Claim Analytics

Handling insurance claims are tricky. Companies face a challenge to maintain a correct balance between cost of operations and CSAT during insurance claims. By using effective claims analytics models, insurers can predict claims and identify potential fraud in advance as well as optimize claim outs and deliver a much superior customer experience. Our solutions in Claim Analytics are as follows

Solution Offerings

    Fraud Detection


    Affine's Fraud Detection Models are well-suited to detect the rare events of fraudulent claims.

    Need

    Frauds cut profits for insurers, limits their ability to offer competitive premiums to their customers, and makes their losses and combined losses worse. Insurance companies focus on not honoring fraudulent claims to reduce any unnecessary loss to the company.

    Impact

    Fraud detection analytics provides higher likelihood of detecting and countering fraudulent claims. It helps in optimal utilization of investigation workforce to detect frauds that creates better customer experience for genuine claims leading to continued patronage and popularity for firm.

        Workforce optimization


        Claims investigation teams can be utilized efficiently with Affine's help by prredicting the expected work volume and prioritizing cases with likelihood of fraud

        Need

        Organizations face a huge pressure on workforce operating costs since excess staff would lead to cost overruns while lower than required staff would adversely impact customer service levels. An optimal workforce needs to be managed and guided to bring down process costs while ensuring minimal redundancy and optimal processing speed.

        Impact

        Workforce optimization helps in achieving higher work efficiency leading to increased profitability. It helps in fraudulent claim rejection at a lower cost. It provides customers with better experience because of quick processing for valid claims.