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How does cognitive automation work?

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Cognitive automation for RPA means having bots that learn from people how to handle unstructured and unclear data so processes can be automated from end-to-end. IQ BotTM is ready to take on your most unstructured data.

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How does cognitive automation work?

  1. 1. James Dening, VP, Automation Anywhere Fujitsu Forum 7th November 2019 How does Cognitive Automation work?
  2. 2. 3,500+ Enterprise Customers, 1,100+ Partnerss, 2,500+ Employees, 90+ countries, 1.7M+ Bots deployed BFSI Engineering Pharma Telecom Hitech Oil, Energy & Utilities Manufacturing
  3. 3. The Evolution of Robots RPA automates repetitive, recurring manual processes Sensors and Vision extend the capabilities of robots OCR starts the automation of data extraction Cognitive layers on top of OCR to automate processes that RPA alone cannot iRPA = Digital Workforce Office automation is catching up with factory automation
  4. 4. Why do we need Cognitive Automation?
  5. 5. Average Company’s Lifespan on S&P 500 Index 90 years 60 years 35 years 25 years 18 years 0 10 20 30 40 50 60 70 80 90 100 1935 1960 1980 2000 2015 Source: Credit Suisse, INNOSIGHT, Standard & Poor’s
  6. 6. Problems for a business
  7. 7. Regulatory burden
  8. 8. The IT landscape is increasing in complexity
  9. 9. More and more data is flooding into every enterprise • More complex systems • Better instrumentation • Increased integration • Internet of Things
  10. 10. The Automation Challenge
  11. 11. Automation + AI/ML: Intelligent Automation
  12. 12. The Automation Challenge
  13. 13. The new workforce
  14. 14. Human and machine together
  15. 15. How does Cognitive Automation work?
  16. 16. Leap from RPA to AI Platforms RPA Typical AI Platform • Designed for business user • Create in minutes/hours • Operationalize in days/weeks • Low upfront investment • 3-6 month ROI • Designed for IT/data scientists • Months to develop • Years to operationalize • High initial investment • Years to recoup investment
  17. 17. Human and machine together
  18. 18. How does Cognitive Automation work?
  19. 19. Parallels with Self-driving Car
  20. 20. Cognitive Automation for Business Processes Recognize Natural Language Processing Understand Enrich Computer Vision Improve Fuzzy Logic Machine Learning
  21. 21. Recognize Convolution Neural Networks, Geometric Hashing, Clustering, Proprietary Unsupervised Learning
  22. 22. Understand Convolutional Neural Nets (CNN), Long Short Term Memory (LSTM), Natural Language Processing (NLP)
  23. 23. Parallels with Self-driving Car
  24. 24. Cognitive Automation for Business Processes Recognize Natural Language Processing Understand Enrich Computer Vision Improve Fuzzy Logic Machine Learning
  25. 25. Example: Document Classification
  26. 26. Traditional Rules based approach for Document extraction ClassifyClassify OCR Attempt OCR Attempt Validate Against Back Office Validate Against Back Office Approval Workflow Approval Workflow Final Review & Approval Final Review & Approval Process Failed Docs Process Failed Docs 4,000 Hrs. Setup Time <30% STP* Legacy Re-codeRe-code
  27. 27. Extract Data Extract Data Extract documents RPA Cognitive Post Human Validation (Split Screen) Validated Manual with improvement in efficiency Learning Digitize & Classify Bills Digitize & Classify Bills 100 Hrs. Setup Time >75% STP Document understanding Enhanced data processing Enhanced data processing Splitting and indexing Splitting and indexing
  28. 28. Traditional Rules based approach for Document extraction ClassifyClassify OCR Attempt OCR Attempt Validate Against Back Office Validate Against Back Office Approval Workflow Approval Workflow Final Review & Approval Final Review & Approval Process Failed Docs Process Failed Docs 4,000 Hrs. Setup Time <30% STP* Legacy Re-codeRe-code
  29. 29. Human in the loop Gather data for training Deep learning models Manage exceptions and learn from them
  30. 30. AI Framework Build Train LearnDeploy Gather data associated with skill to train Human training and feature extraction from data set Human and bot validation through supervised learning Push model to production and run on new input
  31. 31. Examples of Document Classification Invoice Purchase Order Balance Sheet Cash Flow 1040 Income Statement Insurance Claims Mortgage Applications Bank Statements Form 16 (India) SSI W4 GST (India) Explanation of Benefits Shipping Notice Utility Bills Nota Fiscal (Brazil) KYC
  32. 32. Dutch banking and financial services firm – Account Opening Forms Current State  As a part of the business bank account opening process, the bank’s new customers have to populate a form, thus providing key pieces of information such as name of business, annual revenue etc.  Forms are populated, printed, signed, scanned and uploaded to the bank’s online portal  Such documents are fed to multiple bank employees via a queue where data is read and entered manually into an enterprise application to initiate the subsequent process IQ Bot & Enterprise Client Solutions Design  A specific learning instance was created for such financial statements with aliases for each of the balance sheet line items  Respective groups created were trained and staged to production  An RPA Task Bot splits the document to extract specific form pages with the relevant information  Files were batch processed to create CSVs which could potentially be fed into the system using an RPA Task Bot. Pages / Document 10 Straight Through Processing 89 % Documents Sent for Validation 11 % Document Details IQ Bot Metrics Language Dutch Unprocessed Documents -
  33. 33. Sample Document & Fields Extracted KvK nummer Rechtsvorm Oprichtingsdatum Huisnummer Statutaire naam Land Plaats Postcode Toevoeging huisnummer Vertegenwoordige r Straat Gemachtigde Uitgereikt aan Betaalpas en Mjin Transactielimiet Extra Betaalpas en Mijn Belanghebbende Form Fields Table Fields
  34. 34. Business impact
  35. 35. Double Automation Growth with AI RPA + Cognitive RPA only LikelihoodofAutomation Proce ss Process Process Process Process Process Process Proce ss Process Process Process Process Process Process Process Proces s Process Process Process Process Proc ess Process Process Process Process Process Proc ess Proc ess Manual Cognitive Cog+RPA RPA
  36. 36. Best Practices for Successful Cognitive Automation 1. Identify High ROI Processes 2. Select Representative Training Data 3. Add Additional Processes
  37. 37. Knowledge workers no longer need to extract information from unstructured content – documents, images, emails, etc. Knowledge workers are free to do what they do best – make decisions and handle exception.
  38. 38. You and your competition
  39. 39. When is this happening?

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