How automated cash flow analytics help lenders make smarter decisions

Accurate financial analysis is paramount for making well-informed decisions and managing risk effectively in the lending industry.

To achieve this at scale, lenders are embracing the power of automated cash flow analytics to efficiently and accurately analyze borrowers’ financial data confidently.

Automated cash flow analytics technology uses AI and machine learning models to automatically compile and extract valuable insights from financial documents such as bank statements, income statements and balance sheets in one place.

By leveraging cash flow analytics to analyze borrowers’ financial health, lenders can save time, reduce human error and standardize their lending analysis while making faster, smarter decisions.

The traditional lending process

Accurate financial analysis is vital in the lending industry as it enables lenders to assess creditworthiness, determine appropriate loan terms and most of all, mitigate risks. Lenders simply can’t make well-informed decisions or accurately assess a borrower’s creditworthiness without accurate and up-to-date financial information.

Before 2019, credit scores were the most significant borrower metric for consumer lending decisions, often failing to paint the full picture of a borrower’s risk profile. However, today’s consumer and mortgage lenders are increasingly looking to an intelligent infrastructure once developed for small business lending to support their decisions: Cash flow analytics.

Lenders use cash flow analytics to evaluate the flow of money into and out of a borrower’s accounts such as their income, expenses, transaction categories and trends. These details help lenders manage risk, make more informed decisions and qualify borrowers for financing based on the projected future cash flow.

In the traditional lending process, cash flow analysis can be a manual process relying on spreadsheets and human input. This is time-consuming and resource-intensive, making it difficult for lenders to process large volumes of financial data efficiently or accurately. To more precisely predict default, lenders are increasingly looking at cash flow automation technology to expedite, standardize and improve their overall approach.

How automated cash flow analytics help lenders make smarter decisions

By offering lenders a more advanced and reliable way to analyze and interpret a borrower’s financial data, automated cash flow analytics tools enable lenders to make smarter, faster and more confident decisions.

These tools utilize sophisticated algorithms and machine learning techniques to process and extract valuable insights from cash flow statements, income statements and balance sheets. By automating the analysis process, lenders discover a multitude of benefits.

The obvious benefit of automated cash flow analytics is the enhanced accuracy and speed of analysis. These tools can process large volumes of financial data more quickly and efficiently than humans alone, eliminating the potential for human error inherent in manual analysis. 

Automation also enables lenders to standardize their data analysis by assessing borrowers through a unified lens that aggregates past performance, current financial health and future projections. By analyzing the cash flow of a loan applicant, lenders can gain deeper insights into their ability to generate sufficient income to repay the loan, helping mitigate future risk and improve loan portfolio performance. 

These tools can also identify key indicators in historical data and patterns that may signify financial instability or an increased likelihood of default. This early identification means lenders can take preventive measures to mitigate risk such as additional verification checks or restructuring loan terms. 

By helping lenders proactively identify and manage risk, automated cash flow analytics also help lenders improve their loan portfolio management. By automating the analysis process, lenders can streamline underwriting and qualification procedures. This efficiency not only allows lenders to process loan applications more quickly but also helps in identifying potential issues and fraudulent activities in a more timely manner.  

Ultimately, this combination of improved accuracy, risk mitigation and operational efficiency positions lenders to make smarter decisions and spend more time focusing on strategic work and building customer relationships.

Implementing automated cash flow analytics

Implementing automated cash flow analytics involves integrating these advanced tools into existing lending processes and systems. This integration ensures a seamless flow of data and allows lenders to leverage the benefits of automated analysis without disrupting their operations.

By integrating automated cash flow analytics into their existing systems, lenders can harness the power of these tools to enhance their decision-making process and improve overall efficiency.

To successfully implement automated cash flow analytics, lenders should look for technology partners that provide the necessary training and resources to ensure a smooth transition to automated cash flow analytics and take full advantage of its benefits.

How Ocrolus is enhancing automated cash flow analytics

Ocrolus leverages best-in-class artificial intelligence, proprietary algorithms and our collective experience with hundreds of lender clients to provide trusted analytics that empowers lenders to underwrite more loans confidently. We’ve recently expanded our capability to include new features and more robust insights with the goal of enabling faster, more informed decision-making.

Our technology standardizes unstructured, raw data into actionable insights to give lenders the information they need to understand a borrower’s income or business in greater detail. With a proprietary transaction tagging algorithm specifically designed for cash flow underwriting, we enable lenders to easily identify things like income sources, lender payments, recurring transactions and overdrafts while also providing detailed revenue and expense calculations.

We also offer lenders a library of pre-built cash flow attributes that enables them to evaluate borrowers’ debt capacity, cash flow trends, volatility and more. These cash flow features are optimal for risk modeling, allowing lenders to predict a borrower’s ability to repay more precisely.

Lenders can retrieve all of these insights through our easy-to-integrate API endpoints to save time and through our interactive dashboard that provides various cash flow visualizations to help streamline lenders’ workflows.

As the lending landscape continues to evolve, embracing automated cash flow analytics is no longer an option but a strategic imperative for lenders. Automated cash flow analytics gives lenders a competitive edge, enabling them to assess risk more accurately, make data-driven decisions and adapt to changing market conditions.

By leveraging these tools, lenders can ultimately make smarter decisions, mitigate risk and improve loan portfolio management, leading to greater success in an ever-evolving lending landscape.

Takeaways

• Automated cash flow analytics uses AI and machine learning to enable financial institutions to make smarter lending decisions
• Leveraging cash flow analytics helps lenders improve accuracy, risk management and loan portfolio management
• Enabling lenders to assess risk more accurately, automated cash flow analytics give lenders a competitive edge despite changing market conditions

Ready to assess borrower risk with confidence?

Book your demo to discover how Ocrolus empowers lenders to understand the unique cash flow dynamics of their borrowers to manage risk and accelerate lending decisions.