ZI, the NASDAQ symbol for ZoomInfo, is ranked eighth on Fortune's esteemed Future 50 list for 2023. This exclusive list, which includes more than 1,700 of the world's largest publicly traded firms, identifies businesses that are expected to have rapid long-term revenue growth and considerable shareholder returns.
The Future 50 is an index that Fortune has created since 2017 in partnership with Boston Consulting Group (BCG) to highlight businesses that are well-positioned for sustained growth and higher shareholder returns.
The BCG Henderson Institute conducts a thorough review as part of the selection process. Using a "vitality" score, this evaluation looks at market-based standards as well as a thorough examination of a company's growth potential and ability to meet that promise. This assessment includes a range of financial and non-financial measures, including long-term strategic direction, investments, personnel capabilities, technology advancements, organizational structure, and structure.
ZoomInfo's CEO and founder, Henry Schuck, credits the company's continued emphasis on long-term growth for its placement in the Future 50 ranking. In order to effectively interact with their target consumer base, he stresses that many of ZoomInfo's clients are also listed on this prestigious list. They do this by utilizing ZoomInfo's unified go-to-market platform, which is strengthened with cutting-edge data, AI-driven insights, and automated workflows.
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A New and Innovative Credit Scoring Model for Non-Traditional Business Lenders
Applying old-school credit scoring methods and using out-of-date data where new market conditions prevail could restrict lending and hinder economic growth. For such lenders of this type, being shy away from technology and resistant to change could jeopardize opportunities to grow loan portfolios and boost profit.
Lenders traditionally rely on credit scoring based on historical financial data that don’t reveal a business’s ability to repay its loan amount. In this approach, lenders request a mile-long list of personal and business documents from potential borrowers. The financial data includes credit history, annual revenue, balance sheet, income tax returns, profit & loss statement, collateral, and other historical financial statements of the borrowers.
In this credit scoring model, financial data has more weight in determining how stable and efficient the borrower is when it comes to funding their business. Lenders start by determining the ability of a borrower to repay its debt obligations with interest in a given period. For the most part, this typical credit scoring relies on the tenure of the existing loan, the amount and loan type a borrower already has, and current interest rates on the loan.
Lenders use these reports to evaluate the risk profile of the borrower, which helps lenders determine whether to approve a loan or not. Obviously, a borrower with an excellent credit score tends to get a low-interest loan than those with a poor credit score, though the final decision is made by the lender, with FICO inputs used as guardrails.
No doubt, the pandemic has eroded the credit scoring of many businesses who have closed or shut down or lost their biggest clients/customers, entailing innovative ways to assess borrower creditworthiness.
Low-Quality Data and The Unbanked
For example, an excellent credit score does not guarantee that a business will generate the same revenue and will be consistent for its payments in the future. Moreover, it won’t tell if a business has shut down or is struggling with cash flow issues. A new and innovative solution to this increasingly widespread problem is leveraging forward-looking data for determining creditworthiness.
One of the most robust, accurate, and real-time data sources of information is cash flow predictive data. The perfect blend of accounting, banking, financial, and cash flow data help lenders see the past, present, and future financial health of a business and make data-informed intelligent decisions.
Today, some futuristic financial technology companies empower non-traditional business lenders to examine borrowers’ banking, financial, accounting, and predictive cash flow data to take note of spending habits and monitor future income and expenses.
Some advanced lending-tech firms enable lenders to access and analyze these data sets from the click of a button. With the help of artificial intelligence and machine learning, these FinTech firms are creating a single financial data APIs for lenders to collect, review and analyze the most accurate and efficient data of their borrowers.
By leveraging this valuable data, lenders can accurately predict the future financial health of a business, and ultimately reduce loan bias, provide customized solutions, enhance customer experience, lessen credit risk, determine creditworthiness, and take their business forward.
In the current lending scenario, non-traditional lenders must adopt new and innovative credit scoring methods for businesses that are unbanked or underbanked.
Both Forward-Looking and Historical Data are Vital
New credit scoring is an augmentation and not a replacement of traditional credit scoring. Forward-looking data are more numerous and less organized than the data used in traditional credit scores.
Fortunately, besides historical data, real-time financial data is now available for lenders, and state-of-the-art technologies are helping lenders to access, analyze and normalize this financial data. Using this data, lenders can understand their customers better, create new and innovative financial products, and build better-performing loan portfolios.
Today, FinTechs can see a business’ past, present, and future data, enhanced by AI and ML, which means benefits for both customers and lenders. So, if you’re a non-traditional business lender who is struggling to determine the creditworthiness of your borrowers, this new credit scoring technology is your perfect solution. By utilizing a financial data API and using it for credit scoring, you can position yourself as an industry leader and become the financial expert of the future.
