Driving Customer Journey Analytics and Scoring to the Next Level
MetricScape is a highly advanced self-service analytical platform designed to help bankers develop customer level scoring algorithms and conduct detailed customer journey analysis in real time. Designed by data scientists, this integrated platform is built on Spark/Hadoop and can crunch over a 1000+ business metrics per customer in sub-second response time.
MetricScape uses a standard banking data model to integrate both internal and external data sources and uses fit-for-purpose analytics and a curated metrics library to solve various banking problems. You can monetize your data assets and empower your business with four key functionalities of MetricScape.
Self-service user interface with built-in “accelerators” for iterative model development viz. a curated, shareable library of metrics and scoring algorithms, and built-in analytic views that drives specific analyses for banking use cases.
Standard banking data model:
Fit-for-purpose relational data model with custom partitioned storage design on Hadoop that enables efficient metric generation.
Wide user community:
Appeals to business analysts who can customize parameterized metrics using a wizard and to data scientists who can create sophisticated metrics using a high performance, rich Novantas API.
Metadata Governance Framework:
Data governance for agile analytics, automatically tracking changes and recording dependencies for end to end traceability.
Case Study: A Spark-based Distributed Simulation Optimization Architecture for Portfolio Optimization in Retail Banking
Strata Data Conference NYC 2018
“We can look at five years of data for six million customers and obtain insights in minutes,” said Hank Israel.
The role of the branch employee is changing from a transaction position to an advisory one as fewer customers visit the branch, forcing banks to hire more sophisticated and flexible front-line workers.