Just the essentials: get the datapoints financial services brands need to make better decisions

If you’re leading marketing at a financial services brand—credit unions, regional banks, fintech lenders, mortgage providers—you already know how critical data is to keeping your funnel moving. You’ve built strong programs to generate leads, pre-qualify applicants, and feed loan officers. But there’s always another level of efficiency and ROI to unlock when you have richer context on the households you’re targeting.

Think about prioritizing applications in the call center: better data means fewer unqualified prospects, more productive reps, and stronger portfolio growth. That’s where Faraday comes in.

The Faraday data platform

To take your efforts further, you don’t just need more data—you need the right data, delivered in a way that’s immediately usable across your CRM, loan origination system, and campaigns.

That’s where Faraday’s three-part data platform comes in:

• Identity completion: Fill in the blanks with verified names, addresses, emails, and phone numbers so every record maps to a real household.
• Consumer data: Tap into the Faraday Identity Graph (FIG), which includes over 1,500 responsibly sourced datapoints covering 240M U.S. adults and households. These datapoints span demographics, lifestyle, property, and behavioral attributes that make segmentation, targeting, and prioritization easy—even before layering on custom predictions.
• Custom predictive datapoints: AI-trained scores built on your own history—like Likelihood to Refinance, Default Risk Proxy, or ValueScore—so you can prioritize and personalize at scale.

Essential data packages

One way we make the consumer data layer easier to use is by curating industry essential data packages: sets of 20 datapoints that we’ve determined to be most predictive for your industry. We identify these datapoints using our Faraday predictor leaderboard, which ranks datapoints by their predictive power in each particular industry vertical. For financial services, these packages are tuned to help you qualify applicants, segment portfolios, and drive smarter outreach.

• How they’re chosen: We analyze all 1,500+ datapoints in the FIG and surface the ones with the strongest predictive signals for your vertical. That way you get the attributes that matter most, without paying for data you don’t need.

• How they’re delivered: Essential data packages show up just like any other Faraday datapoint—directly appended to your records in your CRM, call center platform, or lead management system in real time through our API or in scheduled batch. No extra setup required.

• How they’re different: Most data vendors hand you a pile of raw attributes. Faraday packages are curated, validated, and aligned to your outcomes. Our data is high-quality, responsibly sourced, and refreshed regularly—and we take on the work of figuring out what’s actually useful for you.

The financial services essential data package

Here’s what’s included in the standard package for financial services brands:

Data Trait	Description
Approximate household income tax rate	Approximate tax bracket for the household, assuming head of household is filing
Home market value v2.0	Estimate of home market value
Household income	Median numeric value of narrow-band income
Living area	The finished square meters of the house
Living Area Square Feet (actual)	Indicates the square footage of the entire living area of the home (minus basement, garage, etc.)
Low/moderate income	True if a household qualifies as low or moderate income for their region under HUD guidelines
Mortgage liability	Primary property mortgage
Property Lot Size in Acres (actual)	Acreage representing entire property; square footage of lot (43,560 square feet = 1 acre)
Single-family household or townhouse	Category of domicile
Year built	The year that the house was originally built (see "Effective year built" for last extensive remodel)
Lifecycle - millennials	This lifecycle segment contains households with adults born between 1981 and 2002
Dwelling type	Advantage-class property type categorization
Homeowner or renter probability	Designation of person-to-property relationship (renter vs. owner), with probability
Mail Order Donor	Household donates through mail order
Net worth	Value equals household asset minus liabilities
Shopping styles	Household's preferred mode of shopping
Home market value trigger	Indicates the home market value has increased or decreased
Credit Score Proxy	Ranking that approximates household credit health, available in 5 or 12 buckets

These datapoints give you immediate visibility into whether a lead or applicant is likely to be a fit for your business, before your loan officers ever pick up the phone.

Why this matters

When you add these essentials to your leads and customer records, you:

• Save money by rejecting unqualified applicants earlier in the funnel.
• Increase conversions by prioritizing the right households for your products.
• Boost efficiency by making sure your reps and loan officers aren’t wasting time on poor fits or low-probability approvals.
• Prove ROI to the CFO with data-driven evidence that marketing spend is driving real portfolio growth.

Smarter data, real results

Industry essential data packages are how Faraday makes your records AI-ready, without heavy lifting from your team. Combined with verified identity completion and custom predictive datapoints, they give you the full modern data stack your financial services brand needs to compete.

Ready to see how these datapoints can transform your funnel? Get in touch with Faraday!