Insurance companies are now using analytics, not only for fraud management but also for cross-selling of their products. These include on-boarding as well for bringing down fraudulent claims.
"At Reliance Nippon Life Insurance, we rely on propensity-based Analytics - for fraud management and post issuance risk assessment - to help selections of insurable life and curb anti-selection. It has helped us strengthen the underwriting guidelines and on-boarding process. We have been able to reduce programmed death claims - even dead man policy cases - by use of various modules in our analytics," said a spokesperson of Reliance Capital.
Under Section 45 of the Insurance Laws (Amendment) Act, no claim can be rejected after three years for any reason. This means the insurer has a three-year window to reject claims on grounds of any misstatement or fraud. Hence, this repository would help them weed out criminals before they are part of the insurance pool.
Private life insurer IDBI Federal Life has internal models to detect fraudulent proposals based on past claim experience and frauds. The company is implementing data analytics solution to make these models more robust and completely automated. Further, they have also implemented Hunter Solution from Experian India. This is an industry level initiative coordinated by Life Insurance Council.
It is not automated, but manual as well. Tapan Singhel, managing director and chief executive officer, Bajaj Allianz General Insurance, said that they use a combination of automated and manual measures to curb frauds.
The company has developed an analytics model for health and motor claims, which brings to the fore certain claims that cross a set threshold or indicators.
Singhel said these cases are then further investigated by the in-house investigation teams through on-ground enquiries.
"To further facilitate analytics, the company has digitalised its claim reports and is in the process of building advanced analytical capabilities," he said.
Modelling techniques are also being used.
Niraj Shah, Director Marketing, Strategy & Products, PNB MetLife Insurance said that they use analytics extensively to improve the quality of our business and increase efficiencies by mapping productivity.
"We do also cluster analysis to identify behavior of high performing distribution and share best practices across the system leading to higher productivity," said Shah.
He said that analytics also helps us identify potential frauds at underwriting and claims stage.
Others are not far behind. Bajaj Allianz General Insurance which has been working with a database of around 7 million active customers, identifies the requirements of the customers through segmentation and propensity modelling, which enables it to offer need-based solutions to them.
Credit information company Experian India has launched Hunter Fraud Management Services earlier this year for the life insurance sector in India. The offering was to help life insurance companies to be a part of the Hunter Closed User Group (CUG) for detection of life insurance fraud.
Life insurance companies that join the CUG will share with Experian any data relating to new policy proposals and claims. The credit information company is looking to offer similar services to general insurers as well. In India, Experian is the only provider of application fraud detection services using National Hunter.
Apart from fraud, cross-selling is also an area of focus for the insurers. IDBI Federal Life for instance, is currently in the process of implementation of a data analytics software for its customer retention mainly focused on persistency and renewal collections . The company expects to further extend this analytics software to develop models to help us to up sell and cross sell to their existing customers in the near future.
"At Reliance Nippon Life Insurance, we rely on propensity-based Analytics - for fraud management and post issuance risk assessment - to help selections of insurable life and curb anti-selection. It has helped us strengthen the underwriting guidelines and on-boarding process. We have been able to reduce programmed death claims - even dead man policy cases - by use of various modules in our analytics," said a spokesperson of Reliance Capital.
Under Section 45 of the Insurance Laws (Amendment) Act, no claim can be rejected after three years for any reason. This means the insurer has a three-year window to reject claims on grounds of any misstatement or fraud. Hence, this repository would help them weed out criminals before they are part of the insurance pool.
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Data from life insurers show there is an at least a 20 per cent rise year-on-year in fraudulent claims, including claims in the name of people who do not exist.
Private life insurer IDBI Federal Life has internal models to detect fraudulent proposals based on past claim experience and frauds. The company is implementing data analytics solution to make these models more robust and completely automated. Further, they have also implemented Hunter Solution from Experian India. This is an industry level initiative coordinated by Life Insurance Council.
It is not automated, but manual as well. Tapan Singhel, managing director and chief executive officer, Bajaj Allianz General Insurance, said that they use a combination of automated and manual measures to curb frauds.
The company has developed an analytics model for health and motor claims, which brings to the fore certain claims that cross a set threshold or indicators.
Singhel said these cases are then further investigated by the in-house investigation teams through on-ground enquiries.
"To further facilitate analytics, the company has digitalised its claim reports and is in the process of building advanced analytical capabilities," he said.
Modelling techniques are also being used.
Niraj Shah, Director Marketing, Strategy & Products, PNB MetLife Insurance said that they use analytics extensively to improve the quality of our business and increase efficiencies by mapping productivity.
"We do also cluster analysis to identify behavior of high performing distribution and share best practices across the system leading to higher productivity," said Shah.
He said that analytics also helps us identify potential frauds at underwriting and claims stage.
Others are not far behind. Bajaj Allianz General Insurance which has been working with a database of around 7 million active customers, identifies the requirements of the customers through segmentation and propensity modelling, which enables it to offer need-based solutions to them.
Credit information company Experian India has launched Hunter Fraud Management Services earlier this year for the life insurance sector in India. The offering was to help life insurance companies to be a part of the Hunter Closed User Group (CUG) for detection of life insurance fraud.
Life insurance companies that join the CUG will share with Experian any data relating to new policy proposals and claims. The credit information company is looking to offer similar services to general insurers as well. In India, Experian is the only provider of application fraud detection services using National Hunter.
Apart from fraud, cross-selling is also an area of focus for the insurers. IDBI Federal Life for instance, is currently in the process of implementation of a data analytics software for its customer retention mainly focused on persistency and renewal collections . The company expects to further extend this analytics software to develop models to help us to up sell and cross sell to their existing customers in the near future.