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We tested our statistical models against 10 proven fraud cases, from Feeding Our Future ($250M) to Wells Fargo ($3B). 9 out of 10 were flagged before enforcement action.
1.1 million identity theft reports filed with the FTC in 2024, totaling $11 billion in losses. Credit card fraud, synthetic identities, and which states are hit hardest.
The IRS tax gap hit $696 billion annually. Audit rates fell 68% since 2010. Here is what the data shows about who is not paying, why enforcement collapsed, and what it costs every taxpayer.
Medicare fraud costs taxpayers tens of billions annually. We analyzed 1.38M providers and 796K opioid prescribers to show where the money goes and how upcoding, pill mills, and exclusion gaps drain the system.
14,703 nursing homes analyzed. $471M in fines, 418K health citations, 70% understaffed. CMS data shows which facilities are safe and which are not.
We analyzed 968,522 PPP loans using Isolation Forest ML. $32 billion in anomalous patterns detected: round dollar amounts, fake employees, shared addresses. Here is what the data reveals.
Fraud costs the US over $1 trillion a year across healthcare, tax evasion, government programs, consumer fraud and wage theft, from 20+ federal sources.
Wage theft costs workers more than burglary, auto theft, and larceny combined. 363,000+ DOL enforcement actions and $4.5 billion in recovered stolen wages tell the story.
Real examples of Michigan companies using AI to reduce expenses, automate workflows, and improve operations. Practical applications for small and mid-sized businesses across the state.
Common analytics pitfalls that cost small businesses real money. From vanity metrics to dashboard overload, here's what to fix first.
Not every business problem needs AI. How to recognize when simpler solutions will outperform a machine learning investment.
Before investing in AI tools, audit your data. A practical checklist covering completeness, consistency, access, and minimum viable data quality.