How to avoid insurance fraud

It’s well known fact that most of the insurance companies across the globe are undergoing multiple challenges to operate economically and efficiently. Here, some of the key areas are highlighted where still many insurance companies that do not likely to struggle, perhaps even to survive in the market those includes, comply with the new and existing regulations, to meet competitive pressures, customer demands, taxation, distribution channels, managing policy administration system that support the current practice and capable for futuristic demands, sketching the strategy from existing business model to world’s highly demanding digitization, solvency and so on. In midst of these critical and frightening environment, couple of risks associated with all insurance companies over the many years, even with the inception of concept called “Insurance”  where many insurers are still struggling to address those pain points – “Moral Hazard” and “Adverse Selection”. 

Moral hazard and adverse selection (Anti-selection/ Negative selection) can be defined in the simpler way but they are very complex to handle during the business operations. We can distinguish moral hazard from adverse selection, which is caused by hidden information rather than by hidden actions.

Moral hazard is a situation in which insured willingly commits, participates or enhances the risk of loss in an event knowing that it is protected against the risk and the insurer will incur the cost.  Simple example could be taking your laptop or an expensive camera without adequate packaging or securing on a trip abroad when it is covered on an All Risk Cover.

Anti-Selection is a situation where insured have information that insurer is not aware (or vice versa) about some aspect of contract (Policy document).  Not disclosing a preexisting illness or similar material risk information is an anti-selection against the insurer.

Sometimes insurer could also indulge in Ant- selection by selection of only good risks and total avoidance of any so called bad risks.  This is done either by rejecting proposals or by quoting very high unreasonable premiums to ensure the insured will not opt for insurance.  A classic example is the recent health insurance situation in US where the Government has to step in with regulations like PPACA popularly known as Obamacare to provide affordable health care to elderly people.

Information is wealth

It is estimated that multi-million USD has been paid by insurance companies worldwide as leakage due to moral hazard.  Economists argue that the inefficiency of the insurer results in information asymmetry. If insurance companies could perfectly observe the actions/proposals of their clients, they could deny coverage to clients. However, since insurance companies cannot perfectly observe their clients' actions individually, the insured risk will be gauged based on the information & material facts disclosed in the proposal only, “If something goes out of control by manual efforts, finally we depend on technology to safeguard or protect from the loss, but once again the technology is controlled by us”.

In many occasions, we had complete dependency on technology to control or reduce the loss arose. In this way, insurers in current age are focusing on technology to win over the current handicaps. Though technology has laid before insurers huge volumes of data, insurers have to use the right set of tools to translate the data availability into a interpretative form to the insurance companies.  This has led to the evolution of data based technology fields like data analytics, data mining, business intelligence and digitization which will help insurers to optimize benefits from data.

In today’s world technology plays a key role in Insurance companies globally are keen to optimize the available information to the best use. Though there are many process are defined by insurers to control adverse risk selection and identify moral hazard. 

Adverse risk selection is handled through prudent underwriting, imposing deductibles and co-payments, refusal to insure (postponement & decline), claim scrutiny etc., however the risk cannot be totally eliminated.

Moral Hazard is handled by effective claim scrutiny and by imposing policy conditions which prevents payment of claims due to aggravation of risk after the loss.   Quick response to a claim intimation and ensuring early claim assessment is also a prevention for moral hazard.

Data mining is a powerful new technology with great potential to help insurers to focus on the most important information in the data they have collected about the behavior of their customers and potential customers.

Data analysis is the process of finding the right data to answer insured’s question, understanding the processes underlying the data, discovering the important patterns in the data, and then communicating their results to have the biggest possible impact.

Business intelligence (BI) is the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes

Digitalization is the process of converting information into a digital format.  Digitized information is easier to store, access and transmit, and digitization is used by a number of consumer electronic devices.  

Data related information will ensure the history of events, claim-loss ratio, product design, distribution channel, target customers, geographical nature (endemic & epidemic) and also assist in arriving the mortality and morbidity, etc. Insurer can very well draw a line on behavioral aspect of insuring people and underwrite accordingly will ensure the profitable (in terms of  reduction in claim payments arise due to Moral hazard and anti-selection) operational flow.

An example of this could be the current fraud indicators for motor claims which is embedded in most of the claims applications today.  The fraud indicator is designed based on the voluminous data collected to identify and isolate incidents which could be an indication for moral hazard.  A simple factor like the timing of the accident and the location could be pointer for the possibility of a moral hazard.  An early morning accident in an isolated road outside the city limits could trigger the fraud alarm for the investigation which can help insurers to probe further.

Conclusion: It’s been noted that the whole insurance industry across the globe has been forced to take up the digital transformation to sustain in the market to meet the customer demands and to be par with competitors. Though, the understanding of digitization and strategy towards the transformation of existing business model to advancement is still in questionable trend. Many insurers are eager to develop their competency with support of multiple external stakeholders. The painful but beneficial transformation might help the insurer to carry out the business effectively and economically. The key benefit of this transition is to pave the way to reduce Moral hazard and Anti-selection which hinders the insurer for the long time and support them to reach their desired goal.