TransUnion and Actable Prove AI Success Starts with Data: Partnership Delivers 10% Lift in Predictive Modeling

Rhea-AI Summary

TransUnion (NYSE: TRU) and Actable announced a partnership that improved AI-driven marketing predictions by integrating TransUnion’s TruAudience Marketing Solutions data into Actable’s models. The collaboration delivered a 10% improvement in model fit and a 19.5% reduction in false positives for a retailer win-back use case. The dataset covers 98%+ of the U.S. population with >700 demographic attributes and >15,000 behavioral signals, which the companies say filled data gaps and improved targeting for high-cost tactics like catalogs and paid media.

The project focused on re-engaging customers who now buy from competitors; companies highlighted broader potential use cases including prospecting, site visitors with limited data, and luxury categories with long buying cycles.

Positive

• Model fit improved by 10%
• False positives reduced by 19.5%
• Data coverage of 98%+ of U.S. population
• 700+ demographic attributes and 15,000+ behavioral signals

Negative

• Results demonstrated on a single retailer win-back use case
• No quantified revenue or ROI figures provided for shareholders

News Market Reaction

+1.83%

1 alert

+1.83% News Effect

On the day this news was published, TRU gained 1.83%, reflecting a mild positive market reaction.

Data tracked by StockTitan Argus on the day of publication.

Key Figures

Price change: -1.28% 52-week range vs high: -17.03% Model fit improvement: 10% +5 more

8 metrics

Price change -1.28% 24h move prior to AI partnership news

52-week range vs high -17.03% Price vs 52-week high of 101.19

Model fit improvement 10% Lift in predictive modeling from TRU–Actable collaboration

False positives reduction 19.5% Lower false positives in AI-driven audience targeting

Population coverage 98%+ U.S. population coverage of TransUnion identity graph

Demographic attributes 700+ Number of demographic attributes in TruAudience dataset

Behavioral signals 15,000+ Behavioral signals available for AI marketing models

Common shares outstanding 194,200,000 Figure cited in Form 144 filing

Market Reality Check

Price: $86.22 Vol: Volume 1,589,421 is below...

normal vol

$86.22 Last Close

Volume Volume 1,589,421 is below the 20-day average of 2,005,794 (relative volume 0.79) normal

Technical Price 83.96 is trading below the 200-day MA at 85.41

Peers on Argus

TRU was down 1.28% with mixed peers: FDS -1.74%, MORN -0.84%, NDAQ -0.62% weaker...

TRU was down 1.28% with mixed peers: FDS -1.74%, MORN -0.84%, NDAQ -0.62% weaker, while CBOE +1.35% and MSCI +0.37% gained, pointing to stock-specific rather than broad sector momentum.

Historical Context

5 past events · Latest: Jan 08 (Positive)

Pattern 5 events

Date	Event	Sentiment	Move	Catalyst
Jan 08	Product/pricing update	Positive	+4.0%	2026 mortgage pricing framed as lowering costs for homebuyers.
Jan 05	Executive appointment	Positive	+4.3%	Appointment of EVP Global Consumer Solutions to drive TruEmpower strategy.
Dec 23	Board changes	Positive	-1.3%	Two directors with strong AI and cloud backgrounds added to board.
Dec 10	Credit outlook	Neutral	+3.7%	2026 forecast of modest credit card balance growth and stable delinquencies.
Dec 09	Fraud solution upgrade	Positive	-1.0%	Enhancements to Device Risk solution to improve fraud detection capabilities.

Pattern Detected

Recent news skewed positive, with three prior announcements seeing gains and two declines, indicating generally constructive but occasionally contrarian reactions.

