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Optimizing Claims: 5 Predictive Models to Augment Claims Processing

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Challenges facing claims departments Digital technologies, cloud computing and AI are having a positive impact on the claims process. However, despite these advancements, risk managers and claims leaders face a number of obstacles. Table A highlights some of the challenges facing risk management and insurers' claims departments. To overcome these challenges many claims departments are adding predictive analytics and AI to optimize claims process. Rising inflation, continuing supply chain issues are having a significant impact on the increasing claims severity A shortage of expert adjusters and cost rationalization issues have resulted longer claims duration and higher costs Litigated claims are becoming more frequent and typically the settlement amount is at least four time greater when an attorney is involved Inability to recover loss costs from a third party can have a negative impact on an organizations risk management and claims profitability Case reserves that are too low or too high can impact on financial performance of organization It's difficult to determine how to effectively prioritize claims so that the ones requiring immediate attention can get it Longer claims cycles and duration results in higher claims settlement and loss expenses Over 80% of claims data is unstructured, medical records, emails, photos and video – making it difficult to identify hidden patterns in the data Growing claims costs Limited resources Rising litigation costs Missed subrogation opportunities Inaccurate case reserving I N D U S T R Y I M P L I C A T I O N S C L A I M S C H A L L E N G E S T a b l e A Inefficient claims prioritization Increasing claims duration Analysis of textual notes and unstructured data OPTIMIZING CLAIMS | 2

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