Cash Flow Forecasting Challenges for Lenders: Key Issues and Solutions

Assessing the financial status of an enterprise is very important for informed decisions. Cash flow forecasting comes in very handy at this stage; however, it is not always as straightforward as it appears. It depends on so many variables affecting the financial outlook of a company that it becomes harder for loan providers to place faith in the forecasts they rely on.

Challenges and Solutions of Cash Flow Forecasting

Inaccurate Data

Many businesses rely on manual processes to build cash flow forecasts, increasing the risk of human error. When lenders cannot trust forecasts developed from faulty assumptions or outdated data, the risks can be slightly easier to assess and structure appropriate terms for the loans from lenders. Given that more than 60% of all business failures are really profitable by nature but happen to have run out of money, a substantial contributor to these situations is indeed inaccurate forecasting.

Solution:

Encourage businesses to integrate real-time financial data from accounting software and banking platforms.

Use AI-driven analytics to cross-check forecasts with historical data and spot inconsistencies.

Offer financial literacy resources or workshops to help businesses improve forecasting accuracy.

Outdated Information

Cash flow forecasts need frequent updates to reflect a business’s current financial condition. However, many SMEs fail to revise their projections regularly, leading to outdated insights that can misguide lenders in credit decisions.

Given that 91% of small firms experience relative success in their first year, yet cash flow is one of the primary reasons they struggle to survive beyond five years, staying updated is crucial.

Solution:

Implement Open Banking and automated financial reporting tools to provide lenders with real-time financial snapshots.

Advise businesses to update forecasts at least monthly and incorporate rolling