How To Crack The Small Business Lending Code

Using a lending analytics platform that combines machine learning, real-time cash flow, and credit intelligence.

 
 

The pandemic has made doing business extraordinarily difficult for many small and medium businesses (SMBs), and for the financial institutions that provide these enterprises their working credit lifelines.

Credit unions that provide credit lines and other business services know well how different lending is to a business than it is to an individual, and more complicated. That’s especially true when it comes to determining creditworthiness.

Adding further pressure to the process is the need for speed. Credit unions that can provide SMB owners and managers the same kind of fast decisioning and funding as these businesspeople enjoy in their personal finances will find themselves a step ahead of the competition from traditional FIs and fintech disruptors alike.

Here, Gord Baizley, CEO of JUDI.AI, explains how its small business lending analytics platform can help member-owned financial cooperatives leverage real-time cash flow and credit intelligence to help their business members – and their own business – survive and thrive.

Please describe the difficulties in credit scoring small businesses and how your solution overcomes that problem.

Gord Baizley: SMBs play a huge role in keeping the economy alive – but most credit unions currently find themselves under indexed in small business lending. Millions of small businesses struggle to access affordable credit because of weaknesses in traditional lending systems. Businesses owned by racial minorities, recent immigrants, and women face even more challenges in accessing credit.

Traditional commercial lending models and processes were designed for analysis of established businesses seeking larger financing amounts – not micro-dollar loans. The highly variated nature of SMB elements such as business models, operating costs, revenue, and seasonality make small business credit decisioning more complex. Not surprisingly, a “one size fits all” credit model approach has proven to be ineffective.

For credit unions to successfully service small business needs, you first need to address common lending barriers such as cost-to-serve, risk, and operational inefficiency. Although it is a part of your DNA to grow communities, you must be ready to overcome:

  • Missed lending opportunities due to low SMB credit score hit rates, inflexible “one size fits all” commercial credit risk models, thin credit history, and stale financials
  • High risk for low margins and interest rates (50% of small businesses fail after five years)
  • Manual inefficiencies in loan application intake, underwriting, and annual reviews
  • Increased competition from big banks, alternative lenders, and big techs that are setting a higher standard for borrower convenience and responsiveness
  • Lack of real-time visibility into predictive risk and growth indicators
  • Lack of post-lending SMB cash flow insights to align product offerings, successfully grow SMB relationships, and acquire new ones

The good news is that it has become much easier to augment your relationship banking tactics with technology such as JUDI.AI.

Our SMB-specific credit model supplements traditional service bureau credit scoring with cash flow analysis and machine learning algorithms to help credit unions gain a more accurate, up-to-date picture of SMB creditworthiness and make better lending decisions – even to those members with thin financial history.

Please describe how JUDI.AI differs from competitors.

GB: Innovative credit unions choose the JUDI.AI lending analytics platform for our SMB credit science expertise, speedy onboarding process and amazing team.

When it comes to SMB credit science, the JUDI.AI team are pioneers in real-time cash flow data analysis and AI-driven modelling. We have built out a robust SMB-specific credit risk model that has decisioned on more than $1 billion worth of SMB loan applications, ingesting more than 25 million data points. We are known for bridging the gap between complex credit modelling, advanced machine learning algorithms, and user-friendly interfaces.

The JUDI.AI solution does not require a significant resource commitment. It can be configured and deployed in four to eight weeks, as opposed to 12 months. It is a standalone, SOC 2 Type 2 compliant platform hosted in the Microsoft Azure Cloud. This is considered by many credit unions to be a quick digital transformation win, with an immediate ROI. Robust APIs and modularity options make JUDI.AI easy to integrate with existing loan origination systems, digital onboarding, or core banking systems.

Also unique to JUDI.AI are our amazing people that really make the difference. Our credit union partners love us for a reason. We have a seasoned customer success team that is skilled in training and digital transformation – averaging an 85% customer satisfaction score. Our data science team continues to grow, with deep machine learning knowledge and credit data expertise. JUDI.AI was also founded by bankers and accelerated by technologists.

Please describe the deployment process for your solution and how it works from the back-office perspective.

