Behavioral signals
Transform consented digital interaction patterns into structured risk indicators that can complement traditional underwriting inputs.
Financial Services Product
More context when traditional data is limited.
Credit bureau, income, application and transaction data remain important. But digital-first and thin-file customers can leave gaps that make confident underwriting difficult.
Zollal Digital Risk Intelligence adds a complementary layer of consent-based behavioral and device signals that can be translated into risk indicators and used alongside your existing decision framework.
Core capabilities
Behavioral Risk Signals
Transform relevant device interaction and behavioral metadata into structured indicators that can enrich a digital risk profile.
Alternative-Data Scoring
Complement bureau, application and financial information with additional digital signals for more informed decisioning.
Thin-File Assessment
Add decision context for new-to-credit or digitally acquired customers where traditional history may be limited.
Fraud & Anomaly Indicators
Surface unusual patterns and risk signals that can support existing fraud, onboarding and review controls.
Segmentation & Prioritisation
Use risk and behavioral indicators to support portfolio segmentation, lead prioritisation and differentiated customer journeys.
API / SDK Integration
Integrate risk outputs into digital onboarding, lending platforms, decision engines, CRM or analytics environments.
Designed to complement—not replace—your existing risk model.
The solution is intended as an additional decision input. Customers can combine digital risk indicators with their own credit policy, bureau data, affordability rules, fraud controls and manual-review processes.
Consumer FinanceDigital LendingBNPLFintechBanksThin-file Customers
Consent, governance and controlled use.
Digital risk programs should be implemented with clear customer consent, approved data-use rules, security controls and documented decision governance. Zollal can help integrate the risk signals into a controlled operating model aligned with the institution's legal, privacy, compliance and credit-risk requirements.