A Banking Big Data & Analytics Platform with 24x7 Support

Enabled a large private bank to implement data and AI-based analytics tool to improve business functions quickly

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About the Client

The client is a multi-national private banking and financial services company based out of India. With subsidiaries on a global platform, the client provides banking and financial products and services to retail and corporate customers.

The Business Challenge

The client wanted to build a scalable (Vertica & MapR) Data and Analytics platform with an objective to analyze unstructured data and business function analysis. Besides, the client wanted to improve business performance in fields of pre-qualified offer generation, pre-approved loans, financial health score, customer document mining, transaction analysis, and conversion tracking. The client also wanted to utilize the existing data to strategize and provide better services to the customers.

What Aptus Data Labs Did

We created a scalable Big Data and analytical platform to analyze structured and unstructured data and business functions. We migrated the data into a new architecture – columnar database model, modified and optimized the data processing jobs, and achieved much better query performance and batch processing.

The Impact Aptus Data Labs Made

We created a scalable Big Data and analytical platform to analyze structured and unstructured data and business functions. We migrated the data into a new architecture – columnar database model, modified and optimized the data processing jobs, and achieved much better query performance and batch processing.

The Business and Technology Approach

Aptus Data Labs used the following methodical approach to plan, develop, and execute the analytical tool to solve the existing challenge. Aptus Data Labs

  • Designed the new database architecture and migrated 300+ application and data to the new platform
  • Implemented data processing and query processing scripts
  • Implemented analytics for pre-qualified offer generation, pre-approved loans, financial health score, segmentation, customer behavior, and recommendation engine
  • Implemented analytics for transactions by categorization mapping, conversion tracking, and transactions analysis
  • Developed internal and external AL-based chatbot
  • Implemented data mining from existing documents and creating metadata
  • Implemented detection of remittances and anomalies
  • Implemented AML (Anti Money Laundering) system
  • Developed an early-warning corporate system
  • Maintained a customizable and scalable computational data-science environment
  • Supported the Big Data infrastructure and platform on a 24x7 model

The reference architecture what we build and worked

Big-data-analytics-solutions-architecture

Tools used

Big Data Platform – Vertica, Oracle, MapR Hadoop platform, Informatica, Talend,SAS, Java, Python,SQL, Linux, Spark, Cloud Computing​.

Data Science and Machine Learning Platform​ – RapidMiner platform​

Platform and App Support​ – Vertica and MapR platform​ 

The Outcome

  • Improved query performance by 100-300%
  • Migrated around 12000+ tables , 1000+ stored procedures, 1000+ workflows & ~700TB data size
  • New Technology adopted – Hadoop/MapR Platform, Kafka, Spark Processing, Vertica/ML, Python, R, RapidMiner, Java, Social Intelligence, Document repository & Text Mining/NLP
  • New Technology adopted – Hadoop/MapR Platform, Kafka, Spark Processing, Vertica/ML, Python, R, RapidMiner, Java, Social Intelligence, Document repository & Text Mining/NLP

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