The Data Scientist Explains: AR Trends and Best Practices

Blog | Oct 19, 2016

Reading time: 3 min

Future technologies always have roots in today’s trends. When you implement automation and other best practices in your AR department today, you’re actually preparing your organization for future technological advancements

Read the final post in our 4-part series on accounts receivable (AR) process automation. Farhad Khalafi, Research and Development Scientist at Billtrust, describes today’s best practices, what is in store for tomorrow’s AR teams and what role robots will play in the future.

part 4/4 quantum graphic reading Q&A with billtrust's research and development scientist, Farhad Khalafi

QUESTION: What are some best practices to make sure AR automation is being utilized to its maximum potential?

Farhad Khalafi: People can be resistant to change. This is often true in the more conservative sectors of business, such as banking and accounting. Sometimes technology solutions can seem unproven, and automating those tasks can be seen as a risky endeavor. In order to encourage adoption of automation, software vendors need to use these tactics:

  • Communicate the benefits of automation in terms of increased efficiency, reduced processing risks and shorter timelines (invoice-to-cash)
  • Reduce deployment time, complexity, and cost
  • Create intuitive interfaces and promote simplicity in UI design
  • Develop testing environments and support parallel running
  • Produce effective demos and ROI analysis
  • Provide training, documentation, and support
  • Accommodate many customer requirements, customizations, and configuration requests

QUESTION: Where do you see AR automation going in the next 5 to 10 years?

FK: I can imagine that the increased use of software robots and intelligent programs will result in automating many aspects of business processes including Credit and accounts receivable (AR) functions. I can also predict that a hardware breakthrough, such as quantum computing, will facilitate further wide-spread adoption of machine learning and artificial intelligence by enabling more complex neural networks, distributed processes and agile clouds.

We will start seeing computer programs that complement and in certain cases replace the “human intelligence” in less well defined areas such as value judgment, decision making, screening, evaluations, risk management and financial planning. Predictive analytics will become an indispensable tool in business planning and strategic management.

Read the entire series!

Catch up with the rest of this interview series explaining the role of automation in A/R processes:

Article 1 - The Data Scientist Explains: Automation and Robotics

Article 2 - The Data Scientist Explains: AR Automation

Article 3 - The Data Scientist Explains: Supervised Machine-Learning

Farhad Khalafi, Research and Development Scientist at Billtrust. Farhad is responsible for incorporating the state-of-the-art technology in machine learning and robotics into Billtrust’s next generation software in Credit and A/R automation, and has over 20 years of experience in software development. He also holds a Ph.D. in Quantum Physics from the University of Cambridge, UK.

Do you have a question for Farhad? Ask him on Twitter @FarhadK