---
title: "AI + Finance: From Transaction-Centric to User-Centric Growth"
author: "Unique Research"
sourcePublication: "Unique Research (FFCAP English library)"
originalPublishedAt: "2023-09-08T18:00:00+08:00"
canonical: "https://ffcap.cn/en/research/20230908a02pb300"
source: "https://ffcap.cn/en/research/20230908a02pb300"
language: "en"
cnSourceUrl: "https://view.inews.qq.com/a/20230908A02PB300"
---

# AI + Finance: From Transaction-Centric to User-Centric Growth

_Unique Research · Insight / AIGC Open Day · September 8, 2023 · Theme: AI + finance · Guests: Youlianyun, Magic Engine, Feidi Tech — full roundtable rewrite_

Open Day series (twice monthly) hosts founders/execs on frontier AI×industry. This session: finance’s shift from tech curiosity to business value · LLM multi-domain outlook · commercialization challenges · 1–3 year outlook.

## Youlianyun (有连云) — “everything connected”

**Yunchuang** — AI content creation for real-time market follow (stocks/funds move too fast for pure manual). **Yunlian** — distribute generated content onto finance platforms for sales/marketing assist. **Yunshu** — content-effect monitoring + analytics for decisions. Accuracy stakes are extreme; generic LLMs often insufficient → proprietary finance models. Clients: fund-industry leaders plus listed semis/new energy/biopharma; products already solve sales/marketing pain and guide roadmap.

## Magic Engine (魔数智擎)

Roots in first-gen data-mining vendor Salford Systems; China core team founded 2018. One-stop financial intelligent decision + AIGC LLM platform: lower model barriers from data→modeling→production for risk control, precision marketing, smart ops. “Last mile” of model landing must be fluent and business-fit—quality, explainability, value match. LLM-era products mimic human data/corpus handling; speed coding for analysts; offline/private deploy for bank risk. Clients across banking/insurance/securities/healthcare/auto/energy (~7 industries; ~50 financial institutions). Cases: first domestic bank project putting complex ML models into credit-card A-card real-time decisioning; state bank VIP churn −76.04% and +¥250M wealth-product sales; regional bank—2 people / 3 months / 10 models → +¥1.1B AUM.

## Feidi Tech (飞笛科技)

Digital AIGC for financial institutions’ user-growth data engine; partners brokers/funds/banks. Full-lifecycle trust management: acquire → retain → activate → convert. Team: senior financial media + internet PMs + quant experts. Services: online “virtual advisors” for product teams; AIGC marketing-material platform for ops; “businessized” digital ops middle platform for data/AI units; professional wealth plans + online content companionship for advisors to win investor trust.

## Roundtable

### Attitude: tech → business value

**Zhang Yan (Youlianyun):** Finance is relatively market-open to new tech—but tech is a tool; must solve real needs, not exist for its own sake; accelerate business as AI marketizes. **Xu Jing (Magic Engine):** Two sink phases—post-2015 head institutions saw AI value; lately recognition sinks to mid/small FIs via marketing + head cases. New bar: no more trial-and-error tolerance; solutions must create lasting business value chains with clients. **Qiu Huihui (Feidi):** vs prior wave, this wave stresses business pressure (stock-client activity down); FIs urgently need problem-solving; product+tech+biz collaboration for sustainability—not tech theater.

### Where LLMs unlock new products

**Zhang:** LLM as methodology across finance/weather/power/pharma; fast landing in CS; extend to risk, AML. **Qiu:** stock efficiency (integrate LLMs for data quality/speed) + incremental apps (buyer-side financial info; finer scene granularity + vertical data; better interaction / noise reduction)—needs ecosystem partners; open-boundary disagreements still block data/tech collaboration. **Xu:** domain data → high-accuracy solutions (Huawei Pangu weather/manufacturing; power load; bank-statement vertical models for AML/fraud); multimodal + traditional data next.

### Commercialization challenges

**Qiu:** ToB clients push short-term monetization vs long vision—align client ROI with company vision; user-centric design; predictable outcomes; drop costly misaligned projects. **Xu:** choose staffing/product/consulting/ecosystem positioning; product-core → ecosystem wins ToB+AIGC. **Zhang:** do long-value work; bind product to needs; iterate; profitability-first for sustainability.

### 1–3 year outlook

**Zhang:** keep landing AI with multiparty ecosystems; focus rigid needs/pain; avoid high-risk adjacent bets. **Qiu:** more important than tech novelty—business-model innovation in a licensed industry: transaction-centric → user-centric digital transformation; platform/ecosystem experiments for better service + resource integration. **Xu:** finance is conservative; validation cycles long; near-term innovation stays in mature lanes (analytics, risk, marketing, fraud); disruptive leaps slower.

_CN images; attach on ingest._

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Editorial English edition published on UniqueCapital: https://ffcap.cn/en/research/20230908a02pb300
On-site reading page: https://ffcap.cn/en/research/20230908a02pb300