Recent Company History

Over the past months, TransUnion has highlighted several strategic developments. On Dec. 9, 2025, it enhanced its Device Risk solution to combat fraud, followed by a Dec. 10, 2025 2026 Consumer Credit Forecast projecting $1.18 trillion in credit card balances and generally stable delinquencies. Governance and leadership evolved with two new board members on Dec. 23, 2025 and a new EVP of Global Consumer Solutions on Jan. 5, 2026. A Jan. 8, 2026 mortgage pricing update focused on lower homebuyer costs. Today’s AI-focused marketing partnership aligns with this broader data-and-AI strategy.

Market Pulse Summary

This announcement highlights TransUnion’s strategy of using broad, enriched datasets to power AI-dri...

Analysis

This announcement highlights TransUnion’s strategy of using broad, enriched datasets to power AI-driven marketing. The Actable collaboration yielded a 10% improvement in model fit and cut false positives by 19.5%, supported by coverage of 98%+ of the U.S. population and 15,000+ behavioral signals. In context of recent AI-focused board and leadership additions, investors may watch for revenue impact, additional use cases, and further commercialization updates.

Key Terms

machine learning models, identity graph, data enrichment, behavioral signals, +2 more

6 terms

machine learning models technical

"By integrating TransUnion’s TruAudience... into Actable’s machine learning models"

Machine learning models are computer programs that learn patterns from past data to make predictions or decisions without being explicitly programmed for each task. For investors, they matter because they can improve forecasting, automate routine work, reduce costs or introduce new risks; think of them as a smart assistant that learns from past results like a chef refining recipes, helping businesses spot opportunities or mistakes faster.

identity graph technical

"TransUnion’s identity graph and enrichment capabilities provide the single source of truth"

An identity graph is a structured map that links different identifiers—like email addresses, device IDs, and customer records—to the same person so a business can recognize and track that customer across channels. For investors it matters because it improves how accurately companies target customers, measure which marketing drives sales, detect fraud and value customer relationships, affecting revenue efficiency and regulatory or privacy risk.

data enrichment technical

"identity resolution, seamless connectivity, and data enrichment will be best positioned"

Data enrichment is the process of improving raw data by adding missing details, correcting errors, and linking it to reliable external information so the data becomes more complete and usable. For investors, enriched data makes company figures, customer behavior, and risk signals clearer—like labeling and sorting a messy toolbox so you can quickly find the right tool—helping with better analysis, valuation, compliance, and faster, more confident decisions.

behavioral signals technical

"covering 98%+ of the U.S. population, with 700+ demographic attributes and 15,000+ behavioral signals"

Behavioral signals are measurable actions or patterns from customers, users, employees or market participants—such as clicks, purchases, login frequency, product returns, search activity, or trading volume—that reveal underlying preferences, intentions or changes in activity. Investors watch these signals as early clues about a company’s future revenue, growth or risk, like noticing footprints on a trail before the crowd arrives; they can flag rising demand, declining engagement, or shifts in sentiment sooner than quarterly reports.

third-party intelligence financial

"This partnership demonstrates how third-party intelligence can unlock better outcomes"

Third-party intelligence is information or analysis about a company, market, technology, or risk that comes from an outside, independent source such as research firms, consultants, data providers, or regulatory filings. Investors use it as an outside check or extra set of eyes—like an independent expert opinion or background check—to validate claims, spot risks or opportunities, and reduce reliance on a single source of information, which helps inform buy/sell decisions and risk assessments.

AI-driven marketing technical

"10% improvement in model fit for AI-driven marketing predictions"

AI-driven marketing uses computer programs that learn from customer data to choose what messages to show, when, and to whom—like a smart personal shopper that learns preferences and suggests the best offers. For investors, it matters because it can lower customer acquisition costs, improve sales conversion and predict trends more quickly, so companies using it can grow revenue faster and allocate marketing budgets more efficiently.

AI-generated analysis. Not financial advice.

