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Blend and Prove cut application drop-off by 16% for banks and credit unions. August 13, 2026 Key takeaways. 16% fewer abandoned applications: Financial institutions using Blend's integration with Prove Pre-Fill reduced application drop-off by an average of 16%. 54% less manual data entry: The integration securely pre-populates verified personal information, cutting the fields applicants must complete themselves by 54%. Faster, more reliable onboarding: Applicants are verified through their mobile devices, accelerating account opening while reducing errors and improving confidence in customer data. Security without added friction: Blend and Prove position identity verification as both a fraud-prevention measure and a way to create a simpler customer experience. Better conversion from existing traffic: By turning more applicants into account holders, banks and credit unions can support account growth and improve returns on their digital marketing investments. The modern way of proving identity. Trusted by 2500+ leading companies to reduce fraud and improve consumer Read the article: Turning Vision Into the Internet's Trust Infrastructure Turning Vision Into the Internet's Trust Infrastructure Prove's 2026 Inc. 5000 recognition reflects its growth and leadership in persistent identity management, deterministic identity, and trusted AI agents. August 12, 2026 Read the article: The Missing Layer in Agentic AI The Missing Layer in Agentic AI Learn how merchants can prepare for agentic commerce by verifying AI agents, securing checkout authorization, and structuring product data for LLMs. August 12, 2026 Read the article: Attackers Have Industrialized the Moment of Urgency: The Hidden Cost of OTP Nobody Talks About Attackers Have Industrialized the Moment of Urgency: The Hidden Cost of OTP Nobody Talks About Discover the hidden costs of SMS OTPs, from fraud and failed delivery to customer abandonment, and how passkeys and persistent authentication reduce risk. August 3, 2026 Ready to get started? Talk to an expert today. Trusted by 2,000+ leading companies to reduce fraud and improve consumer experiences, Prove is the world's most accurate identity verification and authentication platform.

Blend Labs: Q2 earnings snapshot. August 6, 2026, 5:37 PM NOVATO, Calif. (AP) - NOVATO, Calif. (AP) - Blend Labs Inc. (BLND) on Thursday reported a loss of $1.5 million in its second quarter. The Novato, California-based company said it had a loss of 3 cents per share. Earnings, adjusted for stock option expense and amortization costs, were less than 1 cent on a per-share basis. The cloud-based platform for financial companies posted revenue of $33.8 million in the period. For the current quarter ending in September, Blend Labs said it expects revenue in the range of $31.5 million to $33.5 million. In the final minutes of trading on Thursday, the company's shares hit $1.95. A year ago, they were trading at $3.58. This story was generated by Automated Insights (http://automatedinsights.com/ap) using data from Zacks Investment Research. Access a Zacks stock report on BLND at https://www.zacks.com/ap/BLND

CrossCountry Mortgage pushes faster closings with Blend integration. May 20, 2026 Managing Editor Lender says new workflow cuts cycle times by more than half, underscoring growing pressure on speed in purchase-driven market CrossCountry Mortgage is rolling out a new digital mortgage workflow with Blend that the lender says can cut closing times by more than half, positioning faster turn times as a key differentiator for retail lenders as borrowers, real estate agents, and sellers place greater emphasis on certainty and timelines. The integration streamlines key parts of the origination process, including borrower application, document collection, verification, and underwriting workflows. The goal is to reduce manual touchpoints and compress the time between application and clear-to-close. For mortgage professionals, the development reflects a broader operational shift already underway across the industry: lenders are investing heavily in automation and workflow technology to eliminate bottlenecks that slow down loan production. While CrossCountry Mortgage did not specify a standardized baseline for comparison, the claim of cutting closing times "by more than half" suggests a significant reduction in cycle time relative to prior internal processes. The lack of detailed benchmarks, however, leaves open questions about how the improvement compares to broader industry averages or existing fast-close programs. What it means. For LOs, faster closings can translate directly into competitive advantage. In a market where purchase transactions dominate and inventory remains constrained, the ability to close quickly can help win offers and strengthen relationships with referral partners. Get the NMP Daily Essential stories, every weekday. Shorter cycle times may also improve pull-through rates and reduce fallout, while allowing LOs to handle more volume without proportionally increasing workload. At the same time, the shift toward more automated workflows could reshape how LOs interact with borrowers and internal operations teams. As more of the process becomes digitized, the LO role continues to move toward advisory and relationship management rather than manual file shepherding. Industry-wide pressure on speed. CrossCountry's move comes as lenders across channels - retail, broker, and non-QM - look for ways to reduce fulfillment costs and improve efficiency amid ongoing margin compression. Speed to close has emerged as one of the few remaining areas where lenders can clearly differentiate, particularly as pricing competition remains intense and refinance activity subdued. Technology platforms like Blend are increasingly central to that effort, enabling lenders to consolidate workflows, automate verifications, and reduce friction in the borrower experience. For independent mortgage banks and smaller lenders, the move adds to the pressure to modernize technology stacks or risk falling behind competitors that can deliver faster, more predictable closings. *This article was drafted with AI assistance and reviewed and edited by a human editor before publication.