After a brief lull that saw credit union branches and auto lending channels shrink due to the impact of the pandemic, credit unions have bounced back and are adapting to rapidly changing lending ecosystems. Along with banks, credit unions have consistently been touted as one of the pillars on which global lending ecosystems thrive. In the global digital lending market, credit unions have an estimated market share by revenue of 90.8 billion USD and it is expected to grow by 6.2% in the current fiscal year. Therefore, CROs must ask themselves: Are we equipped with the right tools and technologies to take advantage of this market opportunity?
The cons and cons of manual underwriting
Today, customers expect a quick, streamlined process in every transaction that they undertake, be it something as simple as buying shampoo, or something as complex as applying for a loan. Modern transactional processes have underlying expectations of convenience, simplicity, and most of all, immediacy attached to them.
Manual underwriting processes can be time consuming and inefficient and leave less time for the underwriters to focus on the complex loan applications. An infusion of technology to this process can not only speed up decision making but also allow them to make advanced decisions.
The move towards automated credit underwriting
Automated and AI enabled underwriting is not to be considered as a complete replacement of human underwriting; what it essentially does is complement and optimize human underwriting by introducing the element of well-analyzed data that has been consolidated into explainable insights. AI-based credit decisions free the underwriters mind to make more complex decisions and foster stronger relationships with members.
Some of the advantages of using AI-powered credit underwriting are: quicker and advanced decisioning, enhanced customer experience, consistent underwriting process and lower risk amongst many more. In terms of the impact that AI-based platforms can potentially create, leading credit unions have reported up to a 27% increase in approvals, while reporting a 20% decrease in risk.
Questions you need to ask before partnering with an AI-powered underwriting platform
Evaluation of AI-based tools will often be an uphill task for the CRO. Before signing on the dotted line, it is crucial to ask these questions to your AI underwriting vendors.
- Does your value system align with your vendor partner?
A successful collaboration happens when both partners are on the same page. Credit unions are 100% member-focused; thus, the strategic partner’s value system must be aligned to provide their members with heightened services. It is imperative to have an in-depth understanding of the vendor partner’s objectives and their stand on important things to the credit union. Financial inclusivity, customized product offerings, quicker decisioning and reducing losses could all be the focus of your credit union.
- Is the platform ideal for your credit underwriting needs?
An ideal AI-powered credit underwriting platform should be a full lifecycle solution that integrates into real-time and batch processes. The solution should begin with the ability to integrate traditional and/or alternative data resources to understand how data can be better leveraged in your particular case. It should have prebuilt predictors and models for rapid deployment and ROI. An ideal platform should also have the ability to test, experiment and monitor performance. Additionally, it should allow you to flexibly configure your credit union’s risk appetite and have a flexible architecture that seamlessly integrates with your existing LOS and LMS workflows.
- How long does it take to deploy the system?
The time taken to deploy a platform and the extent to which the current ecosystem is disrupted while implementing a solution is of prime interest for any CRO. Reduced time-to-market has driven credit unions to select AI-enabled credit underwriting platforms, especially since it seamlessly integrates with data sources without disrupting current processes. Ideally, a credit platform should not take more than 4-6 weeks to deploy.
- Do you need any in-house technical expertise to use the platform?
Today a credit underwriting platform provider should offer you a no-code platform. No-code platforms help facilitate agility wherein you can change your business rules and strategies without external help and see the results for yourself. An AI/ML based model will ensure that whenever new data is collected, the algorithms automatically change the significant input variables and their weights, auto-adjusting the model. Your model will continue to learn and improve without requiring you or your vendor’s intervention.
- What is the scope of the platform?
Whether you are a 100 million dollar credit union or a multi-billion dollar one, a credit underwriting platform should be able to cater to your needs. Additionally once you select an underwriting partner for a lending portfolio, can you extend the scope of their services to other portfolios?
By using the questions above as a guide to assess your credit underwriting vendors, you’ll be able to navigate options in the market. AI is a powerful tool and an insightful demo can not only tell you what the technology is capable of but it can help you analyze your credit union’s current strategy and provide insights on the next best steps. The right platform will use AI to automate your loan decisioning, increase approvals, lower risk, and support your growth and member satisfaction efficiently.