Calculating a customer or transaction level limit is not rocket science, but gathering the required insights for the calculation is always hard. The applicant’s disposable income level, the probability of not paying back their debt, and your company’s expected return from each sub-segment are just the first few elements to mention.

Depending on which part of the lending landscape you do business in, the principles of limit management may vary. Things to consider before assigning a limit would be different for a new digital bank with a low number of existing customers from a consumer finance company that cooperates with an e-commerce marketplace.

A limit management project at Mindberg.ai starts with assessing the portfolio KPIs, available data, analytic tools, and technology. Then, we create a phased approach in which we can help you start lending with a solid limit model as quickly as possible. Finally, based on this model, we develop a broader plan for the best practice limit management as a mid-term goal.

Every lending business has room for improvement regarding limit management, be it the predictive models used, the fine-tuning of optimization algorithms, or the necessary changes in your risk appetite. Mindberg.ai builds an environment where you can manage the end-to-end limit management process and stay informed and up-to-date on the status of each element.

Mindberg.ai raises your analytical maturity level to a point where you can run different limit management scenarios on smaller customer groups, challenge your existing strategy on live data, and do simulations on your historical data to re-assess your alternative moves.