AWS · Embedded Finance
Lending engine scaled on AWS to fund SMBs across 3 continents.
We rebuilt the lending decisioning engine as an event-driven service mesh on AWS, unlocking 6× loan throughput and cutting unit cost per decision by 33%.
[Loans / day]
6×
[Unit cost]
-33%
[Continents live]
3
[ The Problem ]
Where the business was stuck.
Underwriting engine couldn't scale to meet SMB lending demand across multiple continents.
[ Key Challenges ]
- ▸Batch underwriting pipeline capped at ~2K loans/day
- ▸Regional latency slowed decisions for LATAM and EMEA SMBs
- ▸Model retraining took weeks
Our approach
How we engineered
the outcome.
STEP 01
Event-driven decisioning on EKS with Kafka Streams
STEP 02
Multi-region deployment with edge-local decisioning
STEP 03
MLOps pipeline for weekly model refresh with shadow eval
[ Solution highlights ]
Delivered — measured — in production.
- ✓Loan throughput grew from 2K to 12K decisions/day
- ✓Regional decision latency dropped to <300ms P95
- ✓Unit cost per decision cut 33%
[ Tech stack ]
Built on AWS.
AWS EKS
Kafka Streams
SageMaker
Terraform
"
We went from turning SMBs away to funding them in real time — same day, three continents.
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