Cashflow Simulation Engine

Business objective: Determining whether a loan is truly profitable requires more than knowing the borrower's risk — it requires knowing when default or prepayment happens. Because of the time value of money, timing directly affects true return.

Pain point: An early-life default causes far greater loss than a late one. A prepayment, meanwhile, costs the lender its remaining interest income — the very source of profit. Flat averages capture neither effect. The poster illustrates this with a PD/PA-by-MOB chart, where PA spikes around MOB 36 due to refinancing behavior, while PD follows borrower segment patterns.

Approach: Four stages — (1) Risk Profile: PD/PA per MOB from the credit model, (2) Cashflow Engine: month-by-month simulation in Python, (3) Accurate IRR: captures the timing effect, (4) Decision: Approve/Reject based on realistic figures.

Input/Output: Inputs include term, interest rate (Year 1–3 vs. Year 4+), cost of funds, OPEX, and PD/PA per MOB. Outputs are a monthly cashflow table, IRR, and a credit loss estimate that reflects default/prepayment timing. A sample dashboard shows results (e.g., IRR 17.49%) alongside balance and cumulative credit loss charts.

Impact: Gives lending officers a clearer, timing-aware picture of expected profitability before making Approve/Reject decisions.

Future development: Batch Simulation (assessing multiple borrowers at once) and Break-Even Point estimation (profitability threshold per loan condition).