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Automated Limit Recommendation Module

Affirmative built a transparent, fully explainable model that right-sizes ACH debit and credit limits for every originating company ID. Using 180 days of transaction history and each originator’s current risk grade, it replaces static, manually-set limits with data-backed recommendations — cutting low-value review noise and concentrating attention on genuine high-risk exposure. See the full results inside.

  • How the model works — inputs, aggregation, and risk-tuned buffers
  • The measured impact on review volume across a 6-month lookback of 4,719 company IDs
  • How much total limit exposure the model removed — without slowing legitimate originators
  • Why it’s fully defensible — every limit traces to activity, risk grade, and an auditable multiplier the bank controls

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Case Study: Automated Limit Recommendation Module
What's inside
How the model works
Three inputs — 180 days of debit/credit history per company ID, the originator’s risk grade, and a risk-tuned buffer — combine into one auditable recommended debit and credit limit.
The results
A 6-month lookback across 4,719 company IDs, comparing the current system to model recommendations — with the measured effect on review volume, high-risk focus, and total limit exposure.
Why it matters
Sharper review, lower exposure, and a fully defensible model — every limit traces to activity, risk grade, and a configurable multiplier. The model recommends; final decisions stay with the bank.

See what right-sized limits could do for your institution

We’ll run your originator base through the model and walk your team through the recommendations — no headcount to add, no black box to defend.

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