Shreya I think this is a very important qusetion, and I appreciate that fact that the CAS is engaging in this discussion. Let me look at the issue from a slightly different angle in an attempt to provide some thoughts on Dave Menning's qusetion.From the statistical perspective, specifically within the world of predictive analytics, I agree with some of the other posts that there is a lot of opportunity. There are three fundamental skill sets that underlie any predictive analytics task, which are data processing and manipulations skills, the application of statistical and modeling techniques to the data, and an understanding of the business process to which you are applying the analytics. Adding material to the CAS basic education process could be used to address the theory behind some of the statistical techniques, but the application of these techniques would be difficult to test in a traditional environment. Basic concepts of data processing could also be tested under the current testing system, but this would be of limited value. There are currently two certifications that I know of that focus on predictive modeling, and both of those are tested using actual software and data as part of the assessment. So for the first two elements of a predictive analytics project, adding some statistics to the syllabus would help, but to truly prepare an actuary to work in this environment, expanding that to include an understanding of data and an assessment by the use of some actual data and modeling processes would be ideal.The last piece of the analysis, and arguably one of the most important, is the understanding of the business process to which you are applying analytics, and expands somewhat on the qusetion that Dave asked. When thinking about the application of predictive analytics to rate plan development, I agree that while actuaries still have a strong presence in this area, there are many non-actuaries performing this work as well. I believe adding some statistical content, especially as it relates to techniques in addition to GLM's, will help solidify our position in analytics related to ratemaking. The more difficult qusetion to answer is how we apply actuarial and analytic skills more in the non-ratemaking insurance areas, such as claims, marketing, pure underwriting, etc, and ultimately outside of P&C insurance. It is in these areas that we have a more limited presence, and the demand is being met by non-actuaries. I don't think the answer in this case is to devote more syllabus time to understanding the insurance and other functions more thoroughly, but clearly there are skills that actuaries have that can be beneficial in these other areas. The challenge is how to break through to these areas in a significant way. This a bit off topic and probably better suited for a separate discussion stream.So in short, I think adding some statistics will help, but the greater benefit would come from hands on preparation and training that would require a different testing or assessment process.