Many companies have turned to SaaS decisioning solutions to overcome these issues. For example, the right solution will support any modeling language, enabling your team to quickly deploy advanced predictive, machine- learning models. The solution should also make integrating alternative data quick and easy, so that you can test new data types in real-time. 47% of lenders find access to external data sources challenging 1 As lenders have historically relied on traditional data types, it’s not surprising that many lenders are daunted by the prospect of integrating new data sources, especially as the type of data required can vary by situation. For example, for a consumer without a credit file, using rent payments can be predictive. And for another consumer, looking at mobile wallet information can be helpful for those customers who don’t typically use a card. Studies have defined 4 the following characteristics of good alternative data sources: 1. Coverage – Consistent and broad coverage in a concentrated market enables easily achievable data collection. For example, what percentage of adults use a cell phone in a region? 2. Specificity – Detailed data for a borrower can create a comprehensive picture, such as on-time and late payments over a significant time period. 3. Accuracy + timeliness – Accurate and frequently updated data is critical. Keep it refreshed.
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