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An accelerated cloud adoption strategy for the New Age of Digital Insurance
An accelerated cloud adoption strategy for the New Age of Digital Insurance

May 22, 2023

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Julia Roberts, a popular American actress, has reportedly insured her Smile for $30 million, and Cristiano Ronaldo has insured his legs for $144 million. Bizarre right?

As strange as it may sound, the insurance industry has boomed in the past few years, and now you can insure just about everything you own.

However, this new-age insurance game is becoming increasingly digital

Over the next decade, the insurer will be fully geared with the technologies such as cloud, data analytics, artificial intelligence, machine learning, and blockchain for driving operations, providing improved customer experience, and inducing trust and transparency in the process. 

Despite the picture looking merry from afar, the current digital scenario in the industry needs a lot of improvements and modernization. Rapidly changing customer demands, extreme price competition, and the growing cost of losses are some of the biggest risks for insurance providers moving slowly to the digital world.

Reality Check for Digital Insurance.

New entrants in the industry, insurtechs, are backed with new technologies, funding, and vision to drive product innovation, reduce costs, and improve scalability, which poses a threat to established and large industry players. The new entrants are enticing customers with a better value proposition by offering cloud-enabled and data-driven products. Digital insurance is gaining popularity, and these innovative products are becoming mainstream, especially after the COVID pandemic. Meanwhile, established insurance companies find it difficult to keep up with the rapid changes.

According to Global Insurtech Market – Growth, Trends, and Forecast, global insurtech market revenue was valued at $5.48 billion in 2019 and is expected to reach $10 billion to $14 billion by 2025, growing at a compound annual growth rate (CAGR) of 10.8% between 2019 and 2025.

The Insurance Industry is All About Data!

Traditional insurance companies are embracing new technologies to drive the transformation of their businesses, primarily based on cloud computing. Fuelled by an urgency to join the bandwagon and step into the league of digital insurance, these established players are making some very bad decisions. 

Companies are making the mistake of moving everything all at once into the cloud, which leads to migrating uncentralized and unstructured data, making it impossible to derive intelligence from it. Furthermore, the traditional lift-and-shift operations without any analytics add to the complexity, cost, and risk in the cloud. Abnormalities, errors, risks, duplicate, or unimportant elements of the legacy infrastructure will now be stored in the cloud, exposing a wide variety of vulnerabilities that may lead to a breach.

The solution to this is to harness the power of analytics from existing data assets and leverage it to transform digitally. Understanding the data residing within the system before moving to the cloud is the first step to avoiding the mess later on and simplifying the process. Once enterprises understand the data, they can easily classify and tag data files and make the right choices in selecting the cloud solution and optimizing storage by distinguishing cold data from hot data. This can impact IT spending by reducing the cloud cost significantly. Additionally, organizations can easily identify risk-prone, personal, and sensitive data. This data can then be secured, protected, and governed to avoid any risk.

Let’s take a closer look at why insurance is all about data and why data has become one of its biggest assets. Here are the biggest data points in the insurance industry value chain:

  1. Customer information: The most important data set where customer details are recorded from policy documents, personal information, address proofs, and personal ids, claim documents.
  2. Asset Information: This includes the Data related to the insured asset and related laws and information. 
  3. Policy and claim management: This might include the various versions of policies and claims processing and can vary from customer to customer.
  4. Estimation data: the insurer calculates the risk of the insurance and associated losses. This is traditionally done manually by considering multiple factors: historical Data, behavioral data, non-insurance data, and more.

This is just the tip of the iceberg, as various hidden data points in the insurance industry go unnoticed during manual analysis. This results in enormous amounts of data, which organizations typically store in data lakes. In data lakes, the data is duplicated, unsupervised, and unutilized, adding a number of challenges such as lack of data knowledge, data sharing with access control, and inducing security risks.

What is a data lake? – A data lake is a repository that allows you to store all your structured and unstructured data at any scale.

Aggregating these data lakes into a centralized data ocean becomes crucial for ensuring data consolidation and robust privacy & security of personally identifiable information (PII). Data oceans exist in the cloud. Data management in a data ocean is a one-time activity instead of multiple rounds of management, analysis, security, and compliance checks across numerous data lakes.

What is a data ocean? DataOceans offers one comprehensive platform that optimizes your data to deliver more effective communications across your enterprise and better customer experiences & business outcomes, enabling long-term growth.

 


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