Increasing Insurance Claim Accuracy with BI
Improving the accuracy of insurance claim processing is essential to providing policyholders with timely and correct compensation. By implementing advanced business intelligence tools, insurance companies can better analyze claim costs and trends, which results in better operational oversight for providers, which in turn can lower expenses and pass savings on to clients. When customers feel they can trust their insurance provider, they are likely to keep it. In this blog, we will explore how business intelligence can be used by insurance providers to dissect claims and improve the service they deliver.
Some challenges experienced by insurance companies when they process claims include:
Challenges in insurance claims processing
- Regulatory compliance: Insurance companies must navigate complex regulations, including data protection, privacy, and transparency laws, requiring significant legal resources for compliance.
- Fraudulent claims: Fraudulent claims are costly and time-consuming to resolve, necessitating robust systems for detection and prevention.
- Customer experience: Customers rarely enjoy the process of filing a claim with their insurance. They are unhappy from the start because claims are precipitated by an unfortunate event. Filing a claim can be troublesome with lengthy paperwork and long resolution times.
- Data quality: Claims assessment and settlement can be disrupted by incomplete or erroneous data, policy variations, and inconsistent formats from different sources.
- Lack of resources: During periods of high demand, such as after a catastrophic weather event, insurance companies might not have enough money and resources to process and resolve claims effectively. Policyholders may experience delays and frustration because of this.
- Data management: Processing insurance claims includes handling enormous amounts of different, frequently unorganized data, which, if not adequately organized and processed, can result in delays, inaccuracies, and higher operational expenses when evaluating and settling claims.
Let’s see how business intelligence transforms insurance claim processing.
How business intelligence tools transform claims processing
Business intelligence (BI) transforms claims processing in the following ways:
- Data analysis: BI aids in identifying and addressing bottlenecks and inefficiencies in the claims process by analyzing claims data and metadata of the claims process.
- Real-time reporting: BI provides real-time reporting for managers to monitor claims processing, identify delays, and take immediate action.
- Predictive analytics: BI uses predictive analytics to forecast trends and potentially prevent delays in the claims process, enabling organizations to preemptively tackle issues.
- Identify trends and patterns: BI can assist insurers in determining which types of claims are more likely to be fraudulent or which claims are taking the longest to process. This data can then be utilized to create targeted strategies for increasing claim processing efficiency and reducing fraud.
Let’s learn about claims processing metrics.
Monitoring claim processing metrics
Tracking key performance indicators (KPIs) in claim processing is vital for enhancing efficiency, accuracy, and effectiveness, enabling organizations to make informed decisions and improve the claims handling process.
Here are some important metrics to consider:
Claim amount comparison
This metric provides important information on the frequency and seriousness of claims. As a result, management can effectively analyze risk and make data-driven decisions about pricing and underwriting guidelines. Additionally, it aids in the detection of potential fraud or irregularities in claim filings, allowing the company to reduce losses and maintain a profit.
Claims paid out vs. denied
An insurance company benefits from closely monitoring the claims paid out versus denied metric as it provides insight into their financial health and risk management practices. By evaluating this metric, the company can gauge the effectiveness of its underwriting process and the accuracy of claim assessments. A balanced claims paid out versus denied ratio shows a healthy claims management system, leading to sustained business growth.
Average claim amount per policy type
The average claim amount per policy type metric helps identify trends in claim amounts for various policy types, enabling insurance companies to distribute resources efficiently and set appropriate premiums.
Time for average claim settlement
This indicator is essential for an insurance provider since it has a direct impact on client retention and satisfaction. Providers should strive for the shortest time possible to increase policyholder trust. A lower measurement also indicates efficiency in processing claims.
Average cost per claim
This metric offers a clear picture of the financial effects of each processed claim. By keeping an eye on this statistic, insurance providers and managers are better able see when claims are becoming too expensive, evaluate the success of their underwriting procedures, and make decisions on premium pricing and policy details. Additionally, it aids in setting sensible reserves, controlling risk, and ultimately ensuring that the business remains profitable in the long run.
Loss ratio
The loss ratio metric is used to contrast the overall amount of claims paid with the total amount of premiums collected over a given time period, thereby evaluating the profitability and risk exposure of the insurance company.
Claim settlement ratio
The claim settlement ratio is an important indicator for insurance firms since it compares how many claims they settle against the total number of claims they receive. A greater claim settlement ratio demonstrates the company’s prowess in upholding its contractual duties to policyholders, fostering client confidence and trust.
Let’s consider the benefits of applying BI to insurance claims.
Real-time benefits of BI in insurance claims
Reduced fraud
BI can be used to help insurance companies identify and reduce fraud. For example, BI can be used to identify patterns of suspicious claims or to flag claims that are likely to be fraudulent.
Enhanced customer experience
With BI analyzing claims, agents have access to a high-level overview of claims and their statuses. This helps illuminate process bottlenecks and lead agents to implement fixes. This, in turn, improves the customer experience, making customers more likely to stay loyal to the company that handles their claims efficiently and without hassle.
Increased transparency
BI tools enhance transparency in insurance claims processing by enabling real-time tracking and analysis of every stage of the claim lifecycle. The BI system improves accuracy, reduces fraud, and builds trust by providing comprehensive visibility throughout the claims lifecycle, enabling informed decision-making and regulatory compliance.
Reduced paperwork
BI centralizes information, reducing paperwork, minimizing errors, enhancing data accessibility, and enabling real-time analytics, leading to increased operational efficiency and customer satisfaction.
Generating reports and analytics
Insurance companies can utilize BI to develop reports and analytics that can aid in spotting trends in claim data and improve claim processing choices.
Bold BI empowers insurance companies to embed robust data analytics and visualization capabilities in their day-to-day systems to make their data work for them. The following sample policy claims analysis dashboard helps monitor, track, and analyze insurance claims data to provide insight into claim patterns, assist in fraud detection, better manage claim costs, and enhance the decision-making process.
You can explore more of our sample insurance dashboard to learn more!
Originally published at https://www.boldbi.com on October 19, 2023.
