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Olo Deal Screening

核心功能:针对并购目标先核查交易否决项,再从战略适配、财务状况等五大维度加权打分,含PE专属评估指标,按分数阈值给出对应推荐。典型场景:PE或战略买家筛选并购标的时。输入为目标公司信息及买家投资标准,输出结构化评分报告、强弱项分析及下一步建议。

aniebyl
aniebyl
热度 52.70
最近更新 2026-05-11 17:28:04
分类:数据依赖:纯提示词应用场景:财务 / 市场分析 / 报告撰写 / 数据处理

安装技能

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执行命令安装此 skill: npx secure-skills-cli add olo-deal-screening
Metadata
name
olo-deal-screening
version
1.0.0
description
Target company evaluation and deal qualification for PE and strategic buyers
author
ololand.ai
author_url
https://ololand.ai
license
MIT
triggers
["deal screening","target evaluation","investment criteria","acquisition criteria","deal qualification","deal fit","buyer criteria","deal scoring"]
tags
["finance","screening","m-and-a","due-diligence","private-equity"]

Deal Screening for M&A

Score and qualify acquisition targets against buyer investment criteria.

Screening Framework

Evaluate targets across five dimensions, each scored 0-100:

1. Strategic Fit (25% weight)

  • Industry/sector alignment with buyer portfolio
  • Geographic fit (markets, operations, customer base)
  • Product/service complementarity
  • Technology or capability gap fill
  • Brand and market position value

2. Financial Profile (25% weight)

  • Revenue scale (minimum threshold check)
  • Revenue growth trajectory (3-year trend)
  • EBITDA margin vs. industry benchmark
  • Revenue quality (recurring vs. one-time, customer concentration)
  • Working capital efficiency

3. Valuation Attractiveness (20% weight)

  • EV/EBITDA vs. comparable transactions
  • EV/Revenue vs. sector median
  • Implied IRR at estimated purchase price
  • Multiple arbitrage potential (buy low, exit higher)

4. Risk Profile (15% weight)

  • Customer concentration (top 10 customers as % of revenue)
  • Key-person dependency
  • Regulatory exposure
  • Technology obsolescence risk
  • Litigation or compliance issues

5. Execution Feasibility (15% weight)

  • Management team quality and retention likelihood
  • Integration complexity estimate
  • Competitive auction dynamics
  • Seller motivation and timeline
  • Financing availability

Scoring Output

Overall Fit Score: 78/100 — PROCEED TO DD

Strategic Fit:     85/100 ████████░░
Financial Profile: 72/100 ███████░░░
Valuation:         80/100 ████████░░
Risk Profile:      68/100 ██████░░░░
Execution:         82/100 ████████░░

Recommendation: PROCEED TO DD
Key Strengths: [top 3]
Key Concerns: [top 3]
Suggested Next Steps: [prioritized actions]

Thresholds

Score Range Recommendation
80-100 Strong fit — prioritize for DD
65-79 Good fit — proceed with caution
50-64 Marginal — requires strategic justification
Below 50 Poor fit — pass unless compelling thesis

Deal-Breaker Checks (Auto-Fail)

Before scoring, check for absolute disqualifiers:

  • Revenue below buyer's minimum threshold
  • Negative EBITDA (unless growth-stage thesis)
  • Active material litigation exceeding 20% of EV
  • Sanctioned entities in ownership chain
  • Industry explicitly excluded by buyer mandate

PE-Specific Criteria

For financial sponsor buyers, additionally evaluate:

  • LBO feasibility: Can the deal be levered 3-5x EBITDA?
  • Value creation levers: Revenue growth, margin expansion, add-ons, multiple expansion
  • Exit path: IPO viability, strategic buyer universe, sponsor-to-sponsor
  • Hold period returns: Target 20-25% gross IRR over 3-5 years
  • Fund fit: Check size, vintage, sector focus, geographic mandate

Output Format

Provide structured JSON-compatible output with:

  • overall_score: 0-100
  • recommendation: proceed_to_dd | proceed_with_caution | pass
  • dimension_scores: object with each dimension
  • deal_breakers: list of any auto-fail conditions triggered
  • strengths: top 3 positive factors
  • concerns: top 3 risk factors
  • next_steps: prioritized action items