Import Substitution of Customer Data Management for a Bank
We participated in an import‑substitution project to replace foreign vendor components with a domestic CDI (Customer Data Integration) platform for a bank’s in‑branch customer service application, with the longer‑term goal of substituting the legacy Siebel CRM frontend.
Customer
A regional bank operating 200+ branches across 28 regions.
Business objectives
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Eliminate risks associated with reliance on foreign software and potential sanctions-related support interruption.
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Create a single, reliable source of truth for customer data — a “golden customer record.”
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Remove discrepancies in customer data used across processes and systems.
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Standardize rules for creating, processing and editing customer records.
Development objectives
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Implement registration of new customers via the branch front‑end with data propagation into the CDI.
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Enable distribution of updated customer data from the CDI to all bank systems.
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Implement search of existing customers in CDI with consideration of the customer identification level.
Key outcomes (highlights)
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Development time for the implemented scope reduced by 6×.
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Changes consolidated into 1 microservice instead of modifying 7 separate microservices.
Solution
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Process design: We analyzed dozens of user scenarios and built an end‑to‑end customer data workflow — from customer search to product issuance — with automated and manual conflict resolution (controlled merging of duplicate records).
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Registration flow: Implemented a robust new‑customer registration mechanism in the branch front system with reliable translation and persistence of data into the CDI.
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Duplicate handling and identity level: Delivered logic for assigning customer identification levels and an automated duplicate‑collapse mechanism that improves search accuracy and reduces manual work.
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Data propagation: Implemented processes and integration routes to reliably distribute updated customer records to downstream master systems and CRM.
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Roadmap: Two next stages are planned — building a dedicated customer data store and migrating selected attributes to other master systems.
Business and operational results
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Data quality and consistency: Improved CDI data accuracy via automated and supervised duplicate merging.
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Efficiency gains: Significant reduction in time required to create, search and manually resolve duplicates, lowering staff workload.
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Faster, more accurate branch service: Unified search by the golden customer record and automated duplicate collapse shorten customer service time at the branch.
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Reduced operational risk: Mitigates dependence on foreign vendors and potential disruption from sanctions or discontinued support.
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Standardization: Unified data handling rules and regulated processes across all branches, improving predictability and governance.
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Scalable architecture: Centralized, consistent customer data available across systems supports future growth and integrations.
Why this project matters
Replacing foreign components with a domestic CDI and building robust, automated data workflows yields both technical resilience and direct business value: fewer manual operations, faster branch servicing, consistent customer records across channels, and reduced compliance and supply‑chain risk.
Technologies
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PostgreSQL
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Confluence
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Jira
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Postman
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Swagger
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PlantUML
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React
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.NETREST API
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RabbitMQ