Trey SCHMITT

An Opinion on the Future of Trust, Data, Reputation, and Human Value

If I were criticizing the modern credit system as an economist, technologist, journalist, and systems designer, I would argue that the greatest flaw is not that the system is broken, but rather that it was built for a world that no longer exists, because the architecture of modern credit was designed during an era in which wealth was primarily measured through physical employment, traditional banking relationships, mortgages, installment loans, and consumer debt, whereas today’s economy increasingly derives value from information, intellectual property, digital businesses, creator economies, software development, global connectivity, network effects, and individual innovation, leaving the current credit infrastructure attempting to evaluate twenty-first century citizens with twentieth-century measuring tools.

The modern credit system has become extraordinarily effective at measuring risk, yet remarkably ineffective at measuring potential, and while institutions can quickly determine whether an individual missed a payment six years ago, they often possess little ability to evaluate whether that same individual has since acquired advanced technical skills, built a profitable company, recovered from addiction, published meaningful research, developed intellectual property, become a community leader, or otherwise transformed themselves into a productive contributor to society, resulting in a framework that excels at documenting failure but struggles to recognize growth.

The first missing pillar is what I would call Human Potential Scoring, because the current system devotes enormous resources toward tracking past debt, past mistakes, collections, defaults, utilization ratios, and repayment histories, while allocating comparatively little attention toward intelligence, skill acquisition, education, innovation, entrepreneurship, leadership, adaptability, creativity, or demonstrated problem-solving ability, which means that a software engineer capable of building a billion-dollar platform, a scientist capable of developing a medical breakthrough, or an entrepreneur capable of employing thousands of people may appear less financially attractive than someone who has simply maintained a stable borrowing history, revealing that the prevailing question within the credit system is not “Can this person create value?” but rather “Has this person previously satisfied debt obligations?” and those are fundamentally different inquiries.

The second missing pillar is Reputation Capital, because throughout most of human history reputation functioned as a form of currency, enabling individuals to conduct business, establish partnerships, secure opportunities, and build trust through demonstrated reliability and social standing, yet modern credit systems largely ignore vast reservoirs of reputation data that already exist across professional, commercial, and digital platforms, including verified employment records, client testimonials, professional endorsements, project portfolios, volunteer contributions, community leadership activities, and long-term relationship histories, despite the possibility that these indicators may reveal more about a person’s future reliability than a revolving credit account.

The third missing pillar is Recovery Capital, which may represent one of the most overlooked dimensions of human behavior because contemporary credit systems are highly effective at recording moments of failure yet relatively incapable of recording journeys of recovery, meaning that addiction recovery, bankruptcy recovery, mental health stabilization, successful reintegration after incarceration, escape from domestic violence, or emergence from homelessness frequently remain underrepresented despite often requiring extraordinary discipline, resilience, perseverance, and personal transformation, all of which may reduce future risk rather than increase it, thereby creating the paradox that the system remembers the collapse while forgetting the rebuilding process that followed.

The fourth missing pillar is Data Ownership, because one of the most peculiar realities of the modern information economy is that consumers generate the overwhelming majority of the data that powers credit bureaus, risk analytics firms, identity verification platforms, insurance models, and fraud detection systems, yet consumers rarely possess meaningful ownership rights over the resulting datasets, have limited visibility into how their information is utilized, frequently cannot monetize the value derived from their personal information, and often face substantial obstacles when attempting to audit, correct, or challenge inaccuracies, creating an environment in which virtually every participant profits from personal data except the individuals who created it.

The fifth missing pillar is Real-Time Credit Intelligence, because many current systems rely upon datasets that may be weeks or months old, resulting in assessments that lag behind reality and create situations in which individuals who have improved their financial condition, reduced debt, increased income, accumulated assets, or stabilized employment remain evaluated through outdated information, whereas a modernized framework could incorporate verified banking activity, verified income streams, verified assets, verified employment records, and other real-time indicators to provide a far more accurate reflection of current financial standing.

The sixth missing pillar is Alternative Asset Recognition, because traditional models remain deeply rooted in industrial-era assumptions regarding wealth and value creation, focusing primarily upon loans, mortgages, credit cards, and other conventional financial instruments while often overlooking intellectual property portfolios, software assets, creator revenues, digital businesses, subscription income, royalty streams, domain portfolios, online communities, patents, publications, and other modern assets that increasingly drive economic productivity, thereby creating situations in which highly successful digital entrepreneurs appear less creditworthy than traditionally employed individuals despite generating significantly greater income.

