I have worked with several banks in the past, including Deutsche Bank, where they had a fixed ticket size for equity trades. While working with these banks, I have used various tools and platforms, including Pico Corvil Analytics. In my experience, it is essential to have someone who understands analytics to make the most of these tools, including predictive analysis and handling large amounts of data. The biggest challenge is integrating all the data into a cohesive picture. If a firm does not have someone with expertise in utilizing Pico Corvil Analytics, it can be difficult to achieve optimal results.

If a client wants to get the most out of Pico Corvil Analytics, they need an expert who knows the application inside and out. Some clients may see a very high positive return on investment, while others may not see much benefit or even a negative impact.

When it comes to order execution and revenue, at this time we are just using it to analyze the network-level details. When it comes to running a dark pool, of course, the side effect of having the best execution is getting better revenue, better order flow. It does help in terms of keeping the system competitive.

I'm not familiar with the dollar amounts, what the business makes from the dark pool, but it has definitely improved in keeping it more up to date and competitive with respect to the other banks that are running dark pools.

Our ROI is probably more cost-avoidance than anything. Corvil allows us to see where our issues are and then we don't waste money on areas that aren't going to give us the biggest gains. The whole Solarflare example I mentioned elsewhere is a good one.

As I am working more with Corvil, it looks like it is improving diagnostic times.

In the cases where we go live with any new client, or if we go live with any new exchange flow, then it helps to know the latency on day one. Then, we can produce the latency comparing it to any other flow or with any other statistics. E.g., if their latency has increased or improved the performance. It definitely helps in doing this.

This solution help us determine where to focus our performance improvement efforts. It quickly identifies areas of concern from a performance perspective. It allows us to see the outliers and any increases in the median latency, which tell us whether or not there is a specific area that we need to focus on in terms of performance improvement.

Broadly speaking, this solution has reduced incident diagnosis times because it is a tool that we don't have elsewhere. Sometimes, we use it to breakdown issues.

We seen increased productivity from using this solution. It provides us with a holistic overview of the client order flow through client connectivity to our internal components and risk checks in an exchange. This is not something that we can easily provide ourselves. By definition, it increases our productivity because it allows us to have visibility of that flow in a more granular way.

Corvil has also reduced the time it takes us to isolate root causes.

It helps us determine where to focus our performance improvement efforts. We can ensure the round trip time: From the time we push out an order to the time that we receive an ACK back. Before we started using this tool, we didn't have any visibility into this scope of information. Now that we do, we can tweak our performance on the smart order routing (SOR) engines.

Corvil reduces incident diagnosis time. Market data feed going down triggers a traffic detection gap, which will send an alert to our SNMP destination. Without Corvil, it would take 20 to 30 minutes, and with Corvil, it takes a minute. We have incidences pretty often, so this solution is saving us about two hours a week.

We have seen increased productivity from people using Corvil in the bank. From a fixed point of view, they get a look at the data and payload. 

It has reduced the time that it takes to isolate root causes.