The sales force of Reliance General Insurance flouted underwriting rules, hitting profits and exposing it to bad risk. Here’s how its CTOO found a way to shrink losses and save Rs 1 crore.
But in 2009, despite its high volumes, RGI’s motor insurance business could not set its cash registers ringing. Sriram knew that the underwriting department needed to bring in controls and practices to help them track every motor proposal.With prudent underwriting practices, RGI can now focus more on regions and vehicle make-models which are lucrative and offer better pricing terms.
The balance sheet of the Indian insurance industry is a sight. It’s both exciting and alarming at the same time. Consider this: According to Standard and Poor’s, the Indian general insurance sector is worth Rs 40,000 crore in premium in 2011.
Another report published by FICCI and the Boston Consulting Group states that the insurance industry in India will reach $350-400 billion (about Rs 15.7 lakh crore-18 lakh crore) in premium income by 2020.
That’s the good news. And now for the bad: The underwriting loss of the Indian domestic general insurance companies—according to Crisil—is projected to touch Rs 10,000 crore in 2011. That’s up from Rs 5,900 crore in 2010, an increase of almost 70 percent.
And because motor and health insurance are most prone to underwriting losses, companies that heavily depend on these categories, suffer the most. With 60 percent of its volumes coming from motor insurance, Reliance General Insurance (RGI) falls in the high risk zone.
Stuck In a Rut
Part of the ADAG group, RGI commenced commercial operations in 2001. During the first five years, the private insurer conducted business as a captive company catering to the in-house insurance requirements of Reliance Industries. But in August 2005, it forayed into the retail business. Today, it sells nearly 3 million policies a year.But in 2009, despite its high volumes, RGI’s motor insurance business could not set its cash registers ringing. The company was trying hard to combat the price war waged by its peers after de-tariffication. As a result, the sales force began to pick up business by under-pricing. “Eager to source more business, they turned a blind eye to the quality of business and began to flout the underwriting guidelines set by us. We found that they were picking up the wrong business and exposing us to bad risk,” says Naganathan Sriram, chief technology and operations officer, Reliance General Insurance.
The slowdown made it worse. According to provisional numbers collated by General Insurance Council (GIC), the insurance sector saw growth rates plunge to 6.5 percent during April-June 2009. And RGI recorded a growth rate of a mere 0.2 percent in the first quarter of 2009.
“In the insurance business, profitability is linked to the ability to accurately assess risk. And our sales force was not able to manage risk efficiently. We witnessed an increased number of claims which exerted pressure on our bottom line,” says Sriram.
One way to fix that, Sriram says, was to beef up its technical underwriting teams, but that option was too expensive. “We sell over 3 million policies a year. It is not possible to have physical underwriters scan through all the proposals. We are a decentralized organization and hiring thousands of underwriters would have been a very cost prohibitive proposition,” says Sriram.
There was another way out.
The company’s sales force was picking up the wrong business, exerting pressure on the bottom line and exposing it to bad risk.
Ruling Out Risk
Sriram knew that the underwriting department needed to bring in controls and practices to help them track every motor proposal. Though there were guidelines for maximum discounts to be allowed—for vehicles beyond a certain age, expired policies, a vehicle’s make, model and region—the sales force disregarded them.
Sriram felt a rules engine could be the way forward. Based on a set of rules or guidelines, it would help the company automatically identify bad risk and ensure it did not flow into the system.
This required Sriram to build and roll out about 500 complex rules—a process that took four months. And he knew that apart from his team, he would need experts to help him out. A team of business analysts was involved to map the requirements for the project. They worked closely with the project team and helped them understand the rules. “Even our project managers were not merely technology-oriented people they weremore business focused so they knew the rules,” says Sriram.
With the help of his in-house team, Sriram managed to integrate a fairly complex IT architecture involving: A rules engine from Blaze, Workflow from Savvion, OLAP dashboard from Qlikview and transactional systems from Biztalk.
In the new system, the underwriting guidelines have been implemented as business rules. Motor proposals coming from all RGI branches are fed into the company’s policy administration system: Reliance policy issuance system. A Web service call is made to the blaze advisor rules engine. The system then returns a decision—on whether the rules were followed or not—and a case is registered for underwriters. In case of a deviation, the underwriter, with the help of the system, figures out which rule has been broken. Accordingly, he rejects or escalates cases to the higher authority.
The underwriting team can also view deviations in the Savvion workflow to analyze patterns in guideline deviations by branch, region, sales manager, intermediary and vehicle model. “Through an integration of multiple systems, each proposal is tracked to ensure that the guidelines are adhered to,” says Vikram Arora, chief manager-technology at RGI, who was also one of the project managers for the rules engine implementation.
Arora adds that if the rules are not followed, there are penalty clauses imposed by the system. For instance, in case of deviations, no sales credit will be awarded to sales managers or their intermediaries.
“The system provides real-time business activity monitoring as well as comparative research (through dashboards) to underwriters to fine-tune the process to meet their business objectives,” says Arora.
Today, that has made life much easier for RGI.
The project has translated into plum benefits for RGI. It has helped the private insurer reduce its exposure to bad risk. Around 20 percent of proposals in-warded are immediately flagged for discrepancies and acted upon. Due to this early filtering, there has been a significant reduction in claims frequency (around 20 percent) which has had a positive impact on profitability.
“Of the 20,000 proposals checked during the first month of deployment, 2,000 were rejected resulting in a commission payout of Rs 20 lakh. We have saved Rs 1 crore in the past one year,” says Arora.
The underwriters can now enforce pricing control on a pan-India basis which was not possible earlier. They are now aware of which make-models to insure more and thereby control claim ratios. “Commission payouts to intermediaries can be controlled so that we reward channels who bring us the right risk at the right price. We are able to control our bad book and pinpoint the branches which have a higher number of fraudulent incidents,” says Sudip Banerjee, head-IT and online sales, RGI.
The system provides real-time business activity monitoring as well as comparative research (through dashboards) to underwriters to fine-tune the process to meet their business objectives
Not only that, the system can also rein in profits for erring branches. “We can take corrective and disciplinary action by asking the intermediaries to give less discounts and increase the underwriting controls so that the erring branches also begin to pick up profitable business,” adds Banerjee.
The project will put RGI on a firm footing by improving its market share. With prudent underwriting practices, RGI can now focus more on regions and vehicle make-models which are lucrative and offer better pricing terms. The resultant data can be continually monitored online and rules can be fine-tuned. “Over time, this will result in a better motor portfolio which will lead to significant competitive edge,” says Sriram.
The project has augmented the customer service levels at RGI. With the rules based platform, policy provisioning will be faster as decision from underwriters is system-driven with stringent TAT monitoring. “Out of all the complaints received in our call center, policy delivery delay related complaints used to be around 5,000-6,000. That has now come down to 2,000,” says Banerjee.
It will also bolster employee efficiency at RGI. Earlier sales force used to seek underwriter’s approvals over e-mails resulting in delays in policy issuance and a lack of control over underwriting decisions. Now the entire process is workflow-driven with complete audit tracking. This improves the efficiency of RGI’s employees.
Today, with the rules engine, RGI’s balance sheet is in the pink of health and hopefully that will help better the Indian insurance industry’s numbers.