About the Company: 
The company in question is a subsidiary of a global insurance and reinsurance company. It has more than 100 offices in 6 continents.
In 2016, the company wrote $13.890 billion in gross premiums, of which 69% was insurance, 29% was reinsurance, and 2% was other. Of the company’s gross insurance premiums, 19% was for professional liability insurance, 32% was for casualty insurance, 25% was to the energy sector, and 24% was for speciality insurance such as pollution insurance, aviation and satellite, marine, product recall, political risks, equine, and fine art insurance.

Fixing the policy renewals process
The revenue for insurance companies comes from careful risk analysis to ensure that the liability exposure is as limited as possible. In addition to that, their margins also depend on policy renewals once they’ve expired. This is a challenge because individuals and organisations might not be proactive about renewing their policies if there were no incidents when they were covered by insurance. 
It’s the responsibility of the business analysts and the quality team to predict the probability of policy renewals to ensure that there’s no break in the revenue stream. The increase in the complexity of the parameters upon which accurate predictions are dependent, led to bottlenecks that were affecting their productivity and was leading to a loss in revenue.

Bridging the skills gap
The team needed cutting-edge analytics skills to apply contemporary data modelling techniques to create accurate models. This was a critical point for the team as it was directly tied to their revenue. 
The teams in question also had a mix of professionals from both technical and non-technical programs, so a standardised upskilling program would not have cut it. 
In addition to this, their employees are spread out all over the country which meant that any upskilling initiative had to contend with delivery over different geographical locations.

An analytics program customised for the insurance industry
Since their employees needed to pick up skills specific to the insurance industry, Great Learning designed a program that was customised to the unique needs of the company. The program included contemporary analytics trends that were being used by top companies to solve their business problems. 
The program was also modified so that employees without technical experience were able to follow the curriculum, while still being engaging and valuable to the technical professionals.

Upskilling employees all over the country 
Since these employees were spread out over different locations, Great Learning chose a blended approach of an immersive classroom-based methodology, along with live-streamed online program delivery for different locations. The learning experience was bolstered by case studies that showcased how other companies leverage analytics to deliver business outcomes.

Building an intelligent customer segmentation solution 
After participating in this program, the employees were able to build successful models, to segment their customer base according to the likelihood of them renewing their policies. This enabled the company to predict future insurance policy renewals with greater accuracy. Eventually, this is projected to increase their revenues substantially, and reduce the human resource cost of having to hire specialists.

Upgrading the workforce for a better future
The upskilled employees are also more likely to be engaged in their jobs, which reduces the long-term attrition rate. They now have a strong pipeline of skilled professionals who can be groomed for leadership positions in the future. 



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