GB: We typically start with a proof of concept (POC) that includes:

  • A retrospective underwriting analysis of your SMB loan portfolio – Re-run SMB loan applications through the JUDI.AI credit risk model and compare results
  • A live JUDI.AI deployment focused on automated underwriting – Trialed by your underwriters and lending advisers
  • A snapshot of real-time cash flow monitoring – See a view into credit health post-lending

The fastest and most agile implementation of JUDI.AI is a comprehensive, standalone solution out-of-the-box. We can also customize JUDI.AI to meet your unique credit model and policies, if desired. APIs are available if you wish to integrate this solution within your existing loan origination systems, digital onboarding or core banking platforms of choice.

During the implementation process, we will work closely with your business group to identify goals and measures of success for the first six months, 12 months and beyond.

What is JUDI.AI’s take on SMB lending in the pandemic?

GB: The urgency of the Paycheck Protection Program during COVID-19 pushed many credit unions to adopt faster, more convenient ways to disburse government funds to small businesses. As a result, many were rewarded with the onboarding of new members– and a future opportunity for business banking growth if they can successfully convince these somewhat transient borrowers to stay.

The scale of deposits has outpaced loan demand. Low rates and government payments have resulted in more paydowns, re-financings, and loan portfolio turnover. Establishing the true creditworthiness of SMB borrowers has also become trickier, thanks to a provision in the government’s coronavirus stimulus package, stating lenders that allow borrowers to defer their debt payments cannot report these payments as late to credit-reporting companies.

These reporting restrictions mean any higher risk of default associated with missed and deferred payments over the past few months will not be reflected in traditional credit bureau scoring models.

With the cash flow data analysis and ongoing risk monitoring offered through JUDI.AI, we are helping credit unions to win their PPP borrowers over by:

  • Deepening relationships and providing the business insights and advice SMBs need to grow their business
  • Accelerating the application intake and underwriting process for faster access to financing
  • Making it easier to apply for SMB loans across digital and in-branch channels

Please describe how credit union staff use the system and the learning curve for using it effectively.

GB: We work together on a change management plan to roll out JUDI.AI to the staff, but it usually only takes about three hours of training for SMB lending teams to start helping with credit decisioning and automated underwriting.

Cash flow performance monitoring is also intuitive, with cash flow metrics automatically flagged for investigation. When it comes to analytics, most of our partners are starting with a snapshot of SMB account statuses across their loan portfolio. JUDI.AI comes with this dashboard pre-built for ease of use.

To summarize the three main use cases:

  1. SMB-specific credit analysis and automated underwriting – Increasing the speed and approving 20-35% more SMB loans through automation, machine learning, and alternative cash flow data analysis for increased scoring accuracy. JUDI.AI overcomes the challenge of low SMB credit score hit rates and stale financials by supplementing service bureau credit scoring with cash flow analysis. Manual application intake, credit risk analysis, and credit decisioning are digitized to process 50% more applications with no additional resources. Intelligent credit decisioning is accelerated from weeks to minutes, creating optimal efficiency for borrowers and lending advisers.
  2. Continuous cash flow performance monitoring – Monitoring current SMB operating and financing cash flow positions to immediately flag high-risk indicators and account growth opportunities. JUDI.AI provides continuous cash flow performance monitoring so that credit unions can keep track of the financial health and habits of small business borrowers post-lending. High-risk cash flow metrics are immediately flagged, such as NSFs, missed payments, debt service coverage ratio, new line of credit payments, and negative account balance trends. JUDI.AI also re-scores the risk of loans in real time, presenting an opportunity to streamline annual SMB loan review processes and move to “all-the-time” review processes.
  3. Loan portfolio reporting and post-lending growth analytics – Leveraging data insights and credit intelligence to deepen small business relationships. JUDI.AI provides portfolio performance reporting that helps credit unions prioritize risk and growth opportunities to reduce delinquent loans and accelerate loan portfolio growth. With visibility into key performance indicators and business trends such as number of new SMB account openings, loan approval amounts, and debt service coverage ratio, credit unions can customize segmentation criteria and automatically flag small businesses that qualify for upsell campaigns, including pre-approval credit cards.

Click here for more information about the JUDI.AI small business lending analytics platform. Contact the company here, at info@judi.ai, or at 604.901.5889.

 

 

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