Building Productive Agency Workforce
Agency channel contributes to more than 50 percent of new business premium in Insurance segment. Considerable sales effort is spent in interviewing and recruiting agents. Much of this time is unproductive because many of the agents who join are non-performers or leave the company soon. Data analytics can significantly improve the efficiency of this recruitment process.
Agent Rating Framework
Insurers can adopt an analytical scoring model to rate agent applicants before they are interviewed by the branch or sales managers. This will ensure that interviewing time is spent only on candidates likely to be successful. The output of such a model will be a performance score for each potential agent similar to what we have in Credit Score based on personal, demographic details and application details. Below is the framework overview
Insurers can decide definition of high or low performing agent based on business criteria like number of minimum policies sold per month, time take for agent to be active (selling atleast 1 policy)
Benefits of this approach
- Standard and objective process of agent screening that will identify high potential agents. Individual subjectivity is considerably reduced.
- Time and cost savings resulting from personally interviewing only those potential agents who have score above threshold score.
- Such a solution will help Insurers build highly productive and efficient agency workforce in long term.