– Earnings Call Scheduled for 8:00 a.m. ET on August 14, 2026 –

SHENZHEN, China, Aug. 5, 2026 /PRNewswire/ — RLX Technology Inc. (“RLX Technology” or the “Company”) (NYSE: RLX), a leading global branded e-vapor company, today announced that it will report its unaudited financial results for the second quarter ended June 30, 2026, before the U.S. markets open on Friday, August 14, 2026.

The Company’s management will host an earnings conference call at 8:00 AM U.S. Eastern Time on August 14, 2026 (8:00 PM Beijing/Hong Kong Time on August 14, 2026).

Dial-in details for the earnings conference call are as follows:

Participants may choose between the English and Chinese simultaneous interpretation options above when joining the conference call. Please note that the Chinese simultaneous interpretation option is in listen-only mode. Participants should dial-in 10 minutes before the scheduled start time and ask to be connected to the call for “RLX Technology Inc.” using the appropriate English or Chinese Participant Code above.

Additionally, a live and archived webcast of the conference call will be available on the Company’s investor relations website at https://ir.relxtech.com.

A replay of the conference call will be accessible approximately two hours after the conclusion of the call until August 21, 2026, by dialing the following telephone numbers:

About RLX Technology Inc.

RLX Technology Inc. (NYSE: RLX) is a leading global branded e-vapor company. The Company leverages its strong in-house technology, and product development capabilities and in-depth insights into adult smokers’ needs to develop superior e-vapor products.

For more information, please visit https://ir.relxtech.com.

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SOURCE RLX Technology Inc.

Financial Crime Intelligence Company Debuts Hybrid Threat Central™ Platform

SIOUX FALLS, S.D., Aug. 5, 2026 /PRNewswire/ — Section 2, Inc., today announced its launch as an AML and financial crime intelligence company along with Hybrid Threat Central™ (HTC), a platform built to identify the criminal networks behind financial crime rather than the individual transactions they generate.

An important aspect of Section 2’s approach is a focus on false negatives — the criminal actors and transactions that slip through undetected, in contrast to the false positives that dominate industry conversation. A single missed detection can cost an institution millions of dollars once regulatory penalties and remediation are factored in, with remediation costs alone running roughly 12 times the amount of the original fine.

Despite massive AML spending, confiscation and recovery rates remain below 1% globally. The reason is the overwhelming number of alerts, and manual teams’ inability to stay ahead of the volume. A modern transaction monitoring system at a regional institution generates alerts at a rate that outpaces analyst capacity by approximately 50:1.

To solve the problem, Section 2 is introducing Hybrid Threat Central™ (HTC), a platform built to identify the criminal networks behind financial crime rather than the individual transactions they generate. It is built on Hybrid Threat Finance™ (HTF™), a patent-pending methodology developed by founder and CEO Debra Geister over more than a decade of work in AML and fraud detection.

“Every AML officer knows the number, even if they’ve learned not to say it out loud: somewhere around 1% of illicit financial flows get caught by the global anti-money-laundering apparatus,” Geister said. “Banks spend billions of dollars a year on transaction monitoring, and the detection rate hasn’t meaningfully moved in 20 years. The problem isn’t effort. It’s that the industry has been monitoring transactions when it should be identifying actors.”

From transactions to actors

Traditional transaction monitoring systems generate alert volumes that outpace analyst capacity, according to Section 2, producing false-positive rates estimated at 85% to 95% while an estimated 98% of financial crime goes undetected. The firm estimates the financial industry spends more than $200 billion annually on compliance, investing largely in manual reviews that cannot keep up with the massive number of alerts.

Section 2 said the core flaw is a unit-of-analysis problem: transactions are cheap for criminal networks to generate and abandon, while the underlying business model and network entity behind them are far more durable and far harder for criminals to change. The company uncovers the bad actors and their networks.

HTF addresses that by extending the traditional three-stage AML model — placement, layering and integration — to five stages, adding revenue generation, where criminal proceeds originate, and operational sustainment, where threat actors reinvest to fund ongoing activity.

The platform

Hybrid Threat Central™ is powered by three components, according to the company:

TENet™ (Threat Entity Network), a continuously updated library of financial crime targeting packages built on the HTF™ methodology and covering all five stages of the financial crime lifecycle, delivered via API or SFTP into a bank’s existing transaction monitoring system.TRACC™ (Threat Risk Assessment Command Center), which overlays threat intelligence with an institution’s own risk profile to identify exposure and prioritize which TENet™ packages to deploy.HTF Assist™, an analyst investigation layer that produces investigation-ready case candidates structured for suspicious activity report (SAR) filing.

