High Tech Firm Vianet Uses Graph Database & Graph Data Science to Create Fraud & Bad Actor Platform

The Challenge

The reality for web-properties that rely on users and user interaction across their platforms carries
with it inherent challenges in that bad actors see unique opportunity whether it be by hacking sites
themselves, through impersonation or by many other creative means.

The size of the problem is massive and growing quickly. According to Javelin Strategy & Research,
consumers lost more than $56 Billion through identity fraud schemes in 2020, and fraud schemes are
growing at an alarming rate. According to TransUnion, digital fraud attempts are up 150% in the first
four months of 2021 versus the previous four months.

At the same time, data volumes are exploding and when combined, this creates a perfect storm of risk
for web properties and their users. To make matters more difficult, the available technology options
have not kept pace with all these changes, so owners and managers are left with an almost untenable
problem.

The goal for Vianet was to take all of their deep domain expertise in managing this risk and build that
into a platform that is scalable and able to capture both the current expertise, as well as to easily
codify and monitor emerging threats as well. By taking their domain expertise and IP, and combining it
with graph-database technologies and graph data science techniques, including powerful and cutting-edge
machine learning, they were able to move far beyond the inadequate technology options
available today with a solution that can scale far into the future.

The Solution

Having worked with a previous solution provider that was unable to deliver a scalable graph solution,
Vianet turned to the Graphable team in what has led to a long and fruitful partnership. The particular
combination of Graphable’s skills around graph-centered AppDev and graph data science makes the
relationship a great fit, particularly with Vianet’s unique need for highly connected graph capabilities
and analysis.

Graphable AppDev and data science teams conducted a series of brainstorming and architecture
sessions to capture the breadth of capabilities required for The Captain, with a focus on personas and
the required capabilities to enable them in their roles.

In a series of iteratively advancing engagements and a highly cooperative process, the initial platform
architecture and MVP emerged, evolving further and further to include deep graph-based machine
learning that is now operating 24×7 and surfacing and alerting analysts as potential bad actors and
fraudulent patterns emerge.

This process highlighted an exceptionally strong partnership, but also Vianet’s deep domain expertise,
as well as Graphable’s expertise related to graph database and graph data science. It also highlighted
the value of integrating domain expertise with emerging technologies.

Check out additional graph database use cases.

Download Full Case Study

Read more case studies:

• National Government Consultancy Combines Domo BI/Analytics & Graph Database to Stop PPP Fraud
• High Tech Security Firm Uses Graphable and Domo Analytics to Improve Account Planning Efficiency
• High Tech Security Firm Limbik Uses GraphAware Hume and Neo4j to Create Information Defense System
• High Tech Crypto Security Firm Breadcrumbs Leverages Graphable and Neo4j
• Material Hauling Software Company MatHaul Partners with Graphable to Deliver Revolutionary, Industry-specific ERP Platform