Business Process Automation
What is the goal of Business Process Automation?
Automate the implementation of a task
or set of tasks, such that it requires less
manual work.
Improve:
● Speed
● Robustness
● Scalability
● Cost
● Efficiency
What processes are automatable?
Deterministic / Predictable
Screening / reviewing
Quality control
Document info extraction
Customer contact strategy
“Swivel chair” operations
Routing of customers and employees
through a set of actions
Repetitive, (simple) tasks
Sales pipeline optimization
Robotic Process Automation
● Flexible Integrations
● Screen reading, API access
etc.
● Rule based system
● “If this then that” logic Known Sender?
Mentions Bitcoin?
Mentions “Get Rich Quick”?
Classifying [potential] spam emails
myemail
Exception prone
Limitations of RPA
Hard to encode analysis Limited to simple tasks
Machine Learning
Machine Learning 101
● Provide machine with known examples
● It will learn patterns in the data
● Can take action based on patterns learned
SPAM
SPAM
Classifier
Inbox
Spam Folder
Machine Learning alongside RPA
Analysis
&
insight
Actions
&
automation
Gather, upload &
prepare data for
machine learning
Train machine
learning model
using existing
examples
Test and analyze
your model -
understand how it
makes decisions
Use your model to
make business
predictions
Building Machine Learning models
Machine Learning applied to BPA
Advantages Considerations
● Flexible to data sources
● Closer to human intuition
● Easier to manage
● Easier to train
● Requires existing data
● Interpretability
● Predictability
● Computational expense
Transaction
99% false alert
Rule-based system
(RPA)
✔
? Manual review
✔
✘
Costly and time consuming
Case Study: Compliance with Transactions Sanctions
Transaction
% confidence
Reduce manual reviews
✔
Increase automated
approvals
Machine Learning
Case Study: Compliance with Transactions Sanctions
Example data is
available
Might require language
processing
Personalizable
Repetitive
Process
Data-driven
(large volumes)
Human-intensive
Is my process suitable
for Machine Learning
Automation?
Transaction compliance and fraud detection
Call Centre automation
Customer churn risk assessment
Automated product recommendations
Loan + insurance applications
Workforce schedule optimization
ML Automation in Practice
Supporting
Services
Solution
Definition
Monitoring &
Remediation
Ongoing
Innovation &
Upgrades
Governance &
Signoff
Historic Audit
& Exploration
Complete solution definition
Compliance Case Study
Model
ActionsPredictions
Solution Monitoring + Alerts
mind 3
Compliance mind
400 Outliers detected in the last
hour. URGENT REVIEW.
Performance verification overdue.
Verify now. more
mind 1
Compliance mind
Data drift detected; increase of 20% in
transactions over $100,000 in last week.
more
User James proposed a change in
response to data drift Review it now. more
Decision and Solution Audit
Why were decisions made?
What were the driving factors?
How can decisions be justified?
Solution Upgrades
& Comparison
mind 1
Compliance mind
Solution comparison complete. 27%
improvement detected. more
User James proposed change to model
configuration more
Furnace
API-driven Bayesian optimizer
Meta Learning Engine at the core of
our platform
Analyze
Machine-learning
workbench
Collaborate to solve
your use case
Horizon
Time-series
Forecasting
Build models that
you can trust
minds
Operationalized
machine-learning
Integrate with your
existing infrastructure
THE MIND FOUNDRY PLATFORM
Machine learning integration for enterprise.
A mind has the agency to take your
automation strategy to the next level
mind 1
Compliance mind
425 transactions sent for review
More
Cost savings for June estimated at £3723.
Explore Analysis
Questions?

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Machine learning for business process automation

  • 2. What is the goal of Business Process Automation? Automate the implementation of a task or set of tasks, such that it requires less manual work. Improve: ● Speed ● Robustness ● Scalability ● Cost ● Efficiency
  • 3. What processes are automatable? Deterministic / Predictable Screening / reviewing Quality control Document info extraction Customer contact strategy “Swivel chair” operations Routing of customers and employees through a set of actions Repetitive, (simple) tasks Sales pipeline optimization
  • 4. Robotic Process Automation ● Flexible Integrations ● Screen reading, API access etc. ● Rule based system ● “If this then that” logic Known Sender? Mentions Bitcoin? Mentions “Get Rich Quick”? Classifying [potential] spam emails myemail
  • 5. Exception prone Limitations of RPA Hard to encode analysis Limited to simple tasks
  • 7. Machine Learning 101 ● Provide machine with known examples ● It will learn patterns in the data ● Can take action based on patterns learned SPAM SPAM Classifier Inbox Spam Folder
  • 8. Machine Learning alongside RPA Analysis & insight Actions & automation
  • 9. Gather, upload & prepare data for machine learning Train machine learning model using existing examples Test and analyze your model - understand how it makes decisions Use your model to make business predictions Building Machine Learning models
  • 10. Machine Learning applied to BPA Advantages Considerations ● Flexible to data sources ● Closer to human intuition ● Easier to manage ● Easier to train ● Requires existing data ● Interpretability ● Predictability ● Computational expense
  • 11. Transaction 99% false alert Rule-based system (RPA) ✔ ? Manual review ✔ ✘ Costly and time consuming Case Study: Compliance with Transactions Sanctions
  • 12. Transaction % confidence Reduce manual reviews ✔ Increase automated approvals Machine Learning Case Study: Compliance with Transactions Sanctions
  • 13. Example data is available Might require language processing Personalizable Repetitive Process Data-driven (large volumes) Human-intensive Is my process suitable for Machine Learning Automation?
  • 14. Transaction compliance and fraud detection Call Centre automation Customer churn risk assessment Automated product recommendations Loan + insurance applications Workforce schedule optimization
  • 15. ML Automation in Practice
  • 19. Solution Monitoring + Alerts mind 3 Compliance mind 400 Outliers detected in the last hour. URGENT REVIEW. Performance verification overdue. Verify now. more mind 1 Compliance mind Data drift detected; increase of 20% in transactions over $100,000 in last week. more User James proposed a change in response to data drift Review it now. more
  • 20. Decision and Solution Audit Why were decisions made? What were the driving factors? How can decisions be justified?
  • 21. Solution Upgrades & Comparison mind 1 Compliance mind Solution comparison complete. 27% improvement detected. more User James proposed change to model configuration more
  • 22. Furnace API-driven Bayesian optimizer Meta Learning Engine at the core of our platform Analyze Machine-learning workbench Collaborate to solve your use case Horizon Time-series Forecasting Build models that you can trust minds Operationalized machine-learning Integrate with your existing infrastructure THE MIND FOUNDRY PLATFORM
  • 23. Machine learning integration for enterprise.
  • 24. A mind has the agency to take your automation strategy to the next level mind 1 Compliance mind 425 transactions sent for review More Cost savings for June estimated at £3723. Explore Analysis