Framework

Scale-Appropriate Detection

TL;DR

Framework mapping appropriate cheater detection investment to company growth stage, from seed through Series B+.

Framework mapping appropriate cheater detection investment to company growth stage, from seed through Series B+.

When to Use Scale-Appropriate Detection

When determining how much to invest in fraud/cheater detection at your current growth stage, or when planning detection infrastructure scaling.

How to Apply

1

Seed Stage (0-10K users)

Simple rule-based flagging + manual review

Questions to Ask

  • Flag users with >3 violations in 7 days?
  • Flag transactions >2 std dev from normal?

Outputs

  • $0 cost (piggyback on support)
  • 60-70% detection rate
  • 1-2 hours/week founder review
2

Series A (10K-100K users)

Automated flagging for 5-10 rules + part-time specialist

Questions to Ask

  • Hire part-time Trust & Safety? ($60K/year)
  • Build admin dashboard for flagged cases?

Outputs

  • $100K/year investment
  • 75-85% detection rate
3

Series B+ (100K+ users)

Dedicated Trust & Safety team + machine learning

Questions to Ask

  • 2-3 person T&S team?
  • ML for pattern detection?

Outputs

  • $250-500K/year investment
  • 85-95% detection rate
4

Investment Decision Criteria

Determine when to accelerate detection investment

Questions to Ask

  • Could fraud destroy >10% of customer trust? (Invest now)
  • High-value transactions attracting sophisticated cheaters?
  • Regulatory exposure requiring compliance?

Outputs

  • Investment timing decision

Scale-Appropriate Detection Appears in 1 Chapters

Framework introduced in this chapter

Related Mechanisms for Scale-Appropriate Detection

Related Companies for Scale-Appropriate Detection