Michel haesendonckx • SAP
Download as PPTX, PDF1 like257 views
This document discusses how machine learning and other innovative technologies can contribute to continuous accounting. It describes how machine learning works through data training and inference to derive insights. The document outlines SAP's vision of using a next-generation intelligent ERP with a single data platform and universal journal to automate finance operations and provide predictive insights. Examples are given of applying machine learning to shared services ticket processing, accounts receivable cash application, closing processes, and predictive accounting.
Michel haesendonckx • SAP
- 1. PUBLIC Michel Haesendonckx, Global Solution Owner FP&A, SAP SE Antwerpen, October 4, 2018 How machine learning and other innovative technologies can contribute to continuous accounting
- 2. 2© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Legal Disclaimer The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the permission of SAP. This presentation is not subject to your license agreement or any other service or subscription agreement with SAP. SAP has no obligation to pursue any course of business outlined in this document or any related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation and SAP's strategy and possible future developments, products and/or platforms directions and functionality are all subject to change and may be changed by SAP at any time for any reason without notice. The information on this document is not a commitment, promise or legal obligation to deliver any material, code or functionality. 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. This document is for informational purposes and may not be incorporated into a contract. SAP assumes no responsibility for errors or omissions in this document, and shall have no liability for damages of any kind including without limitation direct, special, indirect, or consequential damages that may result from the use of this document. This limitation shall not apply in cases of intent or gross negligence. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions.
- 3. 3© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Vision of Finance Transformation From daily routine to supporting growth and new business models Automation Running the Business Insights Operations Deliver Insights Operations Predictive Insights Real-time Insights Backward looking Advanced Analytics Support Strategy Operations Forward looking Predictive Insights Real-time Insights Backward looking
- 4. 4© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Digital Age UX Finance Benefits from a Next-Generation Intelligent ERP Unparalleled capabilities to support core finance processes Single data platform Universal Journal Intelligent FinanceApplications Single source of truth • Natural UX • Digital assistant • Business ContextAwareness • Single Journal entry • Actual, plan, simulationdata • Reconciled by design • Transactional & analyticaldata • Unlimited drill-down • Data consistency • Machine learning • Predictive analytics • Cross-companyintegration Business steering with predictive insights Accelerated closing Continuous accounting Dynamic financial planning Automation of finance operations Total spend management Working capital optimization Embedded risk and compliance Real-time business simulation Intelligent ERP… …for intelligent Finance
- 5. 5© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Intelligent Finance process running on single source of truth How to most effectively utilize the company’s financial resources to optimally increase profitability and grow, while avoiding putting the company at serious financial risk Financial Steering Model (Universal Journal) Simulate & optimizeCost control Margin analysis Group Close Financial ReportingEntity Close Plan & forecast Financial accounting Analyze-to-Optimize Record-to-Report Automate PredictDetect Assist
- 6. What is Machine Learning ?
- 8. 8© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Data Training Inference Apply model Services (such as invoice processing, profile matching) …and more Applications (such as cash application) Text Image Video Speech … and more Train model Prepare data Capture feedback How does Machine Learning work? From data to insights
- 9. 9© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Automating the End-to-End processes Increase efficiency and reduce costs with SAP’s Finance Portfolio Detect and prevent Detect and rank information out of Big Data Predict Derive knowledge from historical information to increase the accuracy of predictive scenarios Proactive context sensitive support The digital assistant boost productivity of your financial experts SAP Leonardo Innovations Changing the world of Finance by adding intelligence to applications Automate PredictDetect Assist
- 10. Machine Learning: the next level of Automation
- 11. 11© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Journey to smart automation in SAP S/4HANA Finance Finance Robotics Process Automation Machine Learning Engines SAP S/4HANA Finance – The Digital Core Foundation for digitalautomation eCommerce IoT Business Network Digital Collaboration Accurate digital data Robotics Process Help run repetitive, rule-based monotone tasks Engines specific process knowledge enablesrule-based automation Accurate digital data reduces reconciliations and enables higher degree of end-to-end automated processing Machine Learning Identify hidden patterns inknowledge- intensive processes and then execute processing Accurate digital data
- 12. Machine Learning applied in a Shared Services environment
- 13. 13 SAP Service Ticket Intelligence Automatic classification and suggested responses of shared servicetickets Service tickets Knowledge base articles* Classifications Resolutions Routing SAP Leonardo Machine Learning Integration with SAP Shared Services Framework for reduced time to value Redefine service delivery with conversational interfaces and intelligent automation Improved service response times with automated processing *SAP Service Ticket Intelligence does not replace knowledge managementsolutions. © 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Create your own intelligent infrastructure SAP Service Ticket Intelligence automatically processes inquiries to deliver best-in-class shared services.
