CASE STUDY
Legacy Transformation: Data Management for Credit Bureaus
Introduction
In today’s rapidly evolving credit bureau landscape, staying ahead of the curve requires a robust and adaptable data infrastructure. This case study delves into the successful collaboration between Hoonartek, a leading data and AI solutions provider, and a prominent credit bureau company. Our client faced critical challenges with their legacy bureau solution, hindering their ability to efficiently manage and leverage their data assets.
The Business Challenge
The client’s existing legacy bureau system, built upon a Mainframe and ADABAS platform that had tens of thousands of lines of code, presented several significant limitations. The outdated technology struggled to keep pace with growing data volumes, impacting scalability and performance. Additionally, the reliance on ADABAS created a skillset gap, as finding qualified professionals to maintain and develop the system proved increasingly difficult. Furthermore, a lack of in-depth understanding of the intricate business processes embedded within the system hindered optimization efforts.
Most importantly, Client’s business-to-consumer (B2C) channels, crucial for their day-to-day operations, demanded zero downtime during any modernization efforts. Finally, establishing clear performance benchmarks to measure the effectiveness of any potential solution was paramount to ensuring ongoing success.
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Joint Solution Discovery & Implementation Plan
The client partnered with Hoonartek to delve into the specifics of their requirements and co-create a comprehensive solution. Through collaborative workshops and in-depth discussions, a strategic plan emerged. The proposed approach involved a complete transformation: replacing the legacy Mainframe and ADABAS system with a modern, high-performance solution built on a wall-to-wall Ab Initio platform.
This new system would cater to all of client’s data processing needs across the Insurance, Consumer, and Commercial business domains. Envisioned to handle both batch data processing and real-time data fulfillment through web services, the modernized solution aimed to empower Client with unparalleled data agility and flexibility. The solution was proved first by implementation in an Insurance Bureau followed by Consumer and Commercial Bureau together.
The successful transformation of Client’s legacy solution materialized through the strategic implementation of a suite of Hoonartek’s cutting-edge tools and technologies within the Ab Initio platform. Hoonartek has developed multiple accelerators using Ab initio Platform which were customized according to client needs.
Tools and Technology Utilized
- GDE (Global Development Environment): This unified platform provided a seamless and easy graphical environment for development, testing, and deployment of the new system, streamlining the entire lifecycle and facilitating visual representation of rules as well as logic which helps efficient collaboration between Hoonartek and Client’s teams.
- Conduct>It: Conduct>It product provides sophisticated job automation and monitoring for Ab Initio applications and other programs, linking them together into a single execution environment.
- Co>Relate: Co>relate provides the ability to understand the hidden relationships that exist between data that may be incomplete and inconsistent, such as customer and business names. Facilitated advanced fuzzy matching capabilities, enabling accurate data identification and consolidation even with inconsistencies or missing information.
- Express>It: Express>It enables business-oriented users to rapidly configure, test, and deploy metadata-driven applications.
- Control>Center: The Control>Center product provides complete real-time job monitoring and operational management along with optional scheduling of Ab Initio applications and other programs. It provides Data Observability features to monitor pipelines and infrastructure. Hoonartek had built accelerators on top of this which would provide alerts, drifts, failures and provide Data Observability.
- Query>It: This is a Data Virtualization tool. The data can be stored in a wide range of file systems, including ALDS, S3, Hadoop (HDFS), or Ab Initio’s own highly efficient parallel and indexed file system (ICFF). In addition to supporting SQL query access to these data stores, the Query>It product can also reference data held in third-party databases (such as Snowflake, Teradata, DB2, and Oracle), allowing federated, push-down query access to heterogeneous data. This interactive data exploration and analysis tool empowered the client to delve deeper into their data, fostering data-driven decision making and improved business insights.
- ICFF (Index Compressed Flat Files): The Ab Initio ICFF is a proprietary data storage format used for efficient and scalable data processing of large data sets. It allows for quick access to large volumes of compressed data and supports high-performance operations in Ab Initio applications, very beneficial for industries with extensive data archives that require frequent updates and rapid access.
- Continuous Flows: Established real-time data pipelines, enabling high performance, low-latency real-time data fulfillment through web services applications.
- Metadata Hub: By centralizing metadata management, this tool facilitated improved data governance, reference data management, data quality, and simplified data lineage tracking.
Outcomes
The successful implementation of the Ab Initio-based solution yielded significant benefits for our client, transforming their data management capabilities:
Increasing Scalability with Zero Downtime Migration
- Increased Scalability: The new system effortlessly scales to handle growing data volumes, ensuring Client can meet their future data processing needs with ease. The solution provided data to clients in real time within SLAs. Requests involving complex transformations were served in less than three seconds, which helped them to add new clients as well as products.
- Zero Downtime Migration: The phased migration strategy ensured Client’s critical B2C channels remained fully operational throughout the entire modernization process, minimizing disruption to their day-to-day operations. A phase wise delivery approach was taken to switch off the features at legacy end and switch on the modernized solution.
Improving Performance & Reduced Dependency
- Improved Performance: The inherent performance optimization capabilities of the Ab Initio platform delivered substantial gains in data processing speed and overall system responsiveness.
- Eliminated Skillset Dependency: With the move to a modern platform, Client’s reliance on scarce ADABAS expertise became a thing of the past, freeing them to focus on core business activities. While modernizing the solution for the client, Hoonartek also built business documents for the customer to understand the complexity of the business which helped them in designing new products, defining dynamic rules which helped them in tracing alerts as well as defining triggers.
Cost-Effectiveness & Performance Benchmarks
- Enhanced Cost-Effectiveness: Reduced maintenance costs associated with the legacy system, coupled with streamlined data processing workflows, resulted in significant operational cost savings.
- Established Performance Benchmarks: Clear and measurable performance benchmarks were established, enabling Client to continuously monitor and optimize their modernized data infrastructure for ongoing success. The solution had a feature called ‘Highway’ which had multiple lanes in it. Client had the feasibility to switch on multiple lanes based on the incoming traffic. If the traffic on the high lanes increased, the number of moderate lanes would be reduced accordingly to optimize resource utilization.
Industry Perspective
Hoonartek’s extensive experience within the credit bureau industry played a vital role in ensuring the proposed solution aligned seamlessly with Client’s long-term vision and adhered to all relevant regulatory compliance requirements. The roadmap for implementation focused on minimizing disruption through a phased migration strategy, allowing for a smooth transition of functionalities from the legacy system to the new Ab Initio platform.
Furthermore, Hoonartek committed to extensive knowledge transfer sessions, empowering Client’s team with the necessary expertise to operate and maintain the new system effectively. Additionally, the inherent scalability and performance optimization capabilities of the Ab Initio platform provided a solid foundation for establishing clear performance benchmarks and ensuring ongoing system optimization.
Conclusion
This case study exemplifies the power of collaboration between leading technology providers like Hoonartek and forward-thinking organizations like our client. By leveraging cutting-edge data and AI solutions, credit bureaus can unlock the full potential of their data assets, driving operational efficiency, enhanced decision making, and a competitive edge in the ever-evolving credit landscape.
