Do you need to collect more, spend less and significantly increase unit yields? Do you need to know whether a letter, a call, or no action is your best decision to produce an optimal result? If yes, then you need LIFTSM from First Data—a hosted analytics solution that combines the power of data, predictive analytics and action to dramatically improve collections performance.
LIFT solutions deliver significant returns. This powerful, predictive analytics engine not only provides a score, but recommends the best action to take based upon your business strategy. LIFT works for all levels of delinquencies—not just first cycle.
We Offer the Following LIFT Solutions:
Self Cure Manager—enables you to avoid allocating resources to those accounts that will pay regardless of treatment.
Call Manager—enables you to improve performance by optimizing resource allocation through more intelligent calling queues. By focusing calling effort where the return is the greatest and re-allocating calling effort where the return is the least, you can improve performance and maximize month-end results. Additionally, Call Manager can be integrated into all contact methods, including manual, dialer, and automated messaging through 2Way-ConnectSM.
Letter Manager—enables you to identify those accounts where the cost of sending a letter is higher than the potential return, thus saving money by not sending a letter to those accounts. Letter Manager lets you start generating results immediately as it provides custom strategy capabilities that make it easy to rank accounts and allocate resources.
Settlement Manager—enables you to determine the optimal settlement rate for every delinquent account. Actions include recommending no settlement, to recommending settlements for certain percentages. With Settlement Manager, you can significantly reduce net credit losses through pre-charge off settlements by adjusting offers by segment to maximize response rates.
Outsource Manager—enables you to determine which and how many accounts to send to collection agencies in order to reduce contingency fees while balancing internal resource constraints.