- 14. Machine Learning applied in Accounts Receivables
- 15. 15© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Example: SAP Cash Application Challenges facing AR teams in clearing incoming payments Payments Jane, 34 AR Accountant Lump sum Missing info Discounts Exchange Customer call ???
- 16. 16© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Example: SAP Cash Application Next generation intelligent invoice matching powered by machine learning History Payments Invoices Matching proposals SAP Cash Application intelligently learns matching criteria from historical data and automatically clears payments Machine Learning
- 17. Machine Learning supporting a more efficient Closing https://www.youtube.com/watch?v=jJXqWF1wJkw
- 18. 18© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC More Efficient GR/IR Clearing Next level of user support with Analytics, Assistance and MachineLearning Cleared Balance Efficient clearing Intelligent Recommendation Goods Receipts Rule based clearing Match Nomatch Writeoff GR/IR Posting Invoice Receipts Analytics, Assistance and Machine Learning
- 19. 19© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Analytical capabilities This presentationand SAP‘s strategy and possible futuredevelopmentsare subject to change and may be changed by SAP at any time for any reason without notice. This document is provided withouta warranty of any kind, either expressor implied, including but not limited to the implied warranties of merchantability, fitness for a particular purpose, or noninfringement.
- 20. 20© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Embedded collaboration This presentationand SAP‘s strategy and possible futuredevelopmentsare subject to change and may be changed by SAP at any time for any reason without notice. This document is provided withouta warranty of any kind, either expressor implied, including but not limited to the implied warranties of merchantability, fitness for a particular purpose, or noninfringement.
- 21. 21© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Intelligent recommendations This presentationand SAP‘s strategy and possible futuredevelopmentsare subject to change and may be changed by SAP at any time for any reason without notice. This document is provided withouta warranty of any kind, either expressor implied, including but not limited to the implied warranties of merchantability, fitness for a particular purpose, or noninfringement.
- 22. Machine Learning and Predictive Accounting https://www.youtube.com/watch?v=yH-HJWeDyXA
- 23. 23© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC TOP-DOWN Prediction Time series algorithm on historic data in order to predict future values considering trend, cycles and/or fluctuation Different types of predictive logic adding intelligence to finance applications Predict sum sum BOTTOM-UP Prediction Line item Line item Predictive Accounting on the basis of predicted documents being part of an Sales Order Predictive Predictive individual business process and its Goods Issue Invoice document flow S/4HANA 1809 This presentationand SAP‘s strategy and possible futuredevelopmentsare subject to change and may be changed by SAP at any time for any reason without notice. This document is provided withouta warranty of any kind, either expressor implied, including but not limited to the implied warranties of merchantability, fitness for a particular purpose, or noninfringement.
- 30. Machine Learning for Detection https://www.youtube.com/watch?v=wpakxWVEQv8
- 39. 39© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC Automating the End-to-End processes Increase efficiency and reduce costs with SAP’s Finance Portfolio Detect and prevent Detect and rank information out of Big Data Predict Derive knowledge from historical information to increase the accuracy of predictive scenarios Proactive context sensitive support The digital assistant boost productivity of your financial experts SAP Leonardo Innovations Changing the world of Finance by adding intelligence to applications Automate PredictDetect Assist
- 42. More information on how technology can support the finance function of tomorrow... https://blogs.sap.com/2018/09/20/technology-meets-finance-expertise-sap-s4hana-1809/
- 43. What do you think ? Contact information: Michel Haesendonckx Global Solution Owner Financial Planning &Analysis Finance Solutions SAP SE michel.haesendonckx@sap.com +32 472 491 699
- 44. No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission of SAP SE or an SAP affiliate company. The information contained herein may be changed without prior notice. Some software products marketed by SAP SE and its distributors contain proprietary software components of other software vendors. National product specifications may vary. These materials are provided by SAP SE or an SAP affiliate company for informational purposes only, without representation or warranty of any kind, and SAP or its affiliated companies shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP or SAP affiliate company products and services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty. In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this docume nt or any related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation, and SAP SE’s or its affiliated companies’ st rategy and possible future developments, products, and platforms, directions, and functionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for any reason without notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, or functionality. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undu e reliance on these forward-looking statements, and they should not be relied upon in making purchasing decisions. SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. All other product and service names mentioned are the trademarks of their respective companies. See http://global.sap.com/corporate-en/legal/copyright/index.epx for additional trademark information and notices. © 2018 SAP SE or an SAP affiliate company. All rightsreserved.