Models / Customer Analytics & CRM

ETB Conversion Propensity

Predicts which existing customers take up a further product in 90 days.

Strictly ConfidentialBanking secrecyCustomer PIILimited riskScoring · v2.1 · etb-conversion-propensityOwner Customer Analytics & CRM
92 39K/30d 116

AUC (out-of-time)

0.784

Top-decile lift

3.1x

Segment forecast MAPE (1 month)

4.8%

Segment forecast MAPE (4 months)

9.6%

1 more metric

Next-product top-3 accuracy

0.72

About this model

Estimates, for each existing-to-bank (ETB) customer, the probability of taking up a further product in the next 90 days and which product is most likely. Customer-level scores roll up into conversion forecasts by segment, so Consumer Banking, which owns the model, can size campaigns and set RM targets. Built with Group Data & AI; business owner Mei Ling Tan. The model behind the ETB conversion analytics use case in the Enterprise Data Platform programme.

Intended use

Selecting and sizing ETB cross-sell campaigns, forecasting conversions by segment, and feeding the next-best-offer and lead tracking flows. Not used for credit decisions or pricing; any credit product it suggests still goes through normal underwriting.

Training data lineage

Trained on customer-360-mart monthly snapshots (Jan 2023 to Mar 2026) joined to casa-transactions behaviour features and campaign-history responses, read from the lakehouse gold layer in BigQuery. Features are served from the Vertex AI Feature Store; the model is trained in Vertex AI Pipelines, registered in the Vertex AI Model Registry and monitored for drift by Vertex AI Model Monitoring. Tier 2 model, validated by Model Risk Management.

Limitations & bias notes

Customers with under 6 months of history score close to the segment average. Salary-credit features dominate, so customers paid into another bank are under-scored. Input drift is monitored weekly; a campaign or product change can shift the feature mix quickly, and retraining is expected when PSI on key features passes 0.25.

#propensity#cross-sell#etb#customer-360#xgboost#flagship#edp-use-case#drift-watch

Ownership and sensitivity

Owned by

Consumer BankingCustomer Analytics & CRM

Accountable owner: Mei Ling Tan

Who approves access

  1. Owner, Customer Analytics & CRM, Mei Ling Tan
  2. Data Governance Office, Ahmad Faizal
Strictly Confidential

Customer-level data under banking secrecy and PDPA, and models that decide on customers.

Named-user entitlement with the data owner's consent and a stated purpose; reviewed on expiry.

Banking secrecy
Customer account information protected under the Financial Services Act 2013.
Customer PII
Contains or processes personal data about customers (PDPA 2010).

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Feedback

2.0(1)

Details

Updated
2026-04-20
Latest version
v2.1
Licence
BU Restricted
Access
Restricted
Framework
XGBoost
Language
N/A