Saurabh Gupta

Leading the Data Analytics team for Data Platform.
Responsible to ensure robust data mapping architecture and end to end Data delivery for business stakeholders.

Also involved in Data preparation for Regulatory reporting for Impairment ECL calculation.

Coordinating across business stakeholders and multiple support teams to ensure good quality and timely delivery.

Key Result Areas:
 Model Development: Designing AIRB PD/LGD/EAD model architectures aligned with
PRA rules, ensuring theoretical coherence and robust credit-risk justification.
 Conceptual Soundness: Conducting model structure analysis, evaluating variable
rationale, and validating conceptual adequacy across wholesale portfolios.
 Model Governance: Embedding PRA-aligned governance controls, defining
documentation traceability, and aligning lifecycle artefacts to regulatory expectations.
 Validation Alignment: Performing data representativeness, PSI checks, and surface
metric-based assessments to support independent challenge requirements.
 Model Monitoring: Implementing monitoring frameworks covering Gini, stability
metrics, calibration trends, and early-warning drift behaviour.
 IFRS 9 Testing: Conducting ECL boundary assessments, back-testing alignment, and
ensuring model behaviour stays within expected prudential thresholds.
 Data Engineering: Building model-ready datasets, applying missing-value logic,
pipeline automation, and multi-stage traceability checks.
 Cross-Team Collaboration: Coordinating with MSO, credit risk teams, economists, and
model owners to ensure business-aligned model use boundaries.
 Regulatory Documentation: Authoring LaTeX-based development documents
mapping guideline-to-model adherence and ensuring audit-ready completeness.
 Challenger Models: Structuring challenger PD models to enhance transparency,
support remediation pathways, and reinforce governance expectations.

 Data Architecture: Designed end-to-end data pipelines for campaign targeting,
ensuring segmentation accuracy and cross-system consistency.
 ETL Migration: Led SAS-to-Spark/Hive migration, improving scalability, processing
efficiency, and analytical flexibility across datasets.
 Data Governance: Implemented quality controls, anomaly detection, deduplication
checks, and imputation treatments supporting downstream analytics.
 Automation Frameworks: Developed Unix-based automation modules, streamlining
recurring processes and reducing manual operational gaps.
 Secure Transfers: Built secure file-transfer modules using AMEX SFT protocols,
ensuring compliant and reliable data distribution workflows.

 Risk Analytics: Delivered SAS-based credit rating analytics supporting US insurance
and media portfolios with structured data validations.
 Team Leadership: Directed analysts to deliver multi-portfolio insights, ensuring high
quality modelling inputs and timelines.
 Process Automation: Automated legacy reporting flows using SAS DI, strengthening
reporting accuracy and reducing operational defects.

 Statistical Analysis: Performed SAS-based survey analytics, delivering insights driving
client marketing and behavioural strategy decisions.

 Lifecycle Platforms: Developed modules under RAMP analytics supporting end-to-end
model lifecycle management and validation streams.
 Data Warehousing: Maintained AMEX USA warehouse environments, ensuring data
availability, lineage tracking, and dashboard automation.
 Automation: Created shell-scripted automation tools enhancing reporting timeliness
and operational stability across risk datasets.