Underwriting models need to evolve
Building underwriting rules for lending products is an ongoing process. What began as a straightforward risk strategy targeting specific customer segments has evolved into a sophisticated, data-driven approach. Initially, lenders focused on common patterns like income levels, job stability, and credit scores. However, these patterns exclude workers with multiple income sources, or cumulating multiple jobs.
The rise of open finance platforms has significantly enhanced lenders' ability to adapt and refine these selection rules. This allows for quicker identification of risk patterns, enabling more accurate predictions and ultimately reducing defaults. The integration of alternative data sources is a game-changer in the world of lending, offering unprecedented insights into borrower behavior and risk profiles.
The role of alternative data in risk strategy
Traditional lending models rely on credit reports or banking data as the primary source for underwriting decisions. However, this approach has its limitations, particularly when it comes to underbanked or non-traditional borrowers, such as freelancers and small business owners. These individuals often lack the consistent financial history required by traditional models, leading to their exclusion from mainstream lending products.
At the core of a successful risk strategy lies the ability to quickly adjust and optimize selection rules to minimize defaults. Robust data acquisition practices are essential, as they help lenders avoid costly mistakes and open up opportunities to serve new customer segments. This is where alternative data becomes invaluable.
By incorporating data from gig accounts, wallets, and other non-traditional sources, lenders can gain a more comprehensive understanding of a borrower’s financial health. For instance, rather than waiting six months (or 3 years in some countries!) to analyze a freelancer's income via bank statements and tax reports, lenders can access real-time data from freelance platforms, providing a more accurate and timely assessment of risk.
Open finance platforms: a catalyst for innovation
Open finance platforms change the way lenders approach risk management. These platforms enable the seamless integration of various data sources, allowing lenders to build more accurate and dynamic selection rules. The ability to access a broader range of financial data, including alternative sources, provides a more holistic view of a borrower's financial situation.
This expanded data access accelerates the learning curve for lenders, enabling them to identify risk patterns more quickly and make better-informed decisions. For example, gig economy workers can be evaluated based on their aggregated earnings and activity levels on freelance platforms, providing a more accurate risk profile than traditional banking activity alone.
The key to success is how quickly selection rules can converge to reduce defaults. Lenders who are slow to adapt may find themselves at a competitive disadvantage, as more agile competitors use alternative data to underwrite a broader range of customers more effectively.
Unifying data to bridge the underwriting gap
At Rollee, we believe that a one-source-fits-all approach to underwriting is no longer effective in today’s diverse financial ecosystem. The reliance on banking data alone excludes a significant portion of the global population—over 2 billion individuals who are underbanked or unbanked. To bridge this gap, we advocate for the use of alternative data sources that provide a more inclusive and comprehensive picture of borrower performance.
Our unified API is designed to integrate various data points, including income, activity, taxes, and other alternative metrics. This approach allows risk and data teams to transition from underwriting a small segment of borrowers with general data to underwriting a much broader audience with specific and relevant datasets. By tapping into these alternative data sources, lenders can not only reduce defaults but also expand their customer base to include individuals who were previously overlooked.
This strategy is particularly beneficial for the growing freelance and gig workforce, who often struggle to access traditional lending products due to their irregular income patterns. By leveraging alternative data, lenders can create selection rules that better reflect the realities of these borrowers' financial situations, leading to more accurate risk assessments and improved loan performance.
Data-driven lending
The future of lending lies in the ability to harness the power of alternative data to build more inclusive and dynamic selection rules. Lenders must adapt their risk strategies to stay competitive. By integrating alternative data sources, lenders can not only improve their risk management practices but also serve a more diverse customer base.
The key to success in this new era of lending is agility—the ability to quickly adjust selection rules based on real-time data and emerging trends. Lenders who can effectively incorporate alternative data into their risk strategies will be well-positioned to thrive in the increasingly complex world of finance. At Rollee, we are committed to driving this transformation, helping lenders bridge the underwriting gap and unlock new opportunities in the lending market.
