing of data across enterprises and internal business units

How data clean rooms work for financial services brands

Financial services brands – from insurance to banking to credit card providers – are exploring the opportunities that data clean rooms provide. With data clean rooms, they can:

Connect key data sources

Connect data seamlessly across clouds, warehouses, and clean rooms. Key data sources could include customer data, transactions, merchant data, credit-related sources, brand partner data (such as co-brand or private label), and media partner data.

Access data securely

Give internal and external data science teams secure and safe access to the right data so they can answer big, important questions such as how to optimize spend or improve in-market audience performance.

Measure your impact

Drive channel campaign measurement – across digital, programmatic, TV, premium publisher and co-brand partner – predictive analytics, and audience activation: with a unified view of customers, the right data clean room can empower financial services marketing teams to do all of these things and more.

Want to make the power of data clean rooms even more real and tangible? Let’s explore three use cases where data collaboration can unlock new possibilities for a financial services marketing team.

How financial services brands can benefit from clean rooms

Activate and measure credit-informed prospecting campaigns seamlessly

For lenders and financial institutions, credit-informed strategies like pre-screened credit offers are often a core part of the marketing strategy. By setting up a data clean room strategy, teams have the opportunity to access multiple credit-related data sources from a single environment. 

This means workflows are streamlined, data movement minimized, and latency reduced. Better yet, response data can flow back into the data clean room, enabling the marketing team to conduct closed-loop analytics in near real time. This allows financial services marketers to unlock a data flywheel where continuous activation, analytics, and optimizations are possible with all of the right data finally centralized. 

Identify the right cross-sell and upsell for each customer

It’s well known among advertisers that the cost of acquiring a new customer is more expensive than simply retaining or growing an existing one – up to seven times more expensive, in fact. Enter data clean rooms to supercharge in-market capabilities.

With a single view of customers, marketers can follow them along their purchase journey and the brand touchpoints they have experienced. From there, teams can analyze historical transaction data augmented with valuable second- and third-party data sources in order to quickly build or adjust predictive models and audiences that answer questions such as:

• What’s the next best product to offer?
• What type of messaging theme should be used?
• What channel or channels will work best for delivering this offer?
• How many advertising touchpoints will drive incremental impact?

Brands can connect these audiences to the places where the data matters most, whether it be other internal applications, marketing tools, or media partner destinations. 

Develop and share profiles across the business

Financial services companies face just as many barriers to data sharing internally as they do externally. For instance, depending on the line of business (LOB), it may be illegal to share raw, individual-level customer data. With these types of walls in place, financial services brands often feel like they got the short end of the stick when it comes to comprehensive customer insights. 

Data clean rooms can especially help data science teams overcome this hurdle. With a data clean room, data from multiple LOBs can flow into the environment. Not only is it connected, but it’s stripped of personally identifiable information (PII) and can even be enriched with other data sources. The end result? Rich, responsibly crafted audience profiles to optimize targeting, product strategy, offers, and overall channel strategies.

Mitigate fraud risk

Fraud is on the rise and financial services brands are doing the best they can to defend against this modern-day bank robbery. In addition to new tools and technology, data is at the heart of any financial service company’s fraud and risk defense system. 

A data clean room can enhance a financial services brand’s in-market fraud mitigation capabilities by enabling the alignment of all relevant data sources, including:

• Know Your Client (KYC) data sources
• Core banking AML data, which combines information on retail and commercial parties, including their accounts and transactions and the detailed information risk cases related to these parties
• Supplementary fraud alerts
• Additional key identifiers 

With all of this information securely connected in a data clean room, sharper predictive analytics and real-time triggers become possible. 

Myth vs. Reality: Data clean rooms for financial services

If you are just ramping up your knowledge of data clean rooms, there is a good chance you may have a misconception or two about them. Let’s dispel the most common myths here.

Unlock new possibilities in financial services with data clean rooms

We’re in an exciting time. Many financial services companies are not only exploring all of the possibilities that data clean rooms deliver, but they are seeing the results. For instance, a large global insurance company worked with LiveRamp to improve ROAS by more than 200% through optimized modeling and targeting, ultimately increasing both visitor and conversion rates. 

These are the kind of the results that data clean rooms can deliver by:

Offering safe and secure environments with native integrations to the leading cloud providers.

Enabling flexible, controlled collaboration for financial services brands to use the data that matters most from credit bureaus, transaction networks, co-brands, and private-label partners.

Delivering enterprise-level impact by helping functional business teams across marketing, data science and analytics, risk and fraud, product, and M&A. 

A Single Platform for All of Your Activation, Measurement, and Collaboration Needs

In January 2024, LiveRamp acquired data clean room software provider Habu. LiveRamp CEO Scott Howe shares how the acquisition is accelerating adoption and collaboration across our vast partner network.