IBM Watson Explorer Review

Has helped reduce manual labor in fraud detection, but stability is an issue

What is our primary use case?

It's primarily used with business analytics and also to take care of some of the fraud detection.

I've been using it for two years and it has been working well.

How has it helped my organization?

Implementing the solution really helped with manual labor, it takes care of a lot of FT work. For example, you could have 30 or 40 physical inspectors doing fraud detection, versus using this to get there, to take care of it.

What is most valuable?

Valuable features are the aggregation mode, that's one of the tool sets. And then, training the models, it can also be utilized for that.

What needs improvement?

I would say, give some kind of a community edition, a free edition. A lot of companies do, even Amazon gives you some kind of trial and error opportunities. If they could provide something like that, it would be good.

For how long have I used the solution?

One to three years.

What do I think about the stability of the solution?

Stability is actually one of the areas that could use improvement. Setting it up is always tough. Setting Explorer requires experts, but also the underlying platform is not that stable. So it really needs a good expert to keep it running.

What do I think about the scalability of the solution?

Scalability is fine, it can scale, but it definitely needs experts to do that.

How are customer service and technical support?

IBM technical support, I've worked with them multiple times. I would say there's a lot of improvement that could happen. Compared to any other organization, the speed is an issue. By the time your escalation goes up - it needs a lot of escalation. If you need to go up to the technical account manager, all the way up, it takes hours. People are looking to get the result in minutes. Nowadays, if you're really looking at hours or days, it's a little bit old-fashioned.

Which solution did I use previously and why did I switch?

We actually had nothing before this. People had a business problem, and they came to us, and this was available, part of a suite, and we started using it.

Our most important criterion when selecting a vendor is the supportability; long-term, like in a brand name, that they actively support it, and I know they'll stand behind it. It's not that you'll go with it and they change in a couple of years from now, or the company is not there at all. That's not something we should be a part of.

We went with IBM primarily because Watson Explorer is a bit differentiated. I don't think the others have that kind of deep analytics. If you have that, in a developer community in the space, it can really go even further. For our specific use case, IBM was the right fit.

How was the initial setup?

It was complex.

Which other solutions did I evaluate?

Teradata was one of them, Oracle was definitely there in the mix, Amazon as well.

What other advice do I have?

Look at the entire gambit, and look for your specific use case, or specific business problem you're trying to solve. Analytics is a big, wide area, so you want to really make sure. Look for the top-notch players. IBM is one of them, and I think you should be looking at the entire group. So rather than looking at, "I want to go to cloud, I might pick up Amazon," you need to consider the whole thing.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
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