D&B Finance Analytics
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.
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Axe Credit Portal
Axe Credit Portal – ACP – is a future-proof AI-driven solution to automate the loan process from KYC to servicing including scoring, automatic decisioning, limit management, and collateral management. ACP is a locally hosted or cloud-based solution for lenders looking to provide an efficient, competitive, and seamless omnichannel financing journey for all client segments (Retail, Commercial, Corporate, Sovereign, and FIs.)
ACP is a multi-segment digital lending solution covering not only Retail, Commercial, Corporate, FIs, and Sovereign segments but also other specific types of lending such as Microfinance, BNPL, Embedded financing, Islamic finance, Green Loans, debt servicers & collectors.
Axe Finance is the trusted partner of leading global banking institutions such as Société Générale, OTP Bank, APS Bank, Arab National Bank, Al Rajhi Bank, Saudi EXIM Bank, QNB, ADCB, FAB, Bank of Bahrain and Kuwait, Bangkok Bank, Vietcombank, VIB, Permata Bank, BRED Bank Cambodia, Fidelity Bank, Polaris Bank, African Development Bank Group. among many others.
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Microsoft Cognitive Toolkit
The Microsoft Cognitive Toolkit (CNTK) is an open-source framework designed for high-performance distributed deep learning applications. It represents neural networks through a sequence of computational operations organized in a directed graph structure. Users can effortlessly implement and integrate various popular model architectures, including feed-forward deep neural networks (DNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs/LSTMs). CNTK employs stochastic gradient descent (SGD) along with error backpropagation learning, enabling automatic differentiation and parallel processing across multiple GPUs and servers. It can be utilized as a library within Python, C#, or C++ applications, or operated as an independent machine-learning tool utilizing its own model description language, BrainScript. Additionally, CNTK's model evaluation capabilities can be accessed from Java applications, broadening its usability. The toolkit is compatible with 64-bit Linux as well as 64-bit Windows operating systems. For installation, users have the option of downloading pre-compiled binary packages or building the toolkit from source code available on GitHub, which provides flexibility depending on user preferences and technical expertise. This versatility makes CNTK a powerful tool for developers looking to harness deep learning in their projects.
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Salford Predictive Modeler (SPM)
The Salford Predictive Modeler® (SPM), software suite, is highly accurate and extremely fast for developing predictive, descriptive, or analytical models. Salford Predictive Modeler®, which includes the CART®, TreeNet®, Random Forests® engines, and powerful new automation capabilities and modeling capabilities that are not available elsewhere, is a software suite that includes the MARS®, CART®, TreeNet[r], and TreeNet®. The SPM software suite's data mining technologies span classification, regression, survival analysis, missing value analysis, data binning and clustering/segmentation. SPM algorithms are essential in advanced data science circles. Automation of model building is made easier by the SPM software suite. It automates significant portions of the model exploration, refinement, and refinement process for analysts. We combine all results from different modeling strategies into one package for easy review.
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