# Michelle Huang (@michelle.huangyy) on tiktok

- id: koinon:creator:tiktok_michelle.huangyy
- url: https://koinonlink.com/kol/tiktok/michelle.huangyy
- schema_version: 1.4

## Identity
- platform: tiktok
- handle: michelle.huangyy
- platform_url: https://www.tiktok.com/@michelle.huangyy
- website: https://bit.ly/YourFinanceGirlTT
- country: United Kingdom
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 7190
- following: 41
- posts_observed: 1
- verified: false
- size_tier: nano

## Engagement
- status: not_collected
- status_note: Engagement has not been collected for this creator yet. This is a gap in our collection, NOT a statement that the creator has no engagement. Follower count is known, so it is measurable.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: finance
- subcategory: personal_fin
- category_confidence: 0.98
- category_source: derived_from_recent_content
- topics: Personal finance education, Stock and ETF investing, Property buying vs renting, Money mistakes and smart spending, Income allocation and early investing
- bio: Helping you become financially smarter 📈
9yrs+ on the trading floor. 1st-gen
90k followers on IG
CoinShares Crypto Research👇

## Audience (inferred)
- status: present
- description: Young adults in their 20s-30s interested in learning personal finance, investing basics, stocks/ETFs and property decisions
- roles: consumer
- seniority: learner
- pain_points: Deciding whether to buy property or keep renting, Understanding how to read stocks and choose ETFs, Avoiding common money mistakes like over-relying on discounts, Figuring out how to allocate income and start investing early
- posts_analysed: 40
- confidence: 0.75

## Commercial (inferred)
- audience_buyer_fit: 0.3
- promotion_intent: 0.2
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 42
- authenticity_basis: profile_shape_only
- credibility_score: 42
- flagged_for_review: false
- koinon_bd_grade: C — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [tiktok_michelle.huangyy#b472346b] Should you buy or rent? 🏠 Not financial advice, assumptions are just for illustration and educational purpose. Always do your own research. When you invest, capital is at risk. #buyingahome #renting #PersonalFinance (https://www.tiktok.com/@michelle.huangyy)
- [tiktok_michelle.huangyy#51301294] original sound - michelle.huangyy
- [tiktok_michelle.huangyy#df629bde] It is a becoming a big trend on TikTok now! Click here: buyingahome
- [tiktok_michelle.huangyy#034dcec7] Check out Michelle Huang’s video! #TikTok >
- [tiktok_michelle.huangyy#6575cfd4] Learn about making informed financial decisions
- [tiktok_michelle.huangyy#6b7e645e] Search:
- [tiktok_michelle.huangyy#47b029df] why not to buy property and rent
- [tiktok_michelle.huangyy#96cf9c24] 5 Things you should upgrade when you have money ⭐️💷 #money #lifeupgrade #PersonalFinance

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.75, freshness_days=59, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.75, freshness_days=59, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.75, freshness_days=59, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=59, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=59, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=91, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.25, freshness_days=59, method=Profile-shape heuristic from a single snapshot (follower count, following ratio, account age, posting volume, verification), reduced for engagement red flags where post engagement was collected. Where only a follower count is available the score saturates at 58. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=91, method=llm_partner_fit_classifier + fit_score >= 0.6 AND authenticity >= 60 => A; fit_score >= 0.4 AND authenticity >= 45 => B; else C. authenticity < 30 or a promotional-pattern flag => quarantine. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=91, method=platform_profile

## Freshness
- profile_checked_days_ago: 91
- content_analysed_days_ago: 59
- audience_updated_days_ago: 59

## AI retrieval
- indexing_requests: 11
- user_triggered_requests: 0
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=tiktok_michelle.huangyy
- Request removal: https://koinonlink.com/claim?k=tiktok_michelle.huangyy
- Terms: https://koinonlink.com/for-ai