How Lenders are Using Alternative Data Throughout the Credit Lifecycle and What's to Come
The lending industry is undergoing a significant transformation driven by the advent and integration of alternative data into its core processes. Traditional credit scoring methods, which primarily rely on credit history, income, and debts, are being augmented—or even replaced—by more nuanced and comprehensive data sets. These include information such as utility bill payments, rent payment histories, social media activity, and even educational background.
Through the entire credit lifecycle, from underwriting and account management to collections, alternative data is redefining norms and setting new benchmarks for inclusivity, risk management, and customer satisfaction. Let's explore how lenders are leveraging this goldmine of information and what the future holds for its application.
The Emergence of Alternative Data in Credit Underwriting
Credit underwriting has traditionally relied on credit scores and history, but these parameters often exclude potential borrowers who are creditworthy yet lack a substantial credit history. Alternative data comes to the rescue by providing insights into a consumer's financial behavior through unconventional sources.
Incorporating such data helps lenders gain a more comprehensive understanding of an applicant's creditworthiness, enabling them to serve a broader demographic. It's particularly beneficial for thin-file consumers who may not have an extensive credit history but do exhibit financial responsibility in other areas of their lives. By tapping into this wealth of information, lenders can not only expand their customer base but also mitigate risks more effectively.
Enhancing Account Management and Customer Experience
Beyond the initial credit decision, alternative data continues to play a crucial role in account management. Lenders are using ongoing data analysis to offer personalized products and services that match the evolving needs and risk profiles of their customers. This dynamic approach to account management fosters a more engaging and responsive relationship between lenders and borrowers, enhancing customer satisfaction and loyalty.
For instance, by monitoring alternative indicators of financial health, lenders can proactively offer credit limit increases or adjust terms to better suit their customers' current situations. This level of personalization was uncommon with traditional data sources alone, highlighting the transformative impact of alternative data in fostering more meaningful and beneficial lender-customer relationships.
Revolutionizing Collections and Recovery Strategies
In the delicate arena of collections and recoveries, alternative data is paving the way for more empathetic and efficient practices. By providing a deeper understanding of a borrower's financial situation, lenders can differentiate between those facing temporary setbacks and those with more significant financial challenges. This insight allows for tailored collection strategies that are more likely to result in positive outcomes for both the lender and the borrower.
Gone are the days of one-size-fits-all collection approaches. Now, lenders can employ strategies that genuinely reflect an individual's ability to pay, enhancing recovery rates while maintaining respectful and positive customer relationships. This shift not only improves the bottom line for lenders but also supports a more compassionate and fair financial ecosystem.
Use of alternative data
- 84% of financial institutions surveyed use alternative data, often focusing on deep subprime, subprime and near-prime consumers
- 66% of survey respondents use alternative data in their credit risk assessments for underwriting and portfolio management
- 15% increase in revenue growth is reported by nearly all financial institutions who use alternative data
Source: LexisNexis 2023 survey
Looking Ahead: The Future of Alternative Data in Lending
As we look to the future, the role of alternative data in lending is poised for further expansion and innovation. Advances in technology, such as artificial intelligence and machine learning, are expected to deepen the analytical capabilities of lenders, enabling even more sophisticated use of alternative data. Furthermore, as the regulatory environment evolves to accommodate these changes, we can anticipate a broader acceptance and integration of non-traditional data sources into lending practices.
However, this future also brings challenges, particularly in terms of data privacy and security. Ensuring the ethical use of alternative data will be paramount, necessitating robust frameworks that protect consumer information while enabling its transformative potential.
For a deeper look at the use of alternative data in lending, check out our paper, How alternative data will shift the credit landscape as we know it.
