Warranty Managers are faced with a dilemma on deciding the level of automation in claim processing. Automated approvals can lead to more efficiencies, but may result in excess payments from overcharges and even fraudulent claims.
The benefits of Automated Claims adjudications are:
- Cost Savings from less staff required for manual review of claims
- Improving dealer satisfaction with faster claim payment
- Faster processing of related transactions such as Parts Return and Supplier Recovery
The expected downside effects of Automated Claim Processing are:
- Overpayment of Parts, Labor or Other charges
- Payment of fraudulent or excessive claims
- Missed opportunities to reduce Warranty Costs
Just because a claim is reviewed manually does not mean, the claims processor can catch all the errors the system is not able to. While processor’s experience and knowledge can help identify issues that software may not find, it is still hard to check against a large volume of products, historical claims, and other reference information. The companies can leverage the knowledge of the claims processors when making a decision with incomplete or uncertain information, whereas warranty software systems can help automate the most of the data checks using business rules, reference or historical data.
Best Practices in Claim auto processing
Warranty Departments can achieve close to 80% claim automation while minimizing downside effects but need first to implement systems and practices for
- Validating claims using business rules,
- Checking claims against reference data,
- Profiling repairs based on historical claims,
- Risk scoring claims to support claim decisions, and
- Automating all claims related processes to reduce manual data entry
Business Rules to validate claims data
Business rules within claims processing software can help identify most claim data errors. By capturing these errors during claim entry stage, you can have the dealers or claim submitters provide more accurate data reducing the number of claim with errors pending for review.
The Warranty software system you use needs to have an extensive set of business rules and also provide the flexibility to allow warranty business users to easily fine tune and update these rules without time-consuming development efforts.
Check Claims against Reference Data
Verify the claim data by checking against Warranty Entitlements, Product BOM, Parts Catalog, Standard Repair Times (SRT), Quality failure coding, Parts invoices, and cross reference data that relates component code to labor or parts. These checks can assure the quality of the claims data, but companies need to maintain the reference data to keep it accurate.
The business rules also depend on proper reference data to validate claims. Some companies may not have the data readily available, but these data relationships can be built over time to help cross-check the claim data.
Repair Profiling based on historical claims data
Standardize claim failure based on Causal Part, Component, Complaint, Cause and Corrective Action. Prepare a repair profile based on the Product Model, Component, and failure descriptions. You can identify a list of parts, labor time based on this repair profile. When you check the claim against this repair profile to determine if the claim falls within the parameters for the repair, you can ensure that claim is within previously approved criteria. Repair profiling also helps for the system to continuously learn about repair profiles without someone manually updating this criterion.
Claim Risk Scoring to support claims decisions
Define a methodology to score the claim based on risk assessment. The scoring can be based simple criteria such as claim amounts and frequency or by using advanced analytics such as data mining algorithms to detect anomalies. You can assign a Claim score 1-100 based on weighted criteria and decide your threshold to review a claim manually.
Automation of Claim related processes
Reduce Manual entry of claims data by automating the claims data exchange starting with the ability to upload claims from repair orders. Claims processors can streamline the claims processing by capturing the comments, pictures, and any other communications. Automate Parts Return process by identifying the parts to be returned using pre-defined return policies or requests. Automate generation of Supplier claims from dealer claims. Capture all claim related communication in one place.
Warranty experts at Mize also have prepared a simple checklist of 10 common practice areas for self-assessment to determine your expected level of claim process automation. You can score yourself 0-10 on each of these practices areas based on how strongly you have implemented this practice in your claims processing. The total score will an indicator of your confidence level on what percent of claims you will be able to auto-approve.
|No.||Claim Processing Best Practice||Score (1-10)|
|1.||Identify claim data errors before claim submission|
|2.||Automatically validate, and process claims based on well-defined business rules|
|3.||Track all Warranty policies and entitlements and Validate claims for eligibility and compliance|
|4.||Validate parts against Product service BOM, Parts catalog and Parts invoices|
|5.||Validate claims against based claims history to detect if claim is outside the normal range|
|6.||Validate labor charges against Standard Report Times (SRT) or average labor times|
|7.||Automate Parts Return criteria to identify when you need the parts back|
|8.||Allow the servicers to check warranty eligibility and recommended repair procedures and parts before performing the repair|
|9.||Standardized claim failure coding and trained the dealers on warranty procedures|
|10.||Minimize manual data entry by integrating with work order and service technician applications|
Few Questions on Claim process automation
Does Pareto principle apply to claims processing?
Yes, Pareto principle applies to claims processing where you can find most value by reviewing 20% of claims. The challenge is deciding which 20% of claims to review manually. Highest value claims may not be only claims resulting in excess payments. If you have a solid methodology to assign a claim risk score, that score can be used to identify 20% of claims with highest risk score to review manually.
What threshold should you set for Claim approval amount?
Threshold based on Percentage of the Cost Per Unit (CPU) calculated using the historical claims data provides better barometer than an arbitrary amount.
How to utilize historical claims data?
Determine averages from historical approved claims data to compare labor amount, Parts amount, parts used, repair frequency, and total claim averages.
How do you know if you are reviewing right claims?
You can track dealer requested amounts with manually adjusted or rejected amounts on claims.
If you are ending up with more chargebacks, you may want to review more claims upfront.
What are some easier ways to start in Claims Auto approvals?
Since claims for Service Campaigns or Bulletins are pre-defined and authorized to specific products, those claims can be auto-approved if they meet the pre-set criteria. You can also start by implementing a basic set of business rules and data validations to catch most of the data errors during claims entry and submission.
Should you use random sampling to identify claims to review manually?
A random sampling of claims to review may be beneficial for performing statistical analysis of claim quality. You may be able to extrapolate the claim errors and data quality based on the results from statistical sampling.
Continuous improvement in Claims process automation
Claims process automation also requires continuous improvement. You need to perform the following review steps periodically to ensure your claim automation system is delivering the right results;
- Determine what percentage of adjustments you could make when you manually review the claims. You can identify and add more business rules based on your findings
- Identify top dealers with highest number manual claim reviews, claim adjustments, rejections and chargebacks. Share benchmarking results on dealer performance and provide additional training to these dealers when needed.
- Periodically review the accuracy and variance of warranty and reference data and take steps to improve the integrity and quality of the data being used in warranty processes.
- Review upstream and downstream activities such as product registrations, repair work orders, parts returns, supplier recovery, and service campaigns to automate all claims related processes
Finally, you can also benchmark against your peers in the industry for warranty best practices to identify processes that you can implement.
Next generation Warranty Software from Mize (mWarranty) enables you to automate claims processing and improve efficiencies with business rules, structure data checks and claim scoring to detect suspect claims. Request a demo now to learn how you streamline your claims process.