It is analyzed Bad debt results from sub-optimal decision making at four stages in the policy life cycle – sub-optimal underwriting decision making, absence of interim audits on accounts most likely to default, inability to prioritize premium audits, and inefficient collections process.
We have worked with a few large US Workers Compensation providers to help them reduce bad debt losses. Our solution leveraged our deep analytics capabilities, process improvement capabilities and deep industry knowledge. It has four components. First, based on multiple policy characteristics and external data, we identify segments of risky policies (CART segmentation) which should be rejected either at inception or at renewal. Second, we identify policies which should be audited early (within policy tenure) and cancelled if the identified additional premium is not paid by the customer within the due date. Third, we prioritize premium audit scheduling. Fourth, by analyzing past performance of collections vendors, we also modify the allocation criteria of defaulted policies to different vendors. Assigning more policies to top performing vendors within each policy segment enhances overall collections and reduces bad debt losses. Our solution can help workers’ comp insurance firms reduce bad debt losses by 15-20%.
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