DUENDERS
Case Study
From ingestion to Use Cases: modernizing a bank infrastructure with Palantir Foundry
Many companies still run on old databases or simply Excel files, a testament to the durability and familiarity of these tools, but also a reflection of resistance to change and technological inertia. While these systems may have served businesses reliably for years, their continued use in an era dominated by rapid technological advancements can hinder operational efficiency, scalability, and data-driven decision-making. Moreover, as cybersecurity threats evolve, relying on outdated databases or basic Excel files can expose organizations to significant security vulnerabilities. As competitors embrace more advanced, integrated, and secure data management solutions, companies clinging to antiquated systems risk falling behind, missing out on opportunities, and facing escalating maintenance costs. It's an urgent call to action for businesses to evaluate their data infrastructure and invest in modern systems that align with today's demands and tomorrow's growth.
Legacy systems, which refer to old or obsolete computing software and hardware, present an array of challenges for companies striving to remain competitive.
In this case a bank needed to use a modern data platform, Foundry, in order to enable analysis, insights and AI use cases.
Here the problems encountered:
Integration Limitations: Legacy systems lack the agility to interface seamlessly with modern technologies, preventing banks from adopting innovative solutions.
High Maintenance Costs: As technology ages, the cost of finding and retaining experts in outdated software or programming languages rises, increasing operational costs.
Data Silos: Prolonged use of old systems and the ensuing patchwork of fixes can lead to isolated data repositories, making it challenging to gain an integrated view of operations or customer profiles.
Regulatory Challenges: Outdated systems might not comply with evolving regulatory standards, exposing banks to legal and financial risks.
Decision-making Delays: Legacy systems can slow down information retrieval and processing, hampering the bank's ability to make timely and informed decisions.
Erosion of Customer Trust: The inability to provide contemporary services or ensure data security can erode the confidence customers place in their banks.
Palantir Foundry is an integrated operations platform that bridges data, analytics, and teams. It offers:
Data Integration: A versatile framework connecting to enterprise systems, with auto-scaling data processing and robust security measures.
Model Integration: An environment for model development and evaluation.
The Ontology: A unified semantic model assimilating data and models.
Application Frameworks: Tools for creating operational workflows with low-code and no-code options.
Analytics: Diverse analytical tools that can feed data back into the Ontology.
DevOps: Tools for packaging, deploying, and maintaining data products.
Security: Comprehensive data protection, including encryption, authentication, and audit logging.
Utilizing Palantir Foundry, we effectively streamlined data operations:
Ingesting Regularly Data: Foundry's advanced Data Integration capabilities facilitated the seamless ingestion of data from diverse systems used across the bank's multiple countries and locations.
ETL Pipelines: The platform's tools ensured the creation of ETL pipelines, transforming data into the desired format for storage in the data lake.
Quality Checks: With Foundry's built-in health checks, the bank could consistently ensure the quality and accuracy of its data flows.
Standardize Customer Data: Foundry enabled the bank to harmonize and standardize customer data, using uniform semantic and business terms across all locations, allowing for comprehensive analysis across the entire customer base.
Perform Analytics and Advanced Machine Learning: Using Foundry's Analytics tools, the bank conducted in-depth analyses and implemented advanced machine learning use cases, extracting valuable insights from its data.
Following the implementation of Palantir Foundry:
Enhanced Data Integration: The bank witnessed a significant reduction in data silos, achieving a unified view of data sourced from its numerous global locations. This streamlined data access led to faster decision-making processes.
Efficient Data Processing: The seamless ETL pipelines ensured that data was consistently ready for analysis.
Improved Data Quality: The proactive quality checks resulted in a decrease in data discrepancies, bolstering trust in the bank's data-driven decisions.
Unified Customer View: Standardizing customer data provided a holistic view of the bank's clientele, enhancing use cases in compliance, KYC and helping the bank's anti-money laundering efforts.
Advanced Analytics Insights: The bank unlocked new insights into customer behavior, market trends, and operational efficiencies. The advanced machine learning models further identify anti-money laundering patterns in their clients' transactions that would result in fines in the hundreds of millions as happened in the past for regulated industries.
Moving to a modern data platform is a game-changer.
We offer support in migrating and establishing your data infrastructure across various platforms, including Databricks, Snowflake, Foundry, Rivery, Kebola, Y42, and more.
The optimal choice will hinge on your specific needs. We're here to assist you—from market analysis and platform selection to full implementation.
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