Last week, SKL consultants Sara Lee and Aliza Yau attended the 2017 Data Analytics Seminar at the Actuaries Institute. It was indeed a very interesting seminar. It provided an opportunity to the actuarial community to get an insight into Data Analytics field. Speakers were from various backgrounds.

Key highlights and summary for actuaries on the presentations by speakers:

The actuarial professionals see the trend of incorporating data analytics techniques into the traditional actuarial work. Some actuaries are interested to see what data analytics can achieve within the actuarial industry, and some other actuaries are interested in developing their data analytics skills to adapt to the trend.

Sara Lee asked one of the speaks on what actuaries need to build up on in order to be successful in the data analytics field.

It turns out that actuaries have technical abilities and good business acumen. These are the great foundation knowledge to be prepared for moving toward data analytics field. However, actuaries need to build up on software programming skills (i.e. Python is quite popular in data science field) and the ability to communicate and articulate technical findings.

The real business problem in the analytics world is the illiquidity of data. We have world of data that is valuable. However, if we cannot move around it, then we are not really utilising it and thus cannot bring its value to the businesses and customers.

In addition, companies are very sceptical in sharing data. Data is hard to move around in the market due to regulatory restrictions and other potential violations such as privacy issue. Although we have new data for personalisation, it is inaccessible. Thus, businesses must collaborate to utilise the data and bring benefits to both customers and businesses.

With the data analytics field blooming, the data specialists are in demand. However, we need different types of data specialists to collaborate in order to achieve what we want.

Data Analysts:

  • Manipulate and interpreting data for decision marking and to solve problems.

Data Scientists:

  • Are hybrid experts in analysis and software programming.
  • Possess strong business acumen, coupled with the ability to communicate findings.

Data Engineers:

  • Support the infrastructure required to make data applications and platforms available in agencies and across the public services

Data Architects:

  • Ensure the design of data system
  • Provide technical support for systems to undertake analysis, integrate, centralise, protect and maintain the data sources.

Data policy and law Experts:

  • Monitor the effectiveness of controls
  • Resolve compliance challenges
  • Advise on legal rules and controls to meet applicable legislation and standards
Scroll to Top