Study Highlights Structural Pay Gaps in Professional Compensation
A new category of AI-driven financial technology is emerging at the intersection of compensation analysis, labor economics, and portfolio optimization, reflecting broader questions about how value is created and captured in modern professional careers.
Chicago-based startup Lossdog plans to launch its platform in April 2026, positioning itself around a core premise that has gained traction across academic and policy circles for decades. Many professionals in developed economies are systematically underpaid over the course of their careers, not because of individual performance gaps, but due to structural features of labor markets.
That premise is explored in the company’s inaugural research, The Seven-Figure Pay Gap: A Structural Analysis of Professional Compensation. The analysis draws on decades of peer-reviewed economic literature to argue that cumulative underpayment across a typical white-collar career can reach into the millions of dollars. The drivers, according to the research, are not hidden conspiracies but well-documented dynamics such as labor market concentration, declining labor share of income, and the growing disconnect between productivity and compensation.
The study synthesizes findings from sources including the Quarterly Journal of Economics, the Brookings Institution, and the Harvard Law Review. It identifies five structural mechanisms that compound over time: productivity and wage decoupling, labor market monopsony, value creation versus value capture asymmetry, declining labor share, and the accelerating impact of AI on productivity without proportional wage gains. Together, these forces help explain why aggregate economic growth has not translated evenly into individual earnings.
Lossdog’s platform is designed to operationalize these ideas through data. Rather than focusing solely on investment performance, it combines career compensation analytics with portfolio intelligence to model how earnings decisions and market participation affect long-term wealth outcomes. The approach reflects a broader shift in fintech toward integrating labor data, career trajectories, and capital markets into a single analytical framework.
The company was founded by Tom Sosnoff and Scott Sheridan, who previously built trading platforms thinkorswim and tastytrade. Their latest venture reflects a different application of market data, moving from active trading toward structural analysis of how professionals are priced in labor markets and how that pricing affects lifetime wealth accumulation.
While the platform remains pre-launch, the research is being released as early access opens to the first 50,000 users, creating an initial test of how AI-driven insights into compensation and wealth may shape career and financial decision-making. The findings contribute to a broader conversation among economists, policymakers, and communications professionals about transparency, fairness, and the long-term implications of AI-enabled productivity. As AI continues to reshape how work is performed and measured, questions about who captures the resulting value and who gains early access are becoming central to discussions of trust, equity, and economic opportunity. The research is available upon request to press@lossdog.com
