A complete application, behavioral, and collection scoring solution that will increase the profitability of your portfolio while maintaining its size, decrease the credit default rates, and speed up the scoring process for your clients.
Credit scoring is no longer a simple decision to give a credit to a client or not based on the scorecard. Instead, it is a complex process with multiple stages and a high level of uncertainty, which must work effectively and efficiently yet satisfy strict regulatory policies.
We developed a solution that takes into account all these aspects and guarantees the successful operation of the bank in the modern realities. The solution supports application, behavioral, and collection scoring, can optimize the portfolio in the short-term and long-term following the explore-exploit framework and leveraging the techniques from active learning, works with structured and unstructured data, and most importantly builds interpretable models for regulatory compliance and audits.
With our solution, your bank will increase the profitability of the portfolio while maintaining the portfolio size by working with more creditworthy clients, decrease the credit repayment delays and default rates, and speed up the scoring process.
The solution predicts accurate credit scores for each client. Using this information you can manage the risk by balancing the number of credits and the portfolio size depending on your operational and strategic goals.
For each potential client, the solution predicts the optimal credit size, duration, and interest rate. The algorithm is capable of generating a prediction in real-time.
The framework is highly extensible and can work with any kind of information. Both structured and unstructured data can be effectively mixed in to increase the prediction accuracy, e.g. we can incorporate the information from social media.
The solution uses a proprietary machine learning library for credit scoring based on inductive logic and can output a series of interpretable rules for each credit decision. The algorithmic rules can be extended by the experts making the model even more powerful and sensitive to the unique aspects of your organization. The solution can also work as a black-box and blend thousands of signals using the state-of-the-art deep learning and ensemble learning techniques. In this case, the model is not interpretable but achieves slightly higher credit scoring accuracy.
Monitor creditworthiness of every client during the lending period by analyzing the transaction logs and leveraging the updated information about all credits in your portfolio. Transaction logs allow building interpretable client portraits.
In the case of credit repayment delay, the solution suggests an optimal set of revised terms and actions maximizing the probability of the credit return while minimizing the cumulative cost of all collection efforts.
Originally developed for the mining and oil industries, where the cost of each new hole to drill is very expensive and, hence, only a few observations are available to tune a scoring model, our solution can work even with small credit portfolios.
While the existing models make short-term decisions and reject a significant number of creditworthy candidates, we take a controlled short-term risk with the aim to win in the long-term. Our solution can intelligently allocate a specified percentage of credits to more risky clients with the aim to collect better data. In other words, we make the system unstuck from the local maximum.
Decrease the credit default rate by working with creditworthy clients. Decrease the average credit delay time by implementing effective collection actions and taking preventive measures based on the behavioral scoring. Minimize the rejections to reliable clients and increase the portfolio size. Learn from your entire client base using the explore-exploit framework.
A personalized credit score is generated in real-time based on the information from the client and reputable credit organizations. It takes just 2-5 minutes to give a credit to a client yet the accurate scoring model keeps the risk low.
All decisions are automated and the solution can allocate credits to clients without any human supervision. The all-in-one solution helps your employees be more productive as they can do all of their tasks in one place.
Individual employees have their own biases, might get tired or ignore the business processes defined in the organization. Our solution standardizes credit allocation across the organization making the process more manageable.
Every employee has to learn only one system rather than suffer through the creditworthiness evaluation details and learning about several legacy solutions.
Your employees don't have to spend time on context switching and learning several credit scoring systems for different purposes any more. They can manage data ingestion, data pre-processing, define custom attributes, segment clients, tune and deploy model selection all in one place.
Typically, the roll-out process takes 6-12 months. With our integrated consolidated solution, you can start making better credit decisions in 2-3 months.