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
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.
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
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.
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Graphable delivers insightful graph database (e.g. Neo4j consulting) / machine learning (ml) / natural language processing (nlp) projects as well as graph and Domo consulting for BI/analytics, with measurable impact. We are known for operating ethically, communicating well, and delivering on-time. With hundreds of successful projects across most industries, we thrive in the most challenging data integration and data science contexts, driving analytics success.
Still learning? Check out a few of our introductory articles to learn more:
- What is a Graph Database?
- What is Neo4j (Graph Database)?
- What Is Domo (Analytics)?
- What is Hume (GraphAware)?
We would also be happy to learn more about your current project and share how we might be able to help. Schedule a consultation with us today. We can discuss Neo4j pricing or Domo pricing, or any other topic. We look forward to speaking with you!