Today's credit landscape is in the midst of a revolution. Today’s borrowers — no matter what type of credit they’re seeking — want a straightforward, fast, and personalized lending experience. Lenders desire the same state-of-the-art customer experience that reduces drop-offs during the credit application process, improves customer satisfaction, and boosts revenue. However, legacy systems and infrastructure often hinder a lender’s ability to provide a seamless digital borrowing experience. With the advent of artificial intelligence (AI) and real-time data analytics, credit decisioning is becoming increasingly automated. By choosing the right credit decisioning platform, lenders can improve customer satisfaction and boost revenue.
This blog post will cover the following topics:
1. What is a credit decisioning platform and why do you need it
2. The needs of modern credit decisioning
3. The benefits of using a credit decisioning platform
4. How to choose the right credit decisioning platform for your business
5. The right credit decisioning platform is the foundation of modern credit decisioning
What is a credit decisioning platform and why do you need it
A credit decisioning platform allows lenders to define lending parameters precisely and thus sharpen their ability to approve creditworthy customers while rejecting proposals from customers who either are not creditworthy, fraudulent or cannot afford further debt. A credit decisioning platform also enables lenders to change and tweak lending parameters as the risk profile and goals of the business evolve. The platform automates the collection of data that underpins credit decisions, offers out-of-the-box capabilities to define credit models, tools to speed up manual reviews, and enables use of advanced analytics and Machine Learning (ML) to discover new parameters for credit models.
The needs of modern credit decisioning
Modern credit decisioning requires several capabilities that are absent in conventional credit decisioning tools:
Combining traditional credit data with alternative data sources—such as telecom, utilities, and specialty finance—can help drive more informed credit risk decisions.
Moving beyond traditional modeling techniques, such as logistic regression, to calculate credit worthiness.
Applying advanced analytics and ML to reveal patterns of financial behavior that can help predict a consumer’s financial trajectory
The predictive nature of trended credit data can help strengthen analytics and credit model development.
Addressing the above needs of modern credit decisioning is not merely an incremental change for conventional credit decisioning systems; it requires building an entirely new foundation. This foundation has fundamental characteristics that lend themselves to addressing the core requirements of a modern credit decisioning system. And that new foundation is built on AI and data analytics.
Addressing the above needs of modern credit decisioning is not merely an incremental change for conventional credit decisioning systems; it requires building an entirely new foundation. This foundation has fundamental characteristics that lend themselves to addressing the core requirements of a modern credit decisioning system. And that new foundation is built on AI and data analytics.
The benefits of using a credit decisioning platform
There are numerous benefits to using a credit decisioning platform for modern-day lending.
1. Seamless borrowing experience: By automating much of the lending process, a credit decisioning platform enables lenders to offer a seamless experience for borrowers.
2. Increasing the accuracy of credit decisions: With the use of the right platform, credit decisioning can become more accurate. By aggregating data from multiple sources, analyzing it, and using ML models, a credit decisioning platform can identify patterns that humans would not be able to detect. This allows for a more comprehensive assessment of credit risk and leads to better credit decisions.
3. Personalized credit decisions: In addition to being more accurate, credit decisions made with a credit decisioning platform can also be more personalized. By taking into account factors such as income, employment history, and spending habits, a credit decisioning platform using the right data, can provide a more tailored credit decisions that is specific to the borrower. This leads to a better borrowing experience for the borrower and increased satisfaction with the credit product.
4. Faster credit decisions: A credit decisioning platform can also help speed up the credit decisioning process. By automating the gathering and analysis of data, a credit decisioning platform can provide a credit decision in a matter of seconds or minutes, rather than days or weeks. This not only leads to a better borrowing experience for the borrower, but also allows the lender to capture the business value that would otherwise be lost.
5. Reduced cost of originations: AI-powered credit scoring using the right credit decisioning platform can reduce the cost of origination of loans by up to 40% and reduce the cost of decisioning on low-complexity cases. Also, lenders can scale their operations to new geographies and higher volumes with a marginal increase in human workforce capacity.
How to choose the right credit decisioning platform for your business
When lenders are looking for a credit decisioning platform, certain features and capabilities are essential. Here are 10 things to look for in a credit decisioning platform:
1. Speed: The ability to make real-time decisions. By aggregating the right data sources and enabling the use of a variety of credit models, lenders can now make credit decisions in real-time. This means that borrowers can get an instant decision on their loan application, without having to wait for days or weeks.
2. Customizability: The ability to customize the credit decisioning process. Each lender has its unique lending process and criteria. A good credit decisioning platform should be able to accommodate these differences and allow lenders to customize the software to fit their specific needs.
3. A user-friendly interface. The platform should be easy to use and navigate so that lenders can get up and running quickly, as well as, reduce dependence on engineering resources.
4. Comprehensive reporting and analytics tools. The platform should provide lenders with detailed reports on their credit decisioning process so that they can identify areas for improvements.
5. Advanced analytics and ML capabilities: The platform should allow aggregating data from multiple sources, analyzing it, and using ML models, that can identify patterns that humans would not be able to detect.
6. Flexible integration options. The platform should be able to integrate with a lender’s existing systems and infrastructure so that they can continue to use their existing tools and processes. An API-first credit decisioning platform is best positioned to allow that flexibility of integration.
7. A wide range of credit decisioning models. The platform should offer a variety of credit decisioning models so that lenders can choose the one that best fits their needs.
8. The ability to handle a large volume of transactions. The platform should be able to handle a high volume of transactions so that lenders can scale their business as needed.
9. Reliability, uptime, and 24/7 customer support. A 24x7 borrower experience requires a credit decisioning platform that offers high reliability, uptime and 24x7 customer support.
10. Consumption-based pricing. The platform should allow lenders to start small and scale pricing as the lender experiences value from the credit decisioning platform.
The right credit decisioning platform is the foundation of modern credit decisioning
A credit decisioning platform helps lenders make credit decisions in real time. This type of platform is essential for modern lenders who want to provide a fast and personalized lending experience to their borrowers. Credit decisioning platforms offer many benefits, including the ability to make decisions in real time, customizing the credit decisioning process, and using advanced analytics and ML capabilities to increase the accuracy of lending decisions. When choosing a credit decisioning platform, lenders should keep in mind the 10 things listed above to ensure they find the best solution for their needs. By finding a credit decisioning platform that offers all of these features, lenders can dramatically improve customer satisfaction and boost revenue.
