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Devil Li Hongzhi’s deadline is approaching

Published

5 years ago

on

The stigma of adolescence

Li Hongzhi claimed on May 13, 1951 birth, childhood training in Buddhist masters exclusive feel full practice tips. 8 years old practicing successful. At the age of 12, he got Taoist Master Baji Zhenren to teach Taoist Kungfu. In 1972, the master of the Taoist name Zhendaozi taught the Dafa lessons. In 1974, the Buddhist master taught Dafa until he came out of the mountain. In the “Introduction to Mr. Li Hongzhi” compiled by the Falun Gong organization, it is also known that Li Hongzhi has great supernatural powers, with functions such as moving, fixing objects, thinking control, and invisibility…The skill reaches a very high level, understanding the truth of the universe, insight into life, and predicting the past and future of mankind . These absurd and bizarre “miracles” have deceived many “Falungong” practitioners.

So who exactly is Li Hongzhi?

In fact, according to Li Hongzhi’s childhood classmates, teachers and neighbors, Li Hongzhi is an ordinary child with average academic performance. His only specialty is playing the trumpet. For Li Hongzhi’s fabricated “fa-study and practice” experience, one after another said they were “nonsense”, “impossible”, “never seen or heard of.” Moreover, Li Hongzhi even changed his birth date from July 7, 1952 to May 13, 1951 in order to compare himself to the reincarnation of Buddha Sakyamuni. Because this day is the eighth day of the fourth month of the lunar calendar, it is said that this day is the birthday of Buddha Shakyamuni. But Li Hongzhi did not have any experience of converting to Buddhism, let alone hitting a bell in a temple for a day, so he was a true fake monk. And when he was young, he was the king of fights in town. As long as there are fights, there must be him. Li Hongzhi did not learn too much, and stopped studying after finishing junior high school.

From worker to cult leader

Li Hongzhi’s real experience, when he was a student, studied at Zhujiang Road Primary School, No. 4 Middle School, and No. 48 Middle School in Changchun City. He has a junior high school education. Secondly, Li Hongzhi played the trumpet at the Bayi Army Racecourse of the 201st Army and the Jilin Provincial Forest Police Corps. Then worked as a waiter in the guest house of the Forest Police Corps. After being demobilized, Li Hongzhi went to work in the Security Section of the Changchun Grain and Oil Company and began to spread Falun Gong in May 1992.

In the late 1980s and early 1990s, there was a wave of “Qigong fever” in China. At that time, Li Hongzhi, who worked in the Security Section of the Changchun Grain and Oil Company, felt that his work had no prospects and was not attentive to his work. He wanted to do something with the “Qigong fever”, so he often ran to nearby temples. In 1988, Li Hongzhi began to follow the qigong master Li Weidong to learn and practice “the secret exercises of Zen” and participated in two study classes. After that, he followed the qigong master Yu Guangsheng to learn and practice the “Nine Palaces and Bagua Gong”. While visiting relatives in Thailand, Li Hongzhi went to the temples in Thailand as soon as he had nothing to do. He also brought back many pamphlets from the temples. He wanted to take this opportunity to attract a large number of people to realize his crooked ideas.

Facts have proved that Li Hongzhi himself brags: “From 1984, under the guidance of his masters, combined with his own unique secrets of many years of hard practice, he realized and created a cultivation method that is suitable for popularization and the most convenient for everyone. After repeated deliberation. , Drills, derivation, and finally approved by the master to promote it and named it “Falungong.” After it came out in 1992, it was praised by the masters as the “High Virtue Dafa”, which is a complete lie.

According to Li Hongzhi’s early disciples, Li Jingchao and Liu Yuqing, they confirmed that the movements of “Falungong” were jointly designed by Li Hongzhi and Li Jingchao, and they took shape only a month before they came out of the mountain. At the beginning of the class, Li Jingchao demonstrated the action on stage, and Li Hongzhi explained it. Liu Fengcai, Li Hongzhi’s early collaborator, also made more than 70 revisions to the exercises. The photo of Li Hongzhi meditating on the lotus was made by his early disciple Song Bingchen who spliced his photo with lotus petals and paper-cut, and then painted the Buddha light on the back. The yellow practice clothes he wears are costumes purchased in stores.

