Success Story

Raiffeisen bank adapts to regulatory changes with master data management

We use MDM to support with data quality reports and issue data quality notifications. This enables us to inform the front office or the customer of problems within specific records

Sona Karkoskova Data Governance Manager
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The European bank successfully consolidated customer portfolios for multiple acquisitions and built an MDM hub to power its operations and facilitate regulatory compliance.

Key results

  • Full regulatory compliance with GDPR regulation
  • Reliable prevention of duplicate client records and improved customer experience
  • 20 systems enable critical business operations based on trusted customer data
  • 5,7 million consolidated customer records in the MDM hub

Regulatory compliance triggers data consolidation

The Master data management initiative started small by serving the compliance department and helping with customer data consolidation for regulatory compliance.

“At the very beginning, the business was responsible for the GDPR project implementation. That was the initial trigger for the implementation of Master data management”

Roman Tobisek - Data quality manager and MDM product owner

The bank needed to see which systems have records of every single customer in order to adapt to regulatory changes easily. Roman’s objective was: “To gain the maximum advantage possible from the tool's capabilities and to align it with the data management strategy of the bank.”

To that end, Raiffeisenbank established an MDM hub to achieve a single customer view with full information from all consolidated systems. Customer records are propagated to the enterprise data warehouse daily and enable full GDPR compliance. This includes identifying client information in all systems and supporting the right for erasure. Beyond regulation, the bank relies on deduplicated customer records to decrease costs and improve the efficiency of its marketing activities.

Leveraging embedded data quality for client-first initiatives

The initial use case was extended from regulatory compliance to proactively preventing bad customer data ingestion. The bank deployed 5 web services that were supported by Ataccama ONE MDM. The tool cleansed and validated data entered by branch workers when creating or editing client records.

“We implemented a set of data quality firewalls that are integrated into several front-end applications. These help users search for, enrich, and validate customer records.”

 Lucie Skrackova - Data quality analyst 

The web services incorporate a number of external registries and blacklists for validating addresses and legal entities, as well as detecting relationships between persons.

Supporting group-wide growth strategy through mergers and acquisitions

Having succeeded in operationalizing the two previous initiatives, Raiffeisenbank and Ataccama took the MDM implementation to the next level: 

  • Consolidating client portfolios after a recent acquisition with the goal of preventing customer duplication and preparing the consolidated portfolio for cross-selling.

“Over the past few years, MDM played a crucial role in handling client portfolio acquisitions, effectively increasing the number of clients almost threefold. It helped a lot by ensuring that data was accurate and consolidated within the acquisition projects.”

Roman Tobisek - Data quality manager and MDM product owner

Over the course of its partnership with Ataccama, the bank consolidated customer portfolios of three banks. They gradually moved from one-off tactical portfolio consolidations to strategic MDM working in batch and online modes. In batch mode, the MDM hub consolidates data from 20 source systems, of which 4 are also processed in near real-time mode. Tailored datasets are then provided to the enterprise data warehouse for consumption by the whole organization, while following strict security policies. As Roman puts it: “We're talking about 10s of million (up to  50 million) customer records because they come from 20 different systems.”

Preventing duplicate reporting and enabling data governance

Based on a daily data processing job, the bank generates a report of potential duplicate customer records to complement deterministic matching. The report is processed by customer care representatives who further investigate the data to verify the information. This gives the bank the flexibility to work manually with complicated matching cases and prevent false matches. 

“We use MDM to support with data quality reports and issue data quality notifications. This enables us to inform the front office or the customer of problems within specific records.”

Sona Karkoskova – Data Governance Manager

Raiffeisenbank also uses data governance processes for data reconciliation between separate entities like the main bank and the savings bank (which is its own separate business). With the help of Ataccama ONE MDM, they managed to establish a data governance environment for both entities and are able to exchange information about critical data that are collected. For Sona, this meant: “We can now solve problems by using common principles and procedures to manage shared customer data between entities.”

The future is AI-powered

Raiffeisenbank is aware of existing trends in artificial intelligence and machine learning and actively employs that kind of technology inside their organization. To that end, Roman is eager to take advantage of Ataccama’s GEN AI capabilities as soon as possible:

“The future is in AI, as we can no longer manage the amount of data that keeps coming into our systems at a greater speed than ever.”

Roman Tobisek - Data quality manager and MDM product owner

As the bank changes and develops, the organization also sees a future in the Data Mesh concept. Taking advantage of self-service data management, processing, and consumption for regulatory reporting or marketing campaigns. For Roman, it’s important to “Keep business stakeholders engaged and satisfied without adding more development costs”

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