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Contributory Databases: The Change That Will Unlock New Value For Insurers

The solution is in harnessing internal and external data with an appropriate technology platform to analyse it

A contributory database is all about partnership. Individual companies join as an industry to combine their respective databases into one massive pool of information to get much needed data they cannot get individually. Contributory databases work on the strict principle of "give and take back a lot in return" with a clear set of rules that ensure fair play.

Every company has data on the insured, claims experience, cases of fraud and trends related to intermediaries and their own sales staff. All this information sits in isolation inside each company. It is of limited use for any individual company.

Every insurance company has data on the insured, claims experience, cases of fraud and trends related to intermediaries and their own agents, intermediaries or direct sales staff. All this information sits in isolation inside each company and it is of limited use for any individual company when looking for a broader, more accurate view of a risk.

When aggregated, this information - traditionally hidden from outsiders within individual companies - makes a lot of sense of what's happening in the whole market.

It has been about 15 years since private and foreign investments were allowed in the Indian insurance industry. Earlier, the market had only one life insurance company and four non-life insurance companies, all owned by the government. Today, there are 24 life insurance companies and 28 non-life insurance companies including five standalone health insurance companies. However, even after 15 years, both life and non-life insurers are struggling for profitability. Adding to the challenge is the continuing regulatory pressure for policy-holder protection on one side and solvency on the other.

Working in isolation
It appears every insurance company operates in information silos by design, and analytics is employed but only on the database that each company owns. No company gets insights into the broader marketplace based on the aggregated database of the entire life insurance industry or the non-life insurance industry.

In this context, a contributed data of information pooled from all insurers, can serve multiple purposes and holds the key to unlocking the power of the data.

Analytics is the solution
The solution is in harnessing internal and external data with an appropriate technology platform to analyse it.

Mitigate fraud, waste and abuse
One major consequence of operating in information silos is the challenge of rising numbers of fraud cases and in this respect, India shares the same issues as other insurance markets around the world. Information arbitrage by customers is a significant loss of revenue in insurance and hits the bottom-line directly. The onus is on the insurer to prove mis-declarations in applications or frauds in claims. A contributory database helps the insurer in validating some of these facts and thus mitigating frauds and abuse. For example, the suppression of smoking or alcohol consumption in life or pre-existing diseases in health is a major source of abuse. A contributory database can help identify such mis-declarations.

Improved risk selection and better pricing
Not just choosing and pricing risks wisely but contributory data also helps in saving costs. Knowing a risky driver who has a history of accidents would help in pricing that risk better.

Streamline processes
Improves customer experience
A contributory database is all about settling a genuine claim faster as much as it is about avoiding a fraudulent claim or making faster decisions in underwriting. In effect, it helps improve overall customer satisfaction.

The challenges with leveraging the power of the contributory database are multi-fold. One of the key problems for insurers in India is the quality of data. The issues are: not so clean data (including out-of-date data or other data provided fraudulently or mistakenly by the insured). In addition, there is: disaggregated data, multiple standards, systems and processes, multiple stakeholders, and the lack of clear identifiers which pose an even greater challenge in linking the data and making meaningful insights.

The solution is in big data technology and an effective linking mechanism. The use of the aggregated database is underpinned by strict rules and a robust platform in the regulated environment.

Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house. Unless otherwise noted, the author is writing in his/her personal capacity. They are not intended and should not be thought to represent official ideas, attitudes, or policies of any agency or institution.


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