Upload multi-source data into the mBANK AI pipeline. Engine 1 fuses all data sources, links customers to their signals, and generates Customer 360 profiles with confidence scores.
DATA SOURCE UPLOAD
8 sources • 0 / 8 loaded
🏦
CIF / Core Banking0%
cif_master_march2026.csv14.2 MB
SYNCED • 2m ago
💳
Transaction History0%
txn_history_36m.parquet892 MB
LIVE FEED
🪪
MOI / Government Data0%
moi_identity_batch_20260309.xml3.1 MB
VERIFIED
🔗
Open Banking API0%
openbanking_cbuae_live.json28.7 MB
CONNECTED
📡
Telco & Location0%
etisalat_du_signals_30d.gz156 MB
ACTIVE
📊
Social Signals0%
social_intent_index_20260310.json44.8 MB
INDEXED
📱
App Behavioral Data0%
app_events_stream_live.avrostream
STREAMING
📋
Credit Bureau (AECB)0%
aecb_credit_reports_20260310.enc8.9 MB
PULLED • 1h ago
10,847
Total Records
CIF customers
4.2M
Transaction Volume
36-month history
8
Data Sources
Active pipelines
214
Data Points / Customer
Feature vectors
PIPELINE ARCHITECTURE
01
Data Upload
8 sources ingested into secure mBANK data lake
02
AI Engine 1 Activation
XGBoost model fuses all sources into Customer 360 profiles
03
Customer Output
10 prioritized customers ranked by AI confidence score
04
AI Engine 2 (Per Customer)
Deep product scoring & recommendation generation on demand