Klear.ai Predictive Analytics for Workers' Compensation
Foresight that translates into tangible cost reductions, quantifiable efficiency gains, and better outcomes
Adopt a culture of 'Proactive Claims Management' using Klear.ai suite of products
Improve tactical, operational, and strategic decision with Klear.ai predictive power
Tangible benefits - 10 to 15% in efficiency gains; 15- 20% by preventing fraud, abuse & waste; Increased customer satisfaction
Quick deployment and easy integration with your existing claims management systems through a library of APIs.
More than just claims software,
it’s peace of mind.
An accurate foresight of key components can improve the claims management significantly - helping you optimize tactical, operational and strategic decisions throughout the claims lifecycle.
Klear.ai demonstrates tangible benefits in terms of improved efficiency, early warnings, minimizing costs, recouping losses, resource management and most importantly client satisfaction.
Predict the ultimate cost of claims using advanced proprietary machine learning models. Model ingests the most granular level historic data, identifies the key cost drivers and applies the knowledge to make highly accurate predictions of the cost of claim.
Klear.ai algorithms keep a keen eye on new information flowing into the claim file and adjusts itself dynamically throughout the claims journey.
With Klear.ai, 'surprises' are a thing of past. Accurate foresight lets you pull the right levers to keep costs under control...
Advanced statistical methods offer demonstrable advantages in loss reserving compared to subjective assessment by examiners.
Klear.ai predictive models start working on prediction early in the life of long tailed claims, with minimal sets of data, readjusts the reserves, as new information gets populated in the claim file.
Our models are aligned to your way of doing things - it provides the prediction categorized into Medical Costs, Indemnity Costs - further broken down into Temporary and Permanent Disability Costs), Life Pension (if applicable), Legal Expenses and Other Expenses.
Now equip your examiners with the power of data to set the claim reserves - accurately, objectively and consistently...
Searching for a 'needle in a haystack' is challenging.....not any more !
Fraudulent claims may be 1% to 2% of your overall claims volume, but could contribute to over 10% of total claims costs.
Klear.ai fraud predictive models are built with a proprietary design with AI at the core. Over 45 red flags have been identified, and their patterns have been deeply analyzed on a large database. The predictive value of each of those flags is scored individually and the final risk score is calculated keeping the overall context of a claim in mind. The system not only gives an alert of the claim being 'Suspicious' , but also provides the statistical confidence level of every prediction.
In addition to Claimant Demographics, Injury Details, Employment Details, and Claim Journey Details, Claimant's Behavioral Variables, Klear.ai models extensively use NLP (Natural Language Processing), also commonly called 'Text Mining' on Adjusters' Notes to discern patterns.
Arm your examiners with Klear.ai to weed out fraudulent claims, reducing your overall claims cost by upto 10%
Predicting the likelihood of a claim going into litigation is a valuable tool for your program.
Klear.ai models predict the probability of a claim going into litigation. An early indication of litigation can help the claim managers take a proactive approach to manage the claimant's concerns, in most cases, take appropriate measures to avoid an expensive litigious path.
Our technology helps identify “at-risk” claims using sophisticated machine learning algorithms and AI modeling.
Put your team in the 'driver's seat', and help navigate the claims journey without the litigious road bumps.
An effective insurance subrogation process could help you save upto 20% of paid claims.
Klear.ai AI based predictive models ingest structured and unstructured data to accurately predict the subrogation potential of a claim. Predicting subrogation potential early in a claim lifecycle helps with the faster recovery and increased efficiency of claims processing - without being constrained by statute of limitations.
Enable your claim adjusters to prioritize and focus on claims that have a greater probability of recouping the losses through accurate and early subrogation predictions.
Klear.ai Predictive Suite uses highly sophisticated AI and Deep Learning Models to make accurate predictions of critical claims parameters. Models ingest structured as well as unstructured data (like Adjuster's Notes), and runs them through proprietary statistical models to give the final inputs.
In line with the dynamic nature of insurance business, the solutions are trained to monitor the hit ratio, and use this data to self improvise over a period of time - further entrenching into the core of your claims operation.