Fraud Dog

• 

  team icon

• 

  hero section of landing page

• 

  Dashboard of web app

Inspiration

Preventing fraud is very manual and technical. For a lot of small to medium companies, they don't have the resources to hire a large fraud team, until a significant fraud attack happens. Even then, fraudsters often iterate faster than teams costing the business further losses. So we created a fraud prevention service powered by AI that creates highly accurate fraud rules in seconds opposed to a team of specialists, taking hours/days, helping teams win against fraudsters and safeguard good customers.

What it does

We use AI to analyze a company's transaction data to manage and generate rules based on the client's request. It can create and monitor active rules to determine the effectiveness on catching fraudsters vs good customers.

How we built it

Fraud Dog is led by a founding trio whose backgrounds cover the full stack of fraud science, operational scale-up, and deep-tech automation. Kieran Smith, a London-based roboticist and machine-learning engineer, has spent the last decade turning cutting-edge research into production-grade automation systems. Kyle Wang, former Head of Fraud for a remittance platform processing more than $20 billion annually, brings over ten years of Risk-AI leadership across venture-backed start-ups that have collectively raised more than $100 million and achieved exits exceeding $500 million. Mohammad Laknahour is an experienced full-stack engineer whose work at American Express and BMO equipped him to deliver seamless user experiences while meeting the stringent security and compliance standards of global banks.

What's next for Fraud Dog

Find design partners to work with then fundraising to scale out our solution

Built With

• bolt
• cassandra
• ngrok
• node.js
• postgresql
• python
• supabase