BNPL instant instalment decision
Checkout instalment decision in seconds from bureau and open-banking data; large tickets go to underwriting.
BNPL instant instalment decision
- Basket 18,750, 3-instalment request; customer E.Y., device and email known
- Basket and merchant data pulled: MCC 5732, merchant chargeback rate 0.4%
- Plan: bureau score → open banking → affordability → policy → booking
- Bureau score 1,480, 2 open loans, no delinquency, 1 enquiry in 30 days
- Open banking: 3-month average income 62,000, free monthly cash flow 14,200
- Policy v3.0: instalment 6,250 ≤ 50% of free cash → eligible, above the 15,000 limit
- Decision explanation generated: 3 × 6,250, 0% interest, first instalment today
- Amount > 15,000 → underwriter approved within 90 seconds
- Instalment plan #BN-204118 posted to the ledger, T+1 merchant payout committed
- SMS to customer: plan summary and due dates (8 Sep, 8 Oct, 8 Nov)
Simulation · derived from real agent definitions · every agent can be built by dialogue with the Autonomous Agent and validated with a test corpus
"Pay in 3 instalments" selected at checkout (API)
Instalment plan posted to the ledger, merchant payout committed, customer informed
Agents
Credit Decision Supervisor
Decomposes the objective, delegates to agents, manages approval points, merges the result.
Intake Agent
Checks basket, customer and fraud signals
get_checkoutget_customercheck_fraud_signalsBureau Agent
Pulls the bureau score and open-banking cash flow
get_bureau_scorefetch_open_bankingcompute_affordabilityDecision Agent
Decides and sets the limit from affordability and policy
apply_credit_policyset_instalment_planexplain_decisionBooking Agent
Posts the plan to the ledger, notifies merchant and customer
post_journalconfirm_merchant_payoutsend_smsSteps
| # | Kind | Agent | What happens | System | ms | tok |
|---|---|---|---|---|---|---|
| 01 | ingest | Credit Decision Supervisor | Basket 18,750, 3-instalment request; customer E.Y., device and email known | — | 160 | — |
| 02 | tool | Intake Agent | Basket and merchant data pulled: MCC 5732, merchant chargeback rate 0.4% | Merchant Checkout API | 320 | — |
| 03 | plan | Credit Decision Supervisor | Plan: bureau score → open banking → affordability → policy → booking | — | 260 | 190 |
| 04 | tool | Bureau Agent | Bureau score 1,480, 2 open loans, no delinquency, 1 enquiry in 30 days | Credit Bureau (KKB / Findeks) | 440 | — |
| 05 | tool | Bureau Agent | Open banking: 3-month average income 62,000, free monthly cash flow 14,200 | Open Banking API | 680 | — |
| 06 | verify | Decision Agent | Policy v3.0: instalment 6,250 ≤ 50% of free cash → eligible, above the 15,000 limit | — | 580 | 640 |
| 07 | reason | Decision Agent | Decision explanation generated: 3 × 6,250, 0% interest, first instalment today | — | 420 | 380 |
| 08 | approval | Credit Decision Supervisor | Amount > 15,000 → underwriter approved within 90 seconds | — | 2,200 | — |
| 09 | write | Booking Agent | Instalment plan #BN-204118 posted to the ledger, T+1 merchant payout committed | Core Ledger | 480 | — |
| 10 | notify | Booking Agent | SMS to customer: plan summary and due dates (8 Sep, 8 Oct, 8 Nov) | SMS Gateway | 220 | — |
Merchant KYB onboarding
Registry, UBO and sanctions checks in one flow; low-risk merchants start accepting payments the same day.
AML transaction monitoring alert triage
Alerts arrive enriched with a draft narrative; the analyst always decides and the filing goes out in minutes.
Payment reconciliation exceptions
PSP settlement files matched to the ledger; small breaks fix themselves, large ones go to finance approval.
Time to move from experimenting with AI to transforming with it.
In a 30-minute discovery session we take your 2–3 priority business problems, show a live demo of a similar scenario, and draft a roadmap that starts with the Value layer.
- Your 2–3 priority problems
- Live demo of a similar scenario
- Roadmap starting with value analysis