Star Health, Manipal among worst insurers in claims settlement; SBI General leads the pack

Many customers look at the claims settlement ratio or rely on anecdotal claims stories from acquaintances. However, the claims settlement ratio alone does not give a complete picture. Other data points, especially the claims paid ratio in terms of amount, hold the key.

“Claims settlement ratios in isolation can present a skewed narrative. For example, if an insurer processes 80 small claims of ₹100 but leaves 20 larger claims of ₹1 lakh unresolved, they might still boast an 80% claims settlement ratio,” said Sumit Bohra, president at Insurance Brokers Association of India (IBAI). “This metric fails to account for the proportion of claims paid in terms of total amount, which could be significantly lower.”

Number vs amount of claims

What does a claims settlement ratio tell you about an insurer? It shows how many claims a year an insurer has settled or paid. If an insurer has a claims settlement ratio of 95%, it means it settled 95% of claims it received in a financial year. However, the devil is in the detail. What if an insurer only partially paid the claim? It would still be counted as a settled claim. That said, the amount of claims being settled by an insurer is more important. Higher the claims paid ratio, better is an insurance company in terms of the measured ratio.

However, this data point is not readily available. While insurers showcase their claims settlement ratios prominently, they hardly mention claims payout ratios based on the amount of claims. Though insurers declare total claims amount paid in a year in public disclosures, one needs to calculate the ratio manually for each insurer to make a comparison. Doing this for 34 insurers is not feasible for a customer.

IBAI recently released a handbook for policyholders, General Insurance Claim Insights, compiling metrics like claims paid ratio (amount), claims repudiation ratio, claims pendency ratio, and grievance resolution ratio among others.

The handbook includes all data points at an overall level along with individual lines of business, such as fire, health, marine cargo, marine hull, motor own damage, motor third party, and miscellaneous.

Looking into the health data, SBI General Insurance led with claims paid ratio (on amount) of 88.3%. Its claims paid ratio (on number of claims) remained nearly the same at 88.86%.

Next on the list is Bajaj Allianz, which quotes a ratio of 86.23% in terms of amount and 90.29% in terms of number of claims. This is followed by Royal Sundaram (83.18%), IFFCO Tokio (80.44%), Digit Insurance (79.5%), and Liberty General (79.14%) in terms of claims amount.

Star Health had the lowest ratio, at 54.61%. This means the company settled only about half of the claims it received in a financial year. The other four poor performers were Manipal Cigna (56.14%), Universal Sompo (55.25%), Navi General (61.69%), and Edelweiss (62.34%).

Among noteworthy insurers, ICICI Lombard maintained a ratio of 82.59% in terms of number of claims. This is just 63.98% in terms of amount. HDFC Ergo has it at 86.90% and 71.35%, respectively.

Public insurers performed better on this front, with four of them, New India, Oriental Insurance, National Insurance, and United India, quoting a claims paid ratio (on amount) of 98.74%, 97.35%, 87.95%, and 73.03%, respectively. The claims paid ratio on the number of claims stood at 95.04%, 87.97%, 84.61%, and 84.28%, respectively.

The data is available for the financial year 2022-23. Total claims available for processing in FY23 included total claims outstanding at the beginning of the quarter ended 30 June, 2022 plus total claims reported during the year ended 31 March, 2023. The total amount of claims settled in FY23 was divided with it to reach the claims paid ratio for FY23.

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More data for better transparency

Insurers publish a lot of data, as specified by Insurance Regulatory and Development Authority (Irdai), but only seasoned experts can glean insights out of it. They believe more data points are needed for better transparency and comparative analysis.

“The data is not granular to say the least. The regulator should make way for better reporting requirements. For example, insurers do not classify why a certain amount or number of claims have been repudiated. It could be a fraudulent claim or not in line with agreed policy conditions. We have no way to find out about it,” Bohra said.

“Specified reasons for claims rejection or repudiation can help policyholders know more about insurers. For example, if an insurer detects a high number of frauds, it can give confidence to policyholders that the insurer is efficient in fraud detection. Similarly., policy-condition-specific rejections may showcase bad underwriting practices,” he added.

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Kapil Mehta, co-founder and CEO of SecureNow, said he noticed some discrepancies in the data for a couple of insurers when he ran calculations. For example, the closing claims of one quarter were not the same as the opening claims of the next quarter.

He further said insurers need to declare data separately for group and retail businesses. “Regulator could consider mandating the data disclosure at a portfolio level of group and retail businesses because claims handling process in both is quite different from each other. In retail, data disclosure is needed product wise so that policyholders can make a better product selection. Broad data at a company level is useful but can be refined,” said Mehta.

Some definitions can be made sharper. “In grievances, every insurer has its own way of counting it. For example, grievances can be mailed, registered on phone or via social media. Some insurers capture all grievances, while others only email grievances. A standard way of doing it is needed. Similarly, if a customer makes an enquiry, insurers need to classify if it was a query, service request or a grievance, in a standardised way,” he said.

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Mint take: Insurance data is publicly available, and Irdai also publishes it annually. However, most of it is available at an industry level and in absolute numbers. Key data points, including claims paid ratio in terms of amount, product-specific claims ratios, claims efficiency ratio, claims pendency ratio and claims outstanding ratio, should be readily available on insurance companies’ websites and in the insurance regulator’s annual report for policyholders to make a comparative and informed decision.