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Finance Track · Invitation-Only Strategic Co-Build

Turn Your Finance Expertise
Into Industry-Wide Standards

Years of accumulated Risk Control models, Investment Research systems, Compliance reviews, customer service SOPs... They used to be just your internal assets. Now, they can become "Finance AI Standards" that the entire industry pays to use. KHB provides computing power, technology, and teams; you provide knowledge, data, and scenarios. Strategic Joint Venture to co-build AI infrastructure for the Finance industry.

3T+
China FinTech Market Size in 2026
70%
Financial Institutions Lack In-House AI Capabilities
1 Slot
Only 1 Slot Left in This Track

Five Core Challenges in the Finance Industry

The Finance industry is at a critical juncture of digital transformation and AI empowerment. Top institutions hold valuable Risk Control, Investment Research, and Compliance experience, yet face deep challenges of talent scarcity, high costs, and difficulty in knowledge retention.

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Scarce Risk Control Talent, Long Model Iteration Cycles

Top Risk Control experts are hard to find — training a mature Risk Control modeler takes 5+ years. Risk Control model iteration for new businesses and scenarios often takes 3-6 months, far behind market changes. Institutions constantly face the dilemma of risk exposure versus business growth.

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High Compliance Review Volume, Costly and Inefficient Manual Audits

Financial regulation is becoming increasingly strict, and Compliance review workloads for credit approval, anti-money laundering, and investor suitability management are growing exponentially. Relying on manual review is not only costly but also inefficient and inconsistent, risking regulatory penalties at any time.

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Top Investment Research Expertise Cannot Be Retained, Reliance on Star Analysts

Top brokerages and fund companies have accumulated over a decade of Investment Research frameworks, stock selection logic, and industry analysis methodologies, but they all reside in the minds of star analysts and fund managers. When key personnel leave, Investment Research capabilities decline sharply, and knowledge assets cannot be institutionally preserved.

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High Customer Service Labor Costs, Limited Response Speed

Scenarios like wealth management, retail banking, and insurance customer service require massive manpower investment, making 24/7 service difficult to guarantee. Slow customer consultation response, inconsistent professionalism, difficulty improving customer satisfaction, and persistently high labor costs.

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Small and Medium Financial Institutions Have Weak AI Capabilities, Difficult Digital Transformation

City commercial banks, rural commercial banks, small and medium brokerages, and regional insurers lack AI technology teams and computing infrastructure. Digital transformation faces high technical barriers, large investments, and talent shortages. They want to embrace AI but don't know where to start.

Core Contradiction: Top financial institutions have data, scenarios, and knowledge accumulation, but lack large-scale AI engineering capabilities and computing infrastructure; AI companies have technology and computing power, but lack deep Finance industry knowledge, Compliance experience, and implementation scenarios. Both sides fight independently, causing Finance AI to remain at the "shallow application" level, unable to truly drive industry transformation.

Four Values, Redefining Industry Influence

Co-building Finance AI infrastructure with KHB is not just a technology upgrade — it's a strategic positioning move. You will evolve from an "industry participant" to an "industry rule-maker."

01

Define Industry Standards — From Financial Institution to Rule-Maker

Jointly release the Finance AI Risk Control Specification, and lead the establishment of a Finance AI alliance. Your Risk Control model becomes the Industry Standard, and your Compliance process becomes the benchmark for the entire industry. While other institutions are still "competing on Compliance," you're already defining what "Compliance" means. This is not a simple technology upgrade, but a strategic positioning of industry influence. Once standards are established, all financial institutions in the industry will follow the rules you define, and your institution will become the industry-recognized benchmark and leader.

02

Monetize Knowledge Assets — Generate Passive Income from Experience

Your accumulated years of Risk Control models, Investment Research systems, Compliance experience, customer service SOPs... These used to be just "internal assets," but now they can become licensable, chargeable, and replicable industry Knowledge Bases. Small and medium financial institutions across the industry will pay for your knowledge, and your expertise will no longer be lost when personnel leave, but will continuously generate "passive income." Imagine: thousands of financial institutions nationwide, each using the Risk Control standards and Compliance rules you define, every call generating revenue for you.

03

Capability Leap — Reduce Costs, Increase Efficiency, Strengthen Moat

No need to build your own AI team, no need to invest hundreds of millions in hardware — directly access the industry's top AI capabilities. 10x Risk Control efficiency improvement, 90%+ Compliance automation rate, scalable Robo-Advisor, 24/7 full coverage of customer service, significantly reduced operational costs, and markedly improved service quality. Your institution will be the first to complete AI upgrade, widening the gap with competitors. More importantly, you gain "Industry Standard setting power" that others don't have — a deeper moat than technology itself.

04

Equity Appreciation Returns — Share Industry Dividends

The Joint Venture company is not a simple cooperation project, but an independent industrial AI platform. As industry penetration increases, the valuation of the Joint Venture entity will continue to grow. You not only receive annual dividends but also enjoy capital returns from Equity appreciation. Referencing the valuation logic of global FinTech unicorns, a Finance AI platform that holds Industry Standard setting power has a far higher valuation ceiling than a single financial institution. This is an identity leap from "Finance operator" to "FinTech platform shareholder."

