Revealing the true challenges in fighting bank fraud
From the Infoglde blog:
The results of the survey are currently being compiled for general release, but it was extremely interesting to learn that the key challenges of fraud investigations include:
1. the inability to access data due to privacy concerns
2. a lack of real-time high performance data searching engine
3. and an inability to cross-reference and discover relationships between suspicious entities in different databases.
For regular readers of this blog, it comes as no surprise that identity resolution and entity analytics technology provides a solution to those challenges. An identity resolution engine glides across the different data within (or perhaps even external to) a bank’s infrastructure, delivering a view of possible identity matches and non-obvious relationships or hidden links between those identities… despite variations in attributes and/or deliberate attempts to deceive. (emphasis added)
It being an Infoglide blog, guess who they think has an identity resolution engine?
I looked at the data sheet on their Identity Resolution Engine.
I have a question:
If two separate banks are using “Identity Resolution Engine” have built up data mappings, on what basis do I merge those mappings, assuming there are name conflicts in the data mappings as well as in the data proper?
In an acquisition, for example, I should be able to leverage existing data mappings.