Compare D&B Finance Analytics vs. Scienaptic

AI-driven solutions for credit-to-cash powered by Dun & Bradstreet’s global data and analytics. D&B Finance Analytics offers AI-driven solutions backed by the Dun & Bradstreet Data Cloud. D&B Finance Analytics is a flexible, easy-to-use tool that helps finance teams reduce costs, improve customer service, and manage risk. Manage credit and receivables risks to minimize bad debts, reduce DSO and improve cash flow. Automate manual decisioning and monitoring, customer communication, and matching. Offer your customers an online credit application as well as a payment portal. D&B Finance Analytics consists of two platforms: D&B Credit Intelligence and D&B®, Receivables Intelligence. Together, they provide powerful insights and technologies to help you accelerate your success throughout all your credit-to cash processes. You can quickly gain visibility into credit risks, onboard customers, and set the right terms.

Our platform offers ready-to-use APIs that integrate both conventional and alternative credit data sources, facilitating quicker data ingestion for more accurate credit assessments. It features a robust predictor library built on extensive credit expertise, along with pre-configured attributes that enhance credit decision-making. Our proprietary AI and ML credit modeling approach is fully explainable and yields substantial improvement in outcomes. Users can simultaneously run multiple champion-challenger models, allowing for comparative analysis of credit strategies within a single streamlined workflow. Deployment of new credit models and strategies is swift and efficient. Our AI-driven credit underwriting models are not only explainable and FCRA-compliant but also designed to be highly reliable. They include automated and simplified reasoning for adverse actions, ensuring transparency. Comprehensive documentation is provided, detailing the logic behind the models, their robustness, and any limitations. The attributes of our models are subjected to rigorous disparate impact assessments to confirm the absence of bias in their design. Furthermore, our AI credit models offer a wide and varied range of reasons for adverse actions, ensuring that users have a comprehensive understanding of the decision-making process and its implications. Overall, this combination of features empowers organizations to make informed and equitable credit decisions.