Industry
Banking
Banking Services Transformation: Unlocking Exponential Value
Highlights
- Mortgage lenders in the US assess creditworthiness based on income stability, often resulting in the exclusion of consumers with variable income such as gig workers from the formal credit system.
- The existing mortgage model is underpinned by rigid evaluation criteria and requires fundamental adjustments to align with evolving workforce realities.
- Mortgage lenders in the US must adopt new strategies and craft innovative mortgage products to capitalize on the underserved gig customer segment.
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Introduction
Mortgage lenders in the US tend to prefer borrowers with a stable, continuous sources of income as they are considered low risk.
Lenders verify borrowers’ income through documents such as pay slips, tax returns, and bank statements, assessing creditworthiness to determine if they have the capacity to meet monthly repayments. This mortgage model underpinned by standardized criteria to evaluate creditworthiness and capacity to repay is a legacy of the 20th century. While this model has served the industry well so far, it is not completely suited to the current era characterized by gig and contract workers, freelancers, and self-employed consumers with inconsistent or variable incomes. Such non-traditional income earners struggle to show income stability, maintain debt-to-income (DTI) ratios, and qualify for favorable loan terms. Consequently, this customer segment faces numerous challenges in buying a home and remains under-served given the prevailing mortgage model is not designed to consider their financial reality.
For mortgage lenders, sticking to the traditional model can mean missing out on a huge opportunity—the number of gig workers in the US stood at 70.4 million in 2025.1 Presumably, the US is steadily moving toward a multi-earner era—the number of gig workers is expected to touch 86.5 million by 20271—where consumers prefer to have more than one source of income rather than relying on a single primary source. This shift has tremendous implications for the US mortgage sector. Lenders will need to move away from conventional underwriting practices centered on stable, predictable income. In addition, mortgage lenders must design innovative loan products as well as new lending models that consider multiple income streams. However, while this transition will come with its own pitfalls, the rewards of diversifying into a new customer segment and supporting sustainable homeownership for the gig community is well worth the effort.
Analyzing non-traditional income sources
Let us examine the various types of gig and contract workers, freelancers, and self-employed individuals and their sources of income.
Social media influencers: Influencers get their income from sponsored content, brand deals, affiliate marketing, and merchandise. With businesses diverting a significant part of their advertising budgets from traditional media to digital media, the influencer economy is likely to witness a huge boost. From lenders’ perspective, influencer earnings are widely diverse, ranging from eight-figure salaries for highly compensated influencers to those who scrape by on questionable sponsorships or advertizing revenue.
Stand-up comedians: This segment earns a living through fee income for live appearances, streaming content on web platforms, and media. Compensation is event- or project-specific with comedians charging on a per-performance basis, where rates vary by venue, size, followers, and reputation.
Gig workers: This customer segment includes delivery partners, rideshare drivers, and freelancers, and now comprises a significant proportion of the workforce. Their income is sourced from digital platforms, short-term contracts, and task based assignments where earnings often vary.
Barriers to lending to non-traditional income earners
Non-traditional income earners find it extremely tough to qualify for mortgage loans due to the following reasons.
Income verification: Traditional underwriting requires two years of uninterrupted income history, W-2s, and pay stubs. Non-traditional income earners lack these and utilize 1099 forms, bank statements, or contracts that are not necessarily borrower-friendly. But lenders face challenges in assessing creditworthiness based on digital gig economy and variable income, mainly due to policy requirements around income history and stability, difficulties in calculation, and insufficient underwriting guidelines.
Income instability: Non-traditional income is inconsistent which makes it hard to project future earnings. While borrowers must commit lenders to repay mortgage instalments at regular intervals, platform and demand volatility makes it challenging.
DTI ratios: Mortgage lenders consider a debt-to-income (DTI) ratio below 43% as acceptable to approve a loan. However, for gig workers, lenders prefer a DTI below 40%. Borrowers with non-traditional, variable income face challenges in maintaining a lower DTI ratio, especially when they carry other debt.
Underwriting guidelines: Lender approaches to assessing non-traditional income are often not standardized, leading to inconsistent underwriting decisions. Many lenders consider existing underwriting guidelines on using digital gig economy and variable income for mortgage lending not detailed enough and would prefer more flexibility.
Credit score: Mortgage lenders consider non-traditional income earners as high risk which means that such borrowers require higher credit scores to negotiate favourable loan terms. Gig economy workers have a hard time keeping their credit score in good shape due to irregular cash flows.
New challenges, new strategies
While alternative lending products do exist in the US mortgage market, lenders have not fully leveraged these solutions for the gig economy and multi-income borrowers.
The opportunity lies in refining these products, adopting more prescriptive underwriting practices, and designing a borrower-friendly process to better evaluate fluctuating income streams. By doing so, mortgage providers can position themselves to capitalize on an unserved yet rapidly expanding customer segment.
