---
title: "Unique Viewpoint | From Data to Decisions — AI’s Rise in Finance"
author: "Unique Research"
sourcePublication: "Unique Research (FFCAP English library)"
originalPublishedAt: "2024-05-10T16:00:00+08:00"
canonical: "https://ffcap.cn/en/research/20240510a06e3700"
source: "https://ffcap.cn/en/research/20240510a06e3700"
language: "en"
cnSourceUrl: "https://view.inews.qq.com/a/20240510A06E3700"
---

# Unique Viewpoint | From Data to Decisions — AI’s Rise in Finance

_Unique Research · Panel · May 10, 2024_

From Unique Capital’s **2024 AIGC Application Development Summit** (Shanghai, Jan 24). Moderator: **Wang Chaochao**, Partner, Unique Capital.

## Panel

-   **Diao Shengxin (Kevin)** — Founder & CEO, Fenshi Yuedong (分时跃动)
-   **Zhang Tianhe** — Founder, Shenpu Intelligent (深谱智能)
-   **Cao Hui** — Partner, Huibo Tech (慧博科技)
-   **Qiu Huihui** — Founder & CEO, Feidi Tech (飞笛科技)

## Introductions

**Diao:** 9 years entrepreneurship (2nd company); Wall Street background. Since ~2000 focus: FI client acquisition & marketing. Post-pandemic banks need digital care/precision marketing — offerings evolved digital employees/content → AI interactive services.

**Zhang:** DB-layer tech combining LLMs + graph; “deep data era” beyond big data — symbolism × connectionism; high-performance graph for deep value mining.

**Cao:** GPT for intelligent investment research / product design. Path: research-report DB → 2018–19 smart research → GPT. Mutual funds/brokerages in pipeline; 2024 many institutions finally budget digitalization prioritizing GPT for unstructured info.

**Qiu:** Content digitization + AIGC for online wealth management / buy-side services; broker digitization; partnering Yingmi Fund on seller→buyer shift.

## FI AI adoption

**Diao:** Pre-AI digitalization already hard (CCB work with BCG/McKinsey; WeCom rollout). AI now feels like tool upgrade — leaders already accept online engagement; cost/efficiency narrative is natural. Adoption order: joint-stock leaders (CMB, Ping An) → other joint-stocks → city banks → SOE banks last (watch then provincial pilots).

**Zhang:** Banks less profitable than assumed (annual reports); regulated license business. Mid/large banks moving on intelligent cost-out. Data limits → local deploy/train; graph + vector DBs + LLMs as full stack rebuild — AI ≠ LLM only. Focus: internal users (RMs, risk, ops) SaaS.

**Cao:** Library metaphor — from top-5 search hits to top-2,000 with cite/summarize/multi-agent reports. GPT-4 thought experiments strong; may erase junior analysts while amplifying seniors. Unstructured→structured (charts→Markdown) lifts usable research data from ~20–30% toward ~100% — high willingness to pay, few vendors.

**Qiu:** Joint-stock banks lead with private LLMs on internal KB; SOE banks / top brokers next. LLM often unlocks work they “should have done” — top-down after regulator push for domestic models. Tier-2: watch + small trials, compliance-first; “create conditions to pilot.” Tier-3: copy later.

## Biz vs tech drive; product managers

**Diao:** ~7B bank “person-times” (5–6 cards/person) — tiny change triggers org resource fights. Bottleneck: business people can’t write tech-ready requirements after offline-only careers.

**Zhang:** Align demand → solution → then tech selection; keep all departments communicating.

**Cao:** Missing PMs more than models — GPT-native workflow thinkers, not 3-year traditional analyst tracks. Pessimistic that clients will self-discover in time for startup runway → bias to self-abstract business processes.

**Qiu:** Still mostly business-driven; 2024 shift to business+tech/mid-platform co-drive (who owns budget?). Leaders added PMs in data/IT and tech-side budgets — vendors must help abstract cross-dept needs. Stage 3 (true tech/AI drive) still ahead while clients sediment existing logic.

## Core value / 2023–24 lines

**Diao:** Cheap always-on online engagement without spam; soft content marketing banks never needed when branches filled themselves — collect interaction data for segment models.

**Zhang:** Compute-layer infra (graph DB) under GPU shortage; explainable/auditable finance needs beyond pure LLM for risk; LLM stronger for interact/marketing/CS.

**Cao:** RAG citeable library vs forgetting 80% of 1,000 reports/year — mature for professional “big C / small B.”

**Qiu:** Clients prefer **efficiency over pure cost-cut**; long-tail companionship/education in volatile markets; light data-API deploy before heavy mid-platforms. 140M stock / 700M fund / 700M deposit accounts — AI+data required.

**One-liners:** Diao — “let the spark burn” in 2024; Zhang — big data→deep data, digitize→intelligentize, ecosystem with model/data/app builders; Cao — 2023 “hot” but no killer app yet; 2024 “calm mind,” cost/benefit sober; Qiu — rational optimism, user-centric certainty, embrace ecosystem vs solo.

_Inventory type kept **ranking** despite panel form._

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Editorial English edition published on UniqueCapital: https://ffcap.cn/en/research/20240510a06e3700
On-site reading page: https://ffcap.cn/en/research/20240510a06e3700