As marketers race to adopt AI, new results underscore the critical role of a strong data foundation in driving real business outcomes

CHICAGO, Jan. 14, 2026 (GLOBE NEWSWIRE) -- TransUnion (NYSE: TRU) today announced breakthrough results from a collaboration with Actable, a leader in predictive intelligence for marketers. By integrating TransUnion’s TruAudience® Marketing Solutions dataset into Actable’s machine learning models, the partnership achieved a 10% improvement in model fit for AI-driven marketing predictions.

The project focused on a win-back use case for a major retailer seeking to re-engage customers who now buy from competitors, a notoriously costly and data-scarce challenge. With TruAudience Marketing Solutions data filling critical gaps within the AI model, Actable reduced false positives by 19.5%, to improve audience targeting and enable more efficiency for high-cost marketing tactics, like catalogs and paid media.

Read the full findings in TransUnion’s What Does AI-Ready Really Mean?

“AI isn’t magic, its output is only as good as the information it's given,” said Brian Silver, EVP of Global Marketing Solutions at TransUnion. “Garbage in, garbage out still applies. These results prove that when you start with a strong data foundation, AI can deliver meaningful lift and real ROI.”

Why Data Matters for AI
Poor data quality and fragmented identity undermine predictive performance. TransUnion’s identity graph and enrichment capabilities provide the single source of truth AI systems need—covering 98%+ of the U.S. population, with 700+ demographic attributes and 15,000+ behavioral signals.

“TruAudience data proved most powerful where knowledge gaps exist,” said Matt Greitzer, Co-Founder of Actable. “This partnership demonstrates how third-party intelligence can unlock better outcomes for marketers.”

Business Impact and Future Applications
The enhanced model enables more efficient allocation of marketing resources, particularly for expensive win-back campaigns. Beyond churn reduction, the collaboration identified promising future use cases, including:

• Site visitors with limited data
• Prospecting for new customers
• Luxury goods and brands with long buying cycles, where behavioral signals are weak
  

As AI adoption accelerates, marketers who invest in identity resolution, seamless connectivity, and data enrichment will be best positioned to realize its full potential.

Learn more about TransUnion’s Identity Solutions here.

About Actable
Actable’s Intelligence Factory turns raw customer analytics into structured intelligence that powers activation, predictive insights, and measurable business results.

About TransUnion (NYSE: TRU)
TransUnion is a global information and insights company with over 13,000 associates operating in more than 30 countries. We make trust possible by ensuring each person is reliably represented in the marketplace. We do this with a Tru™ picture of each person: an actionable view of consumers, stewarded with care. Through our acquisitions and technology investments we have developed innovative solutions that extend beyond our strong foundation in core credit into areas such as marketing, fraud, risk and advanced analytics. As a result, consumers and businesses can transact with confidence and achieve great things. We call this Information for Good^® — and it leads to economic opportunity, great experiences and personal empowerment for millions of people around the world. http://www.transunion.com/business

Contact	Dave Blumberg
	TransUnion
E-mail	david.blumberg@transunion.com
Telephone	312-972-6646

FAQ

What improvement did TransUnion and Actable report for AI marketing models on Jan 14, 2026 (TRU)?

They reported a 10% improvement in model fit for an AI-driven marketing win-back use case.

How much did false positives change after integrating TruAudience data (TRU)?

False positives fell by 19.5%, improving audience targeting for high-cost tactics.

What U.S. coverage and data scale does TransUnion claim for TruAudience (TRU)?

TransUnion cites coverage of 98%+ of the U.S. population with 700+ demographic attributes and 15,000+ behavioral signals.

Which marketing use cases did the TransUnion–Actable partnership highlight (TRU)?

The work focused on a retailer win-back campaign and noted prospecting, site visitors with limited data, and luxury buying cycles as future uses.

Will the TransUnion–Actable results directly increase TRU revenue in 2026?

The announcement details model and targeting improvements but does not provide quantified revenue or EPS impact.

How do the TransUnion–Actable results affect marketers using expensive tactics (TRU)?

Improved model fit and lower false positives aim to boost efficiency for costly tactics like catalogs and paid media.