Use case: ThiaperProcess in banking

Process mining for banking: why? 

Reconstruct and analyze and support the re-engineering of business processes based on the actual traces in IT systems.

Discover the stories associated with the entities in your system (the pathways). 

  • Client journeys through departments
  • Invoice journeys 
  • Loan application journeys 

Measure these stories

  • End-to-end average time delays
  • Frequencies
  • Fitness 

Pinpoint the oddities

  • queues at a specific branch
  • repetitive tasks that can be eliminated
  • long throughput times
  • activities that were expected to happen, but didn’t
  • activities that occurred, but were not expected to happen

Have your in-house expert investigate further.

Should it happen or not? Can the journeys though the system be optimized or not? 

  • Is it inefficiency in HR activities? 
  • Is it the ever increasing number of demands from clients (e.g.  loan applications) that need face to face approval with a bank representative?
  • Is end-to-end banking operations processing time longer in one department versus another?
  • Is the time spent waiting for input from clients unusually long? Why?
  • Is it a task that keeps repeating although it shouldn’t?
  • Is there anything  strange in the succession of billing activities?

 

Banks invest in  AI for compliance (11.5%) and risk monitoring (14.4%), more than in  any other business area.  Is your organization keeping up? 

 

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