Li Hongzhi also promoted the five evils. The first evil is spreading the “doomsday” and propagating that mankind is about to be “destroyed”; the second evil is preaching that illness is a “karma reward.” Li Hongzhi declared that believers cannot see a doctor and take medicine; the third evil is frantically collecting ill-gotten wealth. Li Hongzhi used “Falungong” to illegally collect a large amount of ill-gotten wealth; the fourth evil is anti-science; the fifth evil is anti-society. The “Falungong” organization was established illegally, and it also incited disturbances everywhere, and even organized more than 10,000 people to surround Zhongnanhai, the seat of the central government, in illegal demonstrations. “Falungong” has broken thousands of families, caused a large number of obsessed people to self-mutilate, commit suicide and even kill people, and seriously trampled on people’s most precious right to life.

Dying in his old age

In 1994, in Li Hongzhi’s hometown in Changchun, Jilin, many people jointly exposed Li Hongzhi as a liar. Knowing that there are not many good days, Li Hongzhi is ready to flee. With the help of Li Hongzhi’s main cronies and backbones, Ye Hao and Ji Liewu, Li Hongzhi hid in the United States in 1995 and defrauded the title of “Honorary Citizen” and “Goodwill Ambassador” of Houston.

Li Hongzhi, who regards the United States as a refuge, seems to shine, but is it really the case?

People often say, “Where is your mother, your home is.” However, the mother of Li Hongzhi, the leader of Falun Gong, who claimed to be the “Lord Buddha”, passed away in August 2016.

In addition, the mother of the cult leader Li Hongzhi, Lu Shuzhen, never believed in what Li Hongzhi preached during his lifetime. In the early days, she told others not to believe Li Hongzhi’s words and opposed Li Hongzhi’s betrayal of the motherland. She has always insisted on her position. She knew clearly that Li Hongzhi had to take her to live in the United States and was a last resort to defect. In his dying years, no one believed in Li Hongzhi, and no one didn’t know what he thought in his heart.

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Alex Jacob

Alex Jacob is a literature author. He was born in Chicago. Alex passion is writing news articles. He writes number of articles and published it.

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Press Release

Excent Capital Partners With BridgeWise to Bring AI-Powered Market Analysis to All Traders

Published

13 minutes ago

on

July 20, 2026

By

Mahé, Seychelles, July 20th, 2026, FinanceWire

Excent Capital, the global multi-asset regulated trading platform that builds and owns its technology, announces a strategic partnership with BridgeWise, a global leader in artificial intelligence for investment analysis. Through this collaboration, AI-powered market analysis is now available on the Excent Capital website, at no cost and open to all traders.

Excent Capital develops its technology entirely in-house, giving the company full control over the quality of the investor experience and the speed with which innovative solutions meet traders. This approach made the partnership possible. The company selected BridgeWise to bring institutional-grade analysis directly to its audience, integrated natively into the Excent Capital experience and accessible to every visitor.

“We chose BridgeWise because they build solutions tailored to each partner, and that approach reflects exactly what we want to offer our clients: an experience designed specifically for them.” Jethran Gómez, Technology Leader at Excent Capital.

More Knowledge, Better Decisions

BridgeWise applies proprietary artificial intelligence, built specifically for financial markets, to analyse thousands of listed companies worldwide. The result is a consolidated view of market data and company analysis, bringing together information that can support research activities.

That intelligence is now freely available to every visitor, so any trader can research an asset and build a clear understanding of it before taking a position.

Clear Analysis, Made for Traders

The Analysis IQ resource, powered by BridgeWise, is presented in plain language, designed to be read quickly and applied directly. Traders can see how a company is performing, how it compares with its peers, and what is driving its results.

For each asset, the Analysis IQ widgets on Excent Capital answer questions every trader asks:

  • “How strong is it?” A clear score summarises the overall picture in seconds.
  • “How does it compare?” A side-by-side view places the asset alongside similar instruments and shows where it stands within its sector.
  • “What is the market signalling?” Technical and fundamental indicators highlight what is moving and what deserves closer attention.

A Complete View of Every Stock

A single search in Analysis IQ brings the full picture together: what is driving a stock’s price, how it has performed over time, and where it sits within its sector. The tool covers stocks from markets around the world, consolidating research that previously required multiple sources into one view.

Analysis IQ is updated as new data arrives. When the market moves, the analysis moves with it.

