RISK / CASH-FLOW MODELLING / 2016 — 2020

Turning collection behaviour into a lifecycle cash-flow forecast

I translated repayment and collection behaviour into a cash-flow model that showed how portfolio mix and collection timing would shape future liquidity.

Lifecycle viewCash visibilityCollection behaviour connected to future cash timing.

Scenario-readyStress testingManagement could see the effect of changing collection assumptions.

ActionableEarly warningExceptions were assigned to operating owners.

01 / THE CHALLENGE

What had to be made clear

Build a model that could compare cohorts, surface collection-rate shifts, and make cash timing visible under different scenarios.

02 / MY ROLE

Where I carried the decision

I designed the cohort logic, monitoring views, and stress-test cadence used by finance and management.

03 / THE APPROACH

How the work moved from judgment to execution

01 Segmented assets by lifecycle stage and vintage.

02 Tracked collection rate, amount recovered, and timing by cohort.

03 Connected cohort assumptions to cash inflow and liquidity scenarios.

04 Flagged deviations for collection and business owners.

05 Used the model in budget, risk, and crisis-response discussions.

04 / DELIVERABLES

What entered the operating system

↳ Lifecycle cohort model

↳ Collection-rate and amount-recovery dashboards

↳ Cash-flow scenario forecast

↳ Stress-test and exception-review cadence

BEYOND THE RESULT

See the method in the system at work

This case is one part of a wider finance-and-AI practice. Explore the prototypes that make the underlying logic tangible.