The solution to this problem is analytics tools that can rapidly gather and analyze data on comparable historical cases to predict the optimal offer. This predictive analytics use case can help agents understand what percentage of debt is normally recovered in similar cases so they can use the information as a benchmark to determine the minimum to accept and highest likely repayment amount. So, for example, instead of potentially accepting an offer of, say, 60% of the balance with very little data, they would have the insights needed to know that the benchmark is actually around the 70% mark and at minimum they should accept 65%. With data to guide agents, your collections team will see incremental increases in settlement amounts, supporting lower write offs and loan loss reserves.
5. Optimize Contact Strategies
To create brand-defining customer experiences, collections teams need to move beyond the automated dialer to power collections strategies. A customer-first approach to collections means engaging with customers at the right time in the right way. Collections experiences need to be cohesive, so customer interactions are streamlined, effective, and as unobtrusive as possible. While many dialers focus on general ‘high success’ times in the day to contact customers, risk and collections teams can implement predictive analytics models that analyze data, such as contact history or account activity, to predict the optimal contact time and method. To implement analytics models to determine the how and when, an organization needs to create a cohesive collections system that brings all relevant information into one place. By providing a source of truth for collections and risk teams, a business can ensure that customer interactions are all documented and accessible and all information can be easily used to inform models. In a time when customers are choosing which debts to prioritize, creating brand experiences that build engagement and customer loyalty is vital for both increasing willingness to pay and improving customer retention. Optimization of contact strategies with do-not-call, email, and contact logic also empowers collections teams to focus high cost contact methods on high value-at-risk accounts, allowing teams to maximize efforts on the areas offering highest returns. Conversely low-cost methods can be triggered for accounts that are most likely to respond to a gentle nudge. Email, text, and voicemail can all be used to encourage self-cure with the ultimate goal of getting customers to enroll in autopay to reduce recidivism rates. 4
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