How AI-Powered Risk Scores Prove Essential for Lenders Amidst Growing Economic Uncertainty in Emerging Markets

As the global economy continues to face growing pressures, the financial services industry is under immense strain, particularly in emerging markets. According to August 2024 economic data, small and medium-sized business (SMB) and consumer loan delinquencies have increased by 13% to 15% compared to the previous year. These rising delinquency rates signal deeper economic challenges that are likely to persist, especially with looming recession concerns.

Lenders in emerging markets, already grappling with inconsistent credit infrastructures, must now contend with an evolving borrower landscape. Traditional rank-ordering scores, often provided by credit bureaus, struggle to keep pace with rapid changes in borrower behavior. During the pandemic, score inflation further masked the real risk profiles of borrowers, missing opportunities to support resilient borrowers while inaccurately assessing those in financial distress. This dynamic reveals a critical gap in the current approach to consumer credit scoring: lenders need more real-time, nuanced insights to protect their portfolios and capitalize on growth opportunities.

The Growing Complexity of Consumer Lending in Emerging Markets

Emerging markets in regions such as Latin America, Southeast Asia, and Africa are feeling the brunt of economic instability. According to the World Bank, growth in developing economies is expected to slow down to around 3.5% in 2024, significantly lower than pre-pandemic forecasts. Consumer lending, a key driver of economic growth in these regions, has seen significant contractions, with lending activity dropping by up to 20% in some areas of Latin America alone. This drop can be attributed to the increased risk aversion by lenders, a lack of robust credit data, and rising inflation, which has weakened consumer purchasing power.

In these environments, financial institutions are dealing with a unique set of challenges:

• Limited Data: Many borrowers in emerging markets lack sufficient credit histories. This is particularly true in the informal sectors, where gig economy workers and small entrepreneurs are underrepresented in traditional credit systems.
• Economic Volatility: Rising inflation, interest rate hikes, and currency fluctuations are making it harder for borrowers to maintain consistent loan repayments, pushing up delinquency rates.
• Outdated Scoring Models: Conventional credit scoring models are often too rigid, relying on outdated information that fails to capture real-time changes in consumer behavior. This leads to both missed opportunities (e.g., resilient borrowers) and increased risk exposure.

In such an environment, lenders need smarter, faster tools to navigate the complexities of borrower risk profiles and respond more effectively to economic shocks.

AI-Powered Risk Scores: A Game-Changer for Lenders

To fill the gap left by traditional credit scores, advanced AI-powered technology offers a robust alternative that provides deeper, more actionable insights into borrower behavior. 1datapipe’s AI-powered customer analytics solution focuses on two critical areas: Income Estimation Insights and the Financial Inclusion Credit Score. These tools enable lenders to predict borrower behavior in the near term, identify both risks and opportunities and make data-driven decisions faster than ever before.

Income Estimation Insights: Providing Real-Time Financial Clarity

One of the major issues lenders face, particularly in emerging markets, is the inability to accurately assess a borrower’s income stability. Many borrowers operate in the informal economy, where income sources can be irregular and unreported. Relying solely on traditional credit bureau data often fails to paint the full picture of a borrower’s financial health.

1datapipe’s Income Estimation Insights leverages alternative data sources, such as telco information, utility payments, and social signals, to build a comprehensive profile of a borrower’s income patterns. This AI-powered approach provides lenders with a real-time view of income stability, offering the ability to forecast near-term financial distress or resilience. This insight allows lenders to make informed decisions on whether to extend credit, adjust terms, or offer tailored solutions for borrowers who may be struggling due to temporary setbacks but show long-term reliability.

Financial Inclusion Credit Score: Tapping into the Underserved

Emerging markets have long faced the challenge of financial exclusion, with vast segments of the population remaining underserved by traditional banking and credit institutions. In Latin America, for example, over 50% of the population remains underbanked, lacking access to the financial services they need to build credit. This is where 1datapipe’s Financial Inclusion Credit Score comes in.

The Financial Inclusion Credit Score is built on a foundation of alternative credit data, utilizing sources that traditional credit models overlook. By incorporating factors such as mobile payment history, employment patterns, and geo-lifestyle data, this score helps lenders assess the creditworthiness of individuals who may not have a formal credit history but have demonstrated responsible financial behavior in other areas.

By applying machine learning algorithms that analyze this wealth of data, lenders can more accurately segment their borrower base, identifying those with a high potential for repayment despite being invisible to traditional credit bureaus. This not only helps lenders mitigate risk but also expands their total addressable market by tapping into previously underserved populations.

The Case for AI-Powered Technology: Why It’s No Longer Optional

The financial services industry is at a critical juncture. With economic uncertainty mounting, traditional credit scoring methods simply aren’t fast or flexible enough to keep up. AI-powered technology, however, offers a way forward by addressing three key areas:

• Early Detection: AI-powered scores allow lenders to spot distress early, enabling timely interventions before delinquencies spiral out of control. This is particularly important in regions with volatile economic conditions, where minor setbacks can quickly escalate.
• Opportunity Identification: By providing real-time insights into borrower behavior, AI-powered analytics can help lenders identify healthy, resilient borrowers who may have been overlooked by traditional credit scores. Supporting these borrowers with better financial products can lead to increased customer loyalty and long-term profitability.
• Rapid Adaptability: Unlike traditional credit scores, which can take months to reflect changes in behavior, AI-powered risk scores update in real-time, capturing emerging trends and helping lenders stay ahead of the curve.

As we edge toward a potential global recession, these capabilities are no longer just a luxury—they are a necessity. Lenders who adopt AI-powered technology will be better equipped to navigate economic headwinds, protect their portfolios, and identify new growth opportunities.

Staying Ahead in an Uncertain Economy

The future of consumer lending, particularly in emerging markets, will depend on the ability of lenders to quickly and accurately assess borrower risk. Traditional credit scoring methods are no longer sufficient in today’s fast-changing economic landscape, especially as financial pressures mount and delinquencies rise. AI-powered customer analytics solutions, such as 1datapipe’s Income Estimation Insights and Financial Inclusion Credit Score, offer the tools necessary to not only detect early signs of distress but also identify borrowers worth investing in.

Is your organization equipped to meet these challenges with the right tools in place? If you’re looking to enhance your risk assessment strategy, reach out to our team to discuss how we can help you navigate this evolving landscape with 1datapipe’s AI-powered insights.