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Nimish Doshi

Nimish is Director, Technical Advisory for Industry Solutions providing strategic, prescriptive, and technical perspectives to Splunk's largest customers, particularly in the Financial Services Industry. He has been an active author of Splunk blog entries and Splunkbase apps for a number of years.

Industries 3 Min Read

Benford's Law With Splunk

Use Splunk and Benford's Law to detect fraud by analyzing the first digit distribution of numerical data.
Industries 5 Min Read

Using Amazon SageMaker to Predict Risk Scores from Splunk

Splunker Nimish Doshi covers using Amazon SageMaker and Splunk to further develop a fraud detection use case to predict future risk scores.
Industries 10 Min Read

Machine Learning in General, Trade Settlement in Particular

Use the Splunk Machine Learning Toolkit to predict the categorical value of any binary field in an event, and how this approach can be used to predict whether a financial trade will settle before its deadline based on the business semantics of related data.
Industries 5 Min Read

Improvements to Detecting Modern Financial Crime

This blog provides advice to scale the collection and detection of risk scores that are attributed to Financial Crime rules stored in Splunk.
Industries 3 Min Read

Know Your Customer Again Revisited

Splunker Nimish Doshi provides more details about how the Splunk App for Behavior Profiling makes operationalizing the Know Your Customer use easier to implement.
Industries 6 Min Read

Helping Law Enforcement with Call Detail Records

This blog gives Splunker Nimish Doshi's history with CDRs at Splunk and a tip on how to correlate CDRs for catching nefarious behavior.