Big Data has quick solutions for insurance

Predictive analytics and big data concept with hand holding modern smart phone to analyse data from marketing, shopping, cloud computing and mobile devices. PHOTO | FOTOSEARCH

What you need to know:

  • Insurance has a wide range of customers with varied needs. Customer service-led organisations have embarked on the implementation of RPA and Big Data to serve their clients.
  • Business intelligence, robotic process automation and integrated systems have progressively reduced the need for people to conduct mundane tasks.

The insurance industry is more than ever driven by data and technology as the corporations harness information to make predictions on business dynamics.

Business intelligence, robotic process automation (RPA) and integrated systems have progressively reduced the need for people to conduct mundane tasks.

This has led to paperless operations and significant growth of self-service portals for the millennials. Forward-looking firms are leveraging BI to drive product development and innovation, to simplify processes, with the aim of efficiency and quick turnaround.

CUSTOMER DEMANDS

The quick shift has been due to customer demands for quick and easy solutions. Today’s customer does not want to come to an office or wait at a reception for a manual solution. They want speedy and error-free on-demand digital solutions.

Insurance has a wide range of customers with varied needs. Customer service-led organisations have embarked on the implementation of RPA and Big Data to serve their clients. The use of chatbots — with which customers can receive a quotation for a product, pay for it and check due dates for their premiums — will become the norm.

These inclusions will aid in compliance with the Insurance Financial Reporting Standards (IFRS) 17.

These solutions will see chatbots collect premiums in full within a 30-day period in addition to implementing cash and carry. The ultimate goal is to provide the ability to load claims and purchase a policy online through the self-service platform and chatbots.

As a consumer of Big Data, the insurance sector is one of the most challenging since insurers collect large amounts of data from customers, intermediaries and healthcare providers. They, in turn, have to evaluate risks and decide on the premiums to charge customers.

CYBERCRIME

Data, therefore, can be employed to curb fraud and save the industry millions of shillings while making setting of the cost of premiums appropriate and aligned to demographics.

But digital transformation has also come with its risks and threats on data security. According to a study by the Center for Strategic and International Studies (CSIS) and McAfee, cybercrime costs the global economy as much as $600 billion (Sh60 trillion), which translates into 0.8 per cent of total world’s GDP.

That means vulnerability assessments have to be conducted while penetration testing and audits are a must prior to launch.

Reliable firewalls, double-factor authentication and customers’ consent are some of the levels of protection necessary for system security.

SOCIAL MEDIA ANALYTICS

Corporate bodies must constantly survey the market on a regular basis and gain insights from customers, develop digital laboratories for research, while utilising data and social media analytics, to provide further insight into customer preferences and behaviours and product innovations.

The foundation that is being laid by artificial intelligence (AI), machine learning, blockchain, data analytics and predictive analytics will help insurers to grow and adjust with new insurance technologies and capabilities.

To be prepared for a digital future, insurers must adopt the tools of digital transformation and find creative ways to optimise operations.

Mr Ngari is the head of digital at Resolution Insurance Ltd. [email protected] @Hoyeiya