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The Inherent Problems of MDM
The aim to have one master record for each real world entity has always been hard to achieve—and it’s becoming even harder. Companies are contending with: Multiple internal applications—many of which will contain different versions of the same master data record Numerous external data sources that provide…
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Desilo, detangle, deduplicate: A better way to solve a complex data problem.
A comprehensive guide to overcoming your company’s trickiest data record challenges—through contextual Master Data Management. See it in action The Challenge You Face After decades of data collection, your company’s volume of data will have grown exponentially. But most of this data is collected by multiple applications,…
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Quantexa using Google Cloud Video
Ever wondered how Quantexa is using Google Cloud for its business? Check out this video by Dave Burt, Quantexa Global Customer Programs You'll get a quick overview of the tools helping us become more competitive in today's cloud market.
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Is single view enough to action business decisions?
Traditional MDM has historically been around creating a single view of individual or business. Often, that view is static and looks at entities from one angle- and therefore serve for a specific use-case/purpose. As data continues to proliferate, and the value of having each BU look after their data and create use-cases…
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The limitations of standard MDM
I've been discussing this with a collogue of mine earlier today, and I came up with the following list: Increased interest of “transactional” style MDM rather than traditional “registry” style MDM Adoption of specialized units/teams at organization to look after “single view”, often under different names of MDM like One…
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Detect Money Laundering in Correspondent Banking
Low detection rates and high false positives increase your risk High volumes of false positives Poor underlying data and inadequate monitoring results in unmanageable volumes of alerts that swamp your team daily and wastes time that could be better spent detecting criminals. Slow investigations increase costs Inefficient…
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The limitations of standard MDM
Traditional MDM comes with a hefty time burden. It takes months to ingest and transform incoming data. Because its capabilities are not sufficient for the size of the challenge, traditional MDM systems are inflexible and take a long time to gain value from. The time sink Traditional MDM systems often run using a fixed data…
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Is your MDM solution capable of scaling to today’s data sources, volumes, and complexity?
Standard MDM solutions are not built for high volumes of distributed, disparate data, that is generated by various applications and external sources. Traditional MDM probabilistic matching doesn’t work well with siloed data sources. It misses connections, losing context, leads to decision-making inaccuracy, and leaves…
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Detect Money Laundering in Capital Markets
Markets AML Prevent money launderers from taking advantage of capital markets. Use context to improve risk detection. And gain broader coverage by removing data and workstream silos. Learn more
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Combat Trade-based Money Laundering
Trade AML Detect risk in the complexity of global trade. Reveal hidden relationships between importers and exporters. And identify previously unknown money laundering and fraud. Learn more