The platform is built on Google Cloud infrastructure, with Vertex AI powering its machine learning layer. Section 2 designed HTC to be an intelligence layer, not a replacement system — it works alongside an institution’s existing transaction monitoring infrastructure rather than requiring a rip-and-replace. In one deployment alongside an existing transaction monitoring system, Section 2 found that TENet™ reduced false positives from 94% to 18%.

Addressing national priorities and the effectiveness rule

The Section 2 platform is designed to help institutions respond to the Financial Crimes Enforcement Network’s (FinCEN) eight government-wide AML/CFT priorities: corruption, cybercrime, terrorist financing, fraud, transnational criminal organizations, drug trafficking, human trafficking and smuggling, and proliferation financing.

The company also pointed to the “effectiveness rule,” a standard under the U.S. Federal Sentencing Guidelines and the Department of Justice’s Evaluation of Corporate Compliance Programs. Under that standard, a written compliance program is not sufficient on its own; institutions must show their programs are actively working, adequately funded and capable of preventing, detecting and correcting violations to receive legal and sentencing credit. Section 2 said actor-level attribution gives institutions a clearer way to demonstrate the outcomes regulators now expect, rather than alert volume alone.

Built on a decade of investigative practice

Section 2’s Special Investigations Unit (SIU), a team of career intelligence, law enforcement and financial services compliance professionals, serves as the human-in-the-loop oversight behind the platform, the company said. The unit keeps Section 2’s threat actor and typology databases current, produces the whitepapers and case studies that back the platform’s findings, and reviews every classification before it reaches a customer, so that outputs remain sourced, defensible and examiner-ready. The SIU also provides specialized investigation support directly to partners on complex cases requiring deep-dive research.

About Section 2

Section 2, Inc. is a financial crime intelligence company founded by Debra Geister, a three-decade veteran of the AML and fraud detection industry. Geister began her career building foundational detection systems at LexisNexis in the years following the USA PATRIOT Act and later oversaw global compliance functions for major financial institutions before founding Section 2. She has worked as a practitioner in all facets of AML — CIP/IDV, KYC, sanctions, and AML operations. The result is the company’s Hybrid Threat Finance™ methodology and Hybrid Threat Central™ platform which are designed to shift financial crime detection from isolated transactions to the criminal networks and business models behind them.

More information is available at section2.com.

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SOURCE Section 2

The Datarails AI Transformation Package joins wave of forward deployed engineering (FDE) initiatives at Microsoft and OpenAI

NEW YORK, Aug. 5, 2026 /PRNewswire/ — Datarails, the AI-native financial operating system for the CFO’s Office, today launched the AI Transformation Package, a service that embeds a dedicated Forward Deployed Financial Engineer (FDFE) inside a customer’s finance team to build custom AI workflows directly in their Datarails FinanceOS environment.

The launch follows a wave of forward deployed engineering (FDE) initiatives at companies like Microsoft and OpenAI, as tech giants invest billions to deploy technical talent inside customer organizations. Datarails is bringing that model to a function it says those efforts have largely skipped: the CFO’s Office.

The move is backed by recent research which found that nearly one in three finance jobs (31%) now requires AI skills, up from one in four a year ago – outpacing teams’ ability to hire or build against that demand. Moreover, independent research from the Financial Education & Research Foundation (FERF) found that only 15% of organizations consider themselves well or fully prepared to support advanced analytics and AI initiatives.

“You cannot parachute a generalist engineer into finance and expect trustworthy output, which is why we have seen vast demand in the market for finance engineers embedded inside of finance teams,” said Didi Gurfinkel, CEO and co-founder of Datarails. “Our FDFEs have decades of experience on finance teams, which they now bring to bear as they work directly with customers to build bespoke solutions on top of the FinanceOS that underpins their AI efforts. This ensures that all outputs – from Claude, Gemini or ChatGPT – are accurate, governed, repeatable and auditable.”

The service is designed for teams with limited bandwidth but ambitious automation goals; organizations that want to fast-track AI adoption without requiring a lengthy and expensive IT project; and finance leaders who want to increase team output without adding headcount.

Each engagement pairs a customer with an FDFE for 25 hours per quarter across a four-phase model – Discover, Build, Deploy, Evolve – designed to reach a live production workflow within the first quarter.

The AI Transformation Package is now available to existing Datarails customers: https://lp.datarails.com/ai-implementation-services.

About Datarails
Datarails is the AI finance operating system for teams across FP&A, cash management, and month-end close. Uniting financial and operational data, FinanceOS is the trusted data layer for finance teams ensuring every AI output is accurate, governed, repeatable and auditable. It lets users stay within Excel and a web-based platform, transforming the CFO’s office into the home of business insights.

Media Contact
datarails@concrete.media

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SOURCE Datarails