Integrating Predictive Analytics with Core Banking Systems: Lessons from PenFed and IFC

The integration of predictive analytics with core banking systems represents a transformative approach for financial institutions seeking to enhance operational efficiency, risk management, and customer experience. This article examines key considerations in this integration process, drawing insights from the PenFed Credit Union's PANGEN Project for credit card processing and the International Finance Corporation's iPortal and iDesk applications. This article explores essential factors, including data quality frameworks, system interoperability challenges, scalability requirements, regulatory compliance protocols, model transparency approaches, and stakeholder trust development. By addressing these critical elements, financial institutions can successfully implement predictive analytics solutions that drive innovation while maintaining security, compliance, and customer confidence in an increasingly data-driven banking landscape.

Authors

Publication Details

Journal
European Journal of Accounting Auditing and Finance Research
Published
2025-03-15
DOI
https://doi.org/10.37745/ejaafr.2013/vol13n45971
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating Predictive Analytics with Core Banking Systems: Lessons from PenFed and IFC

Mani Kiran Chowdary Katragadda
European Journal of Accounting Auditing and Finance Research
Big Data and Business Intelligence
article

Integrating Predictive Analytics with Core Banking Systems: Lessons from PenFed and IFC

Mani Kiran Chowdary Katragadda
article en

Abstract

The integration of predictive analytics with core banking systems represents a transformative approach for financial institutions seeking to enhance operational efficiency, risk management, and customer experience. This article examines key considerations in this integration process, drawing insights from the PenFed Credit Union's PANGEN Project for credit card processing and the International Finance Corporation's iPortal and iDesk applications. This article explores essential factors, including data quality frameworks, system interoperability challenges, scalability requirements, regulatory compliance protocols, model transparency approaches, and stakeholder trust development. By addressing these critical elements, financial institutions can successfully implement predictive analytics solutions that drive innovation while maintaining security, compliance, and customer confidence in an increasingly data-driven banking landscape.

European Journal of Accounting Auditing and Finance ResearchVol. 13(4)
Openalex Percentile: Top 89%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.