Beyond the Score: How Alternative Data Transforms Credit Decisions
Traditional models often overlook large groups of borrowers, leaving lenders with blind spots and limiting access to credit. To explore how this can change, we recently hosted a webinar together with Scoreplex and GiniMachine, diving into the role of alternative data, explainable AI, and automation in modern lending.
During the conversation, our speakers looked at what “alternative data” really means in practice and why it’s more than just additional fields in an application form. They discussed how digital footprints, device usage, and telco behavior can reveal patterns traditional credit files miss, and how these insights help lenders reach new segments while keeping risk under control.
The session also touched on growing regulatory pressure for transparency in credit scoring and showed how lenders can build explainable, compliant models without slowing down operations. Denis Khromov, CEO of Scoreplex, explained how structured data signals give lenders deeper visibility into financial behavior, while Mark Rudak, Product Owner at GiniMachine, demonstrated how no-code AI makes advanced scoring accessible to teams without technical backgrounds.
For those who couldn’t attend, the full video is now available below.
Both technologies are already embedded into HES LoanBox, creating a full-stack solution that combines data enrichment, credit scoring, and automated decision-making in one platform.
