How Greater Data Insights Are Allowing Lenders to Help SMEs – Fintech Finance Virtual Arena
What’s the biggest workflow bottleneck in your manual underwriting process?
Faster Credit Risk Analysis to Streamline the Loan Application Process
What’s the biggest workflow bottleneck in your manual underwriting process?
Let us guess: the weeks it takes to manually assess the risk profile of potential loan or mortgage applicants. Collecting, documenting and analyzing financial data and credit scores. Rinse and repeat.
Decrease Lending Costs
You know that the credit risk analysis step of your lending process is neither efficient nor scalable.
What if you could offer your customers loan or mortgage credit risk analysis in mere minutes?
Imagine the competitive advantage of differentiating your services with a faster, more efficient loan experience. Our credit risk analysis platform has forever transformed how North American financial institutions determine the risk profile of potential loan or mortgage applicants.
Now, your commercial banking customers can wave goodbye to a lagging loan experience. Your team can leave behind, time- consuming manual processes. And you can stop worrying about inconsistent risk assessment.
How Credit Risk Analysis Works
Our credit risk analysis platform automatically calculates monthly cash flow, annualized cash flow and debt service coverage ratio.
It automatically tags and categorizes individual transactions into groupings – diagnostics (recurring), source (e-transfer) and purpose (loan).
Based on 10M+ data points, it identifies outliers, trends and risk indicators that could lead to failure to pay/delinquencies.
Ken Lim
Process Enhancement Manager, Vancity
It’s great to be able to walk through the decision output with members; even with those who don’t get approved. Because this enables them to understand what they need to address in order to get a loan in the future. Having up-to-the-minute access to this valuable data means that we always have a reason to start a conversation with a member.
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