Anatomy of Today’s Global Traveler

Infographic | February 4, 2020

Do you know the difference between a Hard Insurance Market vs a Soft Insurance Market and the impact it has on your insurance rates? Check out the info-graphic below explaining the difference between the two. Soft insurance markets tend to lead to good conditions for buying insurance, while hard markets tend to lead to the opposite or bad conditions for buying insurance, IE higher costs. What market are we currently in you ask? In short, we are currently in a soft insurance market that is beginning to harden.

Infographic | January 8, 2020

The technology risks and manifestations are potentially interconnected, e.g. a breach could be caused by a staff error which leads to extortion which rejected leads to interruption.

Infographic | August 25, 2021

Emerging from a prevailing pandemic, the industry has to face few upfront hallenges. Some of these include risk management, claims management in the backdrop of the Covid 19 pandemic, digital innovation etc. These challenges will prompt the relevance of insurance BPO in 2021. In this infographic, we look at the role of BPOs inghe insurance sector this year.

Infographic | December 17, 2019

All too often, the same question is asked. What is Professional Indemnity Insurance? Given how many professionals work in Australia, it’s benefits should be more well known. In this infographic, professional Indemnity Insurance is explained simply and easily so you can get the most out of your business insurance.

Infographic | June 30, 2022

Customer experience is the single most crucial factor determining loyalty 85% of insurers are using CX initiatives throughout the customer journey & 90% have a c-suite position dedicated to the consumer experience

Infographic | January 16, 2020

AI can improve productivity and help in decision making through training datasets. According to the survey of the Dataconomy, nearly 81% of 225 data scientists found the process of AI training more difficult than expected even with the data they had. Around 76% were struggling to label and interpret the training data.