---
title: "Ravelin Podcast: How smarter retailers choose fraud technologies"
date: 2017-08-21T21:54:00+01:00
author: Alara Basul
canonical_url: "https://www.ravelin.com/podcast/how-smarter-retailers-choose-fraud-technologies"
section: Podcast
---
Podcast / Link analysis &amp; graph databases

Episode 5

21 August 2017

# How smarter retailers choose fraud technologies

Michaela joins us again to discuss how smarter retailers choose fraud technologies and why machine learning should be considered by all businesses.

![How smarter retailers choose fraud technologies](https://storage.googleapis.com/ravelin-website-assets-production/assets/images/_548xAUTO_fit_center-center_none_ns/1646/16.webp)Gerry recently chatted with [Michaela Verstraeten](https://www.linkedin.com/in/michaelaverstraeten) as part of our [Podcast series](https://www.ravelin.com/podcast/). Michaela has been an advisor to Ravelin more or less since we started, someone whose experience and knowledge we tap into to keep us honest and focused in developing our product for retail.

In the most recent recording, Gerry and Michaela discussed what fraud systems look like today. In particular, they talked about the complexity and integration issues that exist as merchants have built up a hodge-podge of solutions over time to help them manage fraud. Michaela recommends that fraud managers take a cold-eyed review of the systems that they have in place and look to see what they can do to reduce this complexity. Michaela calls this a Fraud Healthcheck.

A Fraud Healthcheck is a great way to surface any potential technology gaps that might exist in a business. Is a machine learning capacity something that would make sense for the business? Perhaps, but Michaela had a very interesting analogy for machine learning, comparing it to a new team member but one that is really really good at processing data! The important takeaway is that rather than seeing ML and AI as a threat, smarter businesses and analysts should see it as a complementary skill set, one that will make them much better at detecting fraud patterns in a sea of data.

[**To learn more about machine learning visit our insights page.**](https://www.ravelin.com/insights/machine-learning-for-fraud-detection)

![Afk Bu I 400X400](https://storage.googleapis.com/ravelin-website-assets-production/assets/images/_122x122_crop_center-center_none_ns/851/afk_Bu-i_400x400.webp)Alara BasulRavelin alumna

More from Alara Basul

- [Infographic: The growing cost of fraud in 2018](https://www.ravelin.com/blog/infographic-fraud-in-2018)
- [Meet Tim Whelan, Ravelin’s VP of Engineering](https://www.ravelin.com/blog/meet-tim-whelan-ravelins-vp-of-engineering)
- [National Cybersecurity month: Raising awareness of fraud in payments](https://www.ravelin.com/blog/cyber-security-month-fraud-awareness)

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