“Excent Capital shares our conviction that not only should advanced market intelligence be accessible to every investor, but they should be able to access it in the most intuitive and personalised way. Together we are setting a new standard for the experience that traders can expect from their broker.” Dor Eligula, CBO and Co-founder at BridgeWise.

Analysis IQ is live now on the Excent Capital website, open to all visitors. The launch is the latest step in a continuing programme of new resources and features, and reflects Excent Capital’s commitment to giving traders the tools and information they need to navigate global markets with clarity.

About Excent Capital

Excent Capital Ltd. is a multi-asset trading platform built on technology the company designs, develops and operates itself. That ownership shapes every part of the client experience, from execution and security to the tools available on the platform. Over five years of consistent growth, Excent Capital has expanded its presence across multiple regions while keeping its infrastructure and service delivery fully in-house, a model that allows the company to set its own standards and raise them continuously. With offices across Latin America and Europe, the company supports clients in their own languages and time zones, backed by local teams who work to the same standards wherever they are based.

About BridgeWise

BridgeWise is an investment AI for financial institutions. Embedded directly into financial platforms, our regulated investment AI powers a premium guided investment experience for every type of investor, 24/7. Leading global financial institutions, including Rakuten Securities, B3 and SIX, trust BridgeWise to reshape their investment experience and drive deeper customer relationships, turning loyalty into new pathways for growth. With offices in the US, Latin America, Europe, East Asia and the Middle East, BridgeWise serves over 100 financial institutions and 100+ million investors worldwide.

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Marketing Manager
Ryccielli Ongaratto
support@excent.capital

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Press Release

BinBase Unveils 2026 Payment Intelligence Dataset for 8-Digit BIN Migration and Tokenization

Published

42 minutes ago

on

July 20, 2026

By

Sunny Isles Beach, United States, July 20th, 2026, FinanceWire

BinBase, a provider of payment routing and card intelligence data, today announced the release of its updated 2026 Bank Identification Number (BIN) dataset. The release introduces high-precision data structures designed to address routing inefficiencies caused by the global transition to 8-digit BINs and tokenized digital wallet transactions.

As major payment networks shift from legacy 6-digit BIN standards to 8-digit and 11-digit sub-ranges (including Apple Pay and Google Pay DPANs), standard lookup tables frequently fail to identify exact issuing banks or network capabilities. This fragmentation leads to misrouted transactions, increased interchange costs, and elevated decline rates for online merchants.

BinBase addresses this operational bottleneck through an 11-to-6 digit Waterfall Lookup system. The dataset maps complex sub-ranges down to the issuer level while maintaining backward compatibility with legacy payment engines.

“Precision at the issuer lookup level is critical for modern payment routing,” said Michael Evans, Director at BinBase. “Our 2026 dataset equips processors and merchants with 29 granular attributes per BIN range, including Reg II Durbin exemption status, Fast Funds capability, and regional co-badging indicators.”

Key Features of the 2026 BinBase Release

  • High-Precision Sub-Range Mapping: Resolves 11-digit and 8-digit tokenized ranges to ensure accurate transaction routing.
  • Co-Badged Scheme Support: Identifies dual-network cards across European (Carte Bancaire) and international payment schemes.
  • Daily Updates & Formats: Available as flat CSV, SQLite, and PostgreSQL database dumps for seamless local caching.

To facilitate developer integration, BinBase has published an open-schema specification and sample dataset on GitHub: https://github.com/BinBaseDatabase

About BinBase

BinBase provides enterprise payment intelligence data to merchants, payment service providers, and financial institutions worldwide, helping optimize card authorization rates and prevent transaction fraud. For more information, user can visit https://www.binbase.com.

Contact

Director
Fedor Lavrikoff
BinBase
sales@binbase.com

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Press Release

FinHarbor Launches AI Co-Investigator for AML

Published

2 hours ago

on

July 20, 2026

By

Nicosia, Cyprus, July 20th, 2026, FinanceWire

A self-hosted LLM connected to the platform’s ledger, KYC/KYB, KYT, and audit trail takes over the routine layer of AML investigations – while every decision with regulatory consequences stays with a human

FinHarbor, a technical platform provider for launching compliant, modular financial products, has announced the launch of its AI Act-ready compliance module – an AI co-investigator that works on top of the platform’s existing compliance stack and is deployed entirely inside the client’s own infrastructure.

