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Treasure for Process Analysis
April 11, 2022

Treasure for Process Analysis

Anonymous | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with IBM Process Mining

We are using IBM Process Mining extensively to monitor our centralized cryptocurrency exchange platform and discover slacks on our systems to ensure efficient trading by our customers. It's been critical in unwinding margin positions that are at risk of default by providing analyses of our transactions. It's also critical in helping us attain a comprehensive trading model for our company.
  • It's working superbly in automation of the major performance indicators.
  • It is smooth with AML compliance (we are in crypto).
  • It's hard to aggregate event logs from external sources while producing final process models to analyze issues.
  • It has helped us with monitoring to display issues on our systems in real time.
  • Has automated most of our back office tasks, it is a treasure trove of data.
The customer support besides providing quick responses also gives very helpful insights. One time I needed assistance in tweaking our workflows, the attending technician organized a two-hour session to help me with this. I appreciate how fast the waiting tickets are responded to and the IBM team is undoubtedly knowledgeable about their software.
We are in crypto exchange and the way we are benefiting from IBM's fault spotter is by helping us to programmatically unwind margin positions during trading. Our selling point is providing our customers with downside protection through centralization; now with IBM process mining we accurately point out deviations from the key indicators under display.

Do you think IBM Process Mining delivers good value for the price?

Yes

Are you happy with IBM Process Mining's feature set?

Yes

Did IBM Process Mining live up to sales and marketing promises?

Yes

Did implementation of IBM Process Mining go as expected?

Yes

Would you buy IBM Process Mining again?

Yes

IBM Process Mining has been suitable in pinpointing issues in our models and optimizing processes. Not only is it efficient for new models but also for improving the existing ones using the event logs data you feed in. However, it may not be entirely suitable for the aggregation of data from external sources.