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The CFO's Guide to Investing in AI - Abacus


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CEO Omar Qari delivered this presentation live at Intacct Advantage 2017 on October 19, 2017. See the full white paper at To learn more about intelligent expense reporting, visit

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The CFO's Guide to Investing in AI - Abacus

  1. 1. Real Time Expense Reporting Investing in AI The CFO’s Guide to
  2. 2. AI is helping teams get more done. Every team needs an AI strategy.
  3. 3. The finance team’s work is changing…
  4. 4. Here’s how much extra time you’d have to focus on adding value work if you made manual work to only 10% of your time.
  5. 5. It’s OK to be skeptical. Chatbots will not help you close your books anytime soon.
  6. 6. AI combines three developments:
  7. 7. Artificial Intelligence A computer system that can make decisions and solve problems autonomously. More accurately, the field of computer engineering dedicated to creating these systems. Machine Learning Automated data analysis that builds analytical models through repeated trial and error. Deep Learning What happens inside a neural network. Neural Network A trainable computer system made up of interconnected processing elements. With multiple levels of processing, any complex task can be divided into relatively simple bits of data analysis. Machine Learning Algorithm A formula or programming command that teaches computers how to figure out how to solve problems. Applying an algorithm is what makes a computer “intelligent.” Helpful definitions
  8. 8. AI is about structured data. Machine learning finds patterns in big data, which aligns it uniquely with Finance’s skillset.
  9. 9. Think of it as your newest team member.
  11. 11. Invest in AI where
 it returns the most
 near-term value.
  12. 12. Automate
 manual work Application #1 Use AI to realize new
 productivity gains.
  13. 13. r Abacus and NASS Case Study Predictive expense management helped the field services company spend 35% less time on reconciliation.
  14. 14. Prevent fraud Application #2 AI finds the kinds of anomalies that indicate 
  15. 15. r Preventing fraud risk at POS Case Study Sift Science helped OpenTable reduce review time by 80% and improve detection by 200%.
  16. 16. Uncover hidden insights Application #3 AI makes your strategic advisory more valuable.
  17. 17. r Product suggestions boost online sales Case Study AI-powered recommendations increased the site’s revenue per user by 16%
  18. 18. How to 
 manage the cultural shift Get your team excited 
 for AI Train your people in data analytics and cross- channel communications Learn and practice good management
  19. 19. Why are we talking so much about 
 AI now? “AI” is a generic term that’s been around since the 1950s. Machine learning has been around since the 1940s. For decades, progress on AI was slow. Recently, development has accelerated as machine learning systems have gotten access to enough computing power and enough data to be able to learn. FAQ
  20. 20. How does AI differ from normal software? Is software simply getting better? Traditional software is able to solve problems that humans set up. Machine learning is able to set up problems for itself. It’s the difference between calculating a formula and being able to write a formula itself. FAQ
  21. 21. Is AI “coming” or is it here? AI will evolve gradually, like any other technology. Some capabilities are available already, but researchers are developing more every day. New features will develop in other departments before becoming stable enough for Finance to trust. But AI is definitely coming; even the next version of Excel is set to include machine learning capabilities. FAQ
  22. 22. What is AI good at now? • Finding outliers & insights in bodies of data • Automating complex processes in specified domains • Reading and processing text • Compliance assurance, audit prep, financial reporting • Predictive intelligence FAQ
  23. 23. What challenges will I face implementing AI? According to research by Salesforce, companies typically encounter four problems when preparing for AI: • Data is often siloed. • Expertise: Data scientists and other experts are scarce and expensive. • Infrastructure: Powerful computing can be cost-prohibitive. • Context: AI is considered science- fiction and out of reach. FAQ
  24. 24. Download our eBook,
 “The CFO’s Guide to 
 AI Strategy” Real Time Expense Reporting @abacus