What We Build Together

Not simply "deploying an AI system," but a complete industrial AI infrastructure from Knowledge Base and standards to services. Each component has clear deliverables and value.

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Finance Knowledge Base

  • Risk Control Rule Base
  • Compliance Review Knowledge Base
  • Investment Research Analysis Model Base
  • Customer Service Script Library
  • Anti-Fraud Rule Engine
  • Wealth Management Knowledge Base
  • Financial Product Knowledge Base
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Industry Standards

  • Finance AI Risk Control Specification
  • Finance AI Capability Assessment Standards
  • Finance Data Security Guidelines
  • Finance AI Ethics Guidelines
  • Robo-Advisor Service Specifications
  • Industry White Paper Publication
  • Industry Alliance Formation Leadership
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Industry Services

  • Intelligent Risk Control SaaS
  • Compliance AI System
  • Knowledge Base Licensing
  • Finance AI Certification
  • Institutional AI Capability Assessment
  • Managed Operations
  • Customized Solutions
What makes the co-build model unique: The enterprise partner is not a "client" but a "co-founder." Every Risk Control model, every Compliance rule, every Investment Research framework you contribute becomes a core asset of the Joint Venture company, continuously generating revenue. This is not a procurement project, not outsourced development, but a strategic-level binding of two industry players, jointly building an AI infrastructure platform for the entire industry.

Finance AI is a Trillion-Dollar Blue Ocean

China's FinTech market size continues to grow rapidly, yet AI deep penetration rate is less than 5%. The first player to establish Industry Standards will reap the largest market dividends.

¥3T+
China FinTech Market
Size in 2026
5000+
Nationwide Licensed
Financial Institutions
<5%
Finance Industry AI
Deep Penetration Rate
48%/yr
Finance AI Market
CAGR
How significant is the first-mover advantage? In any industry, the first player to set AI standards typically captures over 60% of market share. This isn't the difference between "doing it early or late" — it's the difference between "the one who sets the standard" and "the one who uses the standard." When the entire industry uses the standards you define, you become the rule-maker of this industrial AI era, and all latecomers must follow your path. The Finance industry is currently in the "window period" of AI standardization — whoever strikes first occupies the most advantageous position.

Three Tiers, Choose One

Financial institutions at different development stages have different collaboration needs. We offer three tiers of collaboration depth, and we recommend starting with medium collaboration and gradually upgrading to deep collaboration.

Light Collaboration
Standard Co-Build · Ideal for Testing Waters
KHB Investment
  • AI tech stack support
  • Partial computing resources
  • Standard drafting guidance
Institution Investment
  • Knowledge licensing
  • Expert annotation support
  • Scenario validation environment
Deliverables
  • Finance AI Standard White Paper
  • Joint industry authorship
  • Standard publication rights
Deep Collaboration
Joint Venture Co-Build · Strategic Level
KHB Investment
  • Full computing infrastructure
  • AI technology + full team
  • Equity participation (35%)
  • Joint operations management
Institution Investment
  • Knowledge + data + scenarios
  • Co-build fund + Equity
  • Industry resource integration
Deliverables
  • Industrial AI Joint Venture Company
  • Industry-wide service output
  • Dividends + appreciation by Equity
  • Industry Standard setting power

Six Steps to Launch Co-Build

From intent submission to co-build launch, the average cycle is 60-90 days. Each step has clear deliverables and milestones — trackable and quantifiable.

01

Intent Submission

Fill out the Finance Track exclusive application form, submitting basic information such as institutional qualifications, business scale, and Knowledge Base status. KHB's strategic partnership team will feedback preliminary review results within 5 business days.

02

Qualification Pre-Review

Evaluate core indicators including the institution's industry position (whether it's a top player), knowledge assets (whether sufficiently accumulated), collaboration willingness (whether determined for deep cooperation), and decision-making efficiency (whether it can move forward quickly).

03

Strategic Discussion

Senior executives from both sides engage in in-depth dialogue to clarify core topics such as co-build direction, collaboration tier, Equity framework, and investment division of labor. This is a key step in reaching strategic consensus, typically requiring 1-2 rounds of in-depth exchanges.

04

Joint Project Initiation

Form a joint preparation team — KHB sends a technical lead, and the financial institution sends a business lead — to jointly complete core documents including the project proposal, business plan, Knowledge Base inventory list, and implementation roadmap.

05

Joint Venture Signing

Officially sign legal documents including the Joint Venture agreement, knowledge licensing agreement, standard co-build agreement, and confidentiality agreement. Clarify key terms such as Equity ratio, investment valuation, revenue distribution, and governance structure.

06

Launch Co-Build

The Joint Venture entity is officially established, launching work including computing deployment, knowledge organization, model training, and standard drafting. Typically, the first phase of the Knowledge Base goes live within 30 days after signing, and the Industry Standard White Paper is published within 6 months.

Co-Build with KHB
Finance Industry AI Infrastructure

Only 1-2 top enterprises per track for co-build, only 1 slot left in the Finance Track.
First-come, first-served — seize the window of opportunity for setting industry AI standards.

Hotline: 4006801888 · WeChat/QQ: 722496 / 489562