However, this will require them to define and embrace new strategies and design innovative mortgage lending solutions to extend homeownership to this customer segment. A more inclusive and future-ready lending framework demands focused adjustments across documentation, underwriting, borrower education, technology adoption, and policy alignment to bring this customer segment into the formal financial system and enhance access to credit facilities. Let us examine how lenders can close existing gaps in their loan approval processes and enable accurate, fair, and scalable lending decisions.
Mortgage lenders must expand the range of acceptable income documents to reduce the risk of creditworthy and eligible borrowers staying out of the formal credit system due to technical issues such as format inconsistency. Given that gig economy and self-employed borrowers cannot provide traditional income documents, lenders must consider a wider set of income proofs including bank statements, platform-generated earning summaries, contracts, and other types of validated income records.
- Bank statements: Mortgage lenders can consider bank statements to assess income when traditional paystubs or tax returns are not available—appropriate structured income-averaging models must be put in place along with robust verification procedures. At the same time, lenders must ensure prudent underwriting standards to curb subjective decisions and improve consistency across lending teams:
- 12–24 months of business or self-employment.
- Controlled and cyclical cash flow patterns, rather than one-time spikes in income.
- A responsible and well-managed credit profile.
- Standardized data-driven income analysis tools.
- Multiple income sources: Many gig workers earn from a variety of sources. Treating each income stream separately can be an inefficient strategy that may lead to conservative underwriting outcomes. Mortgage lenders can better evaluate creditworthiness by adopting multi-source income-underwriting models that:
- Consider income from diverse sources.
- Account for seasonal patterns and cash-flow variations.
- Leverage predictive analytics and historical financial behavior to forecast future income stability.
- Reduce reliance on single-source verification.
With variable income patterns on the rise, assessing risk demands a more sophisticated approach. Mortgage lenders must leverage advanced data analysis and AI-driven tools to analyze voluminous income records. AI-driven automation improves accuracy by reducing human error and greatly accelerates underwriting while allowing humans to take decisions that demand judgement and reason.
Borrowers lack complete understanding of credit, debt ratios, affordability, and the loan process, resulting in significant rework. Mortgage lenders must drive financial literacy in this customer segment, helping them to better manage their credit scores, maintain low DTI, plan and save for higher downpayments, and meet documentation expectations. Financial literacy resources should be simple and must be shared with borrowers early in the process, reducing cycle time and underwriting friction, in turn improving loan pull-through.
Fannie Mae and Freddie Mac are among the leading government-sponsored entities (GSEs) that shape underwriting norms. Without clearer and more prescriptive guidance on variable income assessment, mortgage lenders cannot serve this customer segment. Better clarity leads to consistency across lenders and mitigates post-funding quality control risks, furthering standardization in the evaluation of non-traditional income. In addition, mortgage lenders must influence GSEs on the need to recognize multiple, unrelated co-borrowers in underwriting systems with standard ownership agreements and partner with fintechs to explore cash-flow-based credit scoring models. Policies offering additional protections, income safeguards, and benefits that lower financial volatility make underwriting more predictable and reduce lender risk. Broader policy alignment can also help stabilize the financial lives of this borrower segment.
Some US states recognize gig workers as employees, easing the process of income evaluation, while some others consider co-ownership registries, provide legal templates for non-married co-borrowers, and offer homeowner protection for group purchases. Federal agencies are investigating the possibility of accepting non-traditional income documents such as 1099s to make mortgages more accessible. Mortgage lenders must work with policymakers to replicate these measures in other states and advocate for supportive frameworks, which will contribute to a more resilient borrower ecosystem.
Clearly, the existing mortgage lending framework offers plenty of opportunities for transformation, especially in the way borrower risk is understood and assessed. With a growing gig and self-employed customer segment, it is imperative for the mortgage industry to shift beyond rigid, traditional policies and processes and fundamentally recalibrate lending models to align with today’s workforce realities, in turn creating an inclusive credit ecosystem.
Keep pace with change
The US mortgage industry stands at a defining moment.
The American dream of homeownership is no longer powered by a single paycheck, a traditional household, or a predictable career path. In the intensely competitive US mortgage market, perpetually adapting to change is key to remaining relevant. The rise of the non-traditional earner customer segment constitutes one such change that demands adjustments to mortgage lenders’ existing model.
Modifying the mortgage lending model is critical to establish inclusive practices which will ultimately drive sustainable homeownership. If lenders continue to view creditworthiness through outdated lenses, they will not only miss out on a growing opportunity but also inadvertently participate in the active exclusion of a generation that is already doing everything right: working hard, saving diligently, and seeking stability through homeownership.
Mortgage lenders must act fast, adapting their lending policies and systems, to meet the changing needs of 21st century borrowers. However, this is easier said than done—mortgage lenders must consider partnering with a service provider with deep mortgage expertise, digital capabilities, and implementation experience to usher in an era of inclusive lending.
References
1 Fortunly, Gig Economy Statistics: The New Normal in the Workplace, January 2025, Retrieved December 2025, https://fortunly.com/statistics/gig-economy-statistics/