The seventh missing pillar is Network Trust, a category that organizations such as LexisNexis and other sophisticated analytics providers have quietly explored for years through relationship mapping, identity verification systems, business affiliations, professional networks, and risk associations, because who an individual works with, who verifies them, what organizations they belong to, and what networks they participate in can reveal valuable information regarding credibility and trustworthiness, yet consumers frequently possess little visibility into how such relationship intelligence is collected, interpreted, or utilized, creating a substantial transparency imbalance between institutions and the individuals being evaluated.

The eighth missing pillar is Explainable Decisions, because modern systems routinely generate outcomes that can profoundly affect a person’s access to housing, employment, insurance, financing, or business opportunities while providing only limited explanations regarding the reasoning behind those decisions, forcing consumers to navigate opaque processes that rarely identify precise corrective actions, whereas a truly modern system would operate more like an educational platform by clearly identifying current standing, desired targets, contributing factors, improvement opportunities, and estimated timelines for achieving better outcomes.

The ninth missing pillar is Portable Global Identity, perhaps the most important long-term challenge facing the credit industry, because identity, reputation, financial history, education, employment records, professional achievements, and trust indicators remain fragmented across nations, platforms, institutions, and databases, resulting in situations where individuals can possess substantial wealth, impeccable professional reputations, and decades of verified accomplishments while simultaneously appearing invisible within unfamiliar jurisdictions, highlighting the need for a secure, privacy-conscious, portable trust framework capable of translating reputation and credibility across geographic boundaries.

Yet even these nine pillars fail to address deeper structural questions surrounding accountability, governance, and power, because the current system rarely confronts the issue of who monitors the monitors themselves, and while consumers are audited continuously through credit reports, fraud models, identity verification systems, and risk assessments, the organizations performing those evaluations often operate with significantly less scrutiny than the individuals they evaluate, raising legitimate concerns regarding algorithmic accountability, error rates, cybersecurity practices, data sourcing standards, vendor oversight, and institutional transparency.

Likewise, the system frequently ignores the inherent tension between shareholder incentives and consumer interests, because publicly traded information companies exist to maximize shareholder value through revenue growth, product expansion, data acquisition, and increased market penetration, while consumers often seek greater privacy, reduced surveillance, and tighter restrictions on data collection, creating a structural conflict that deserves far more public discussion than it currently receives.

The discussion must also extend beyond the three major credit bureaus because they represent only a portion of a far larger data brokerage ecosystem consisting of hundreds of information suppliers, marketing databases, insurance databases, court record aggregators, utility reporting systems, telecommunications providers, identity verification vendors, fraud prevention companies, and analytics firms that collectively shape how individuals are evaluated across financial and non-financial domains.

Another missing element is recognition of the Error Economy, because databases are not synonymous with truth, and inaccuracies can produce significant consequences involving employment, housing, insurance, banking access, and financial opportunities, often placing the burden upon consumers to identify, dispute, and correct information they never knew existed in the first place, thereby creating a system in which errors can become economically expensive despite originating outside the consumer’s control.

Perhaps the most significant missing question is whether society should continue treating credit primarily as a mechanism for detecting risk or whether it should evolve into a framework for measuring broader human capability, because today’s architecture is fundamentally designed to answer a single question: “Will this person cost us money?” while the emerging economy increasingly requires answers to much larger questions such as “Can this person create value?”, “Can this person be trusted?”, “Has this person demonstrated resilience?”, “Can this person innovate?”, and ultimately “What is this person’s total economic, intellectual, social, and productive contribution?”

In my view, the future of credit is not a better credit score, a more sophisticated bureau, or a more powerful risk algorithm, but rather the development of a comprehensive trust infrastructure capable of measuring trustworthiness, capability, reputation, resilience, innovation, productivity, and contribution alongside financial behavior, while simultaneously providing individuals with ownership rights over their own data, meaningful transparency into how decisions are made, and greater participation in the value generated from the information they create, because the real debate is no longer about credit reports or credit scores alone, but about who controls trust itself in the information age.