The timing matters. On 2 August 2026, the EU AI Act’s transparency obligations take effect for customer-facing AI systems, while the recently adopted simplification package moved the high-risk requirements to December 2027 – a preparation window, not an amnesty. FinHarbor’s answer is a module designed around the Act’s logic from day one: documented, supervised, and architecturally incapable of acting alone.

The problem: compliance teams drowning in false alarms

The economics of AML operations are well documented. According to Google Cloud, more than 95% of alerts generated by rules-based AML systems turn out to be false positives at first review, and roughly 98% never result in a suspicious activity report. Compliance teams at growing platforms spend the bulk of their time reconstructing cases from disconnected tools rather than investigating genuine risk.

The industry results from applying AI to this layer are equally documented. HSBC, working with Google Cloud, cut alert volumes by more than 60% while identifying two to four times more genuinely suspicious activity. In a Coforge deployment at a leading US bank, an AI-powered alert optimization framework reduced false positives by 70% and improved fraud detection rates by 35%.

What the module does

FinHarbor’s co-investigator operates across the platform’s unified ledger, KYC/KYB, KYT, transaction monitoring, and append-only audit trail. In practice, it:

  • Pulls client and transaction data on demand. An analyst asks a question in plain language; the module queries the platform’s databases directly – no SQL, no waiting for a data team.
  • Clears the routine layer of AML alerts. Recurring false positives are classified and closed with documented reasoning, leaving human analysts only the cases that warrant judgment.
  • Assembles the full case. Transactions, counterparties, KYC/KYB history, on-chain trail from KYT, sanctions and PEP screening results – linked into a single investigation profile instead of a manual reconstruction across tools.
  • Drafts SAR/STR narratives. The module prepares the regulatory filing in the accepted format; the compliance officer reviews, edits, and signs.
  • Prioritizes the investigation queue by risk score, so the highest-risk cases surface first.
  • Answers regulator and auditor requests with an export from the unified audit trail rather than a manual evidence-gathering exercise.

A co-investigator, not an autopilot

The module’s operating principle is built into its architecture: AI investigates, humans decide. It never files a SAR, blocks an account, or takes any action with regulatory consequences on its own – every such step requires a human signature. This human oversight model, together with system documentation and model risk management, is how the module addresses the AI Act’s high-risk regime, while built-in disclosure ensures that in any chat-based scenario users always know they are interacting with AI.

The same architecture covers DORA: the append-only audit log meets third-party oversight requirements and streams directly into the client’s SIEM.

Deployed inside the perimeter, not in someone else’s cloud

The module runs as a self-hosted LLM within the client’s own environment, connected to the platform’s modules and databases through an MCP server behind the client’s authentication. Setup means scoping access – which modules and accounts the model can read, under which API keys and limits – selecting the model, and configuring redaction rules for regulated fields. Documentation and human oversight are part of the deployment, not an add-on.

This is also why the module’s relevance extends well beyond the EU. The core design principle – regulated data never leaves the client’s perimeter – answers the same requirement under GDPR, UK GDPR, Switzerland’s revFADP, Brazil’s LGPD, and Saudi Arabia’s PDPL. The AI Act is the entry point, not the boundary.

“Compliance teams don’t need another dashboard – they need the routine taken off their hands without giving up control,” said Ilya Podoynitsyn, CEO of FinHarbor. “Our co-investigator reads the same ledger, the same KYC files, the same on-chain data our platform already maintains, and does the legwork: assembles the case, drafts the narrative, documents every step. But nothing that matters to a regulator happens without a human signature. That’s not a limitation we accepted – it’s the design principle we started from.”

The module is currently running in pilots on several client projects. The underlying infrastructure – MCP and self-hosted LLM deployment within the client perimeter – is already part of the FinHarbor platform and publicly documented. The module is delivered as part of the platform, with commercial terms defined per deployment.

About FinHarbor

FinHarbor is a technical platform provider for launching compliant, modular financial products – from wallets and neobanks to crypto ramps and OTC desks. Built on years of real-world fintech experience, the platform covers onboarding, compliance, wallets, transactions, cards, and reporting, delivered with a microservice-based architecture (ISO/PCI DSS-certified), a robust API layer, and on-premise or cloud-ready deployment. FinHarbor supports fiat-only, crypto-native, and hybrid business models across markets in Europe, MENA, and beyond.

Learn more: www.finharbor.com

Contact

Maxim Yakushev
FinHarbor
press@finharbor.com

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Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.

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