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Author's profile photo Alex Liu

Apply Machine Learning in Business Credit Rating 机器学习在商业信贷评级的应用

This blog outlines our general product direction and should not be relied on in making a purchase decision. This blog is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any course of business outlined in this blog or to develop or Release any functionality mentioned in this blog. This blog and SAP’s strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. SAP assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent.In the current global economic environment, identifying and managing credit risk across an organization has become increasingly important to the success and longevity of any business. SAP HANA accelerates processes and breaks data volume barriers to provide new management insights; financial operations teams want to better balance credit risk and opportunity – using all internal and external information they have available to them today. Can we bring the power of HANA to bear for more insightful credit management?Image if

  • You could identify hidden revenue opportunities within your customerbase through predictive analytics?
  • You could better judge real-time global credit exposure and respond quicker to credit events?
  • You could retain your high-value customers with the right credit offers?
  • Your financial operations agents could delight customers with the best next-step recommendations based on dynamic economic model predictions?
  • You could build profitable long-term customer relationships with intelligent interactions in line with your credit strategy?

Data analysis of your customer base lets you investigate how historical sales, payment behavior, key financial metrics, and so on, translate to future performance of the customer relationship. How do predicted results and liquidity forecasts compare with actual receivables? What are the main quantitative and qualitative influencers of customer creditworthiness? We are using SAP HANA and SAP ERP and SAP Predictive Analysis to intuitively design complex
models for implementing credit policy, visualize, discover, and share hidden insights and unleash the value of your customer data.

Are you interested in joining our co-innovation efforts? Contact Alex Liu for more information on how your company can join SAP in this road to changing credit management practices.

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      Author's profile photo Former Member
      Former Member

      Hi Alex,

      when will the ramp-up start for this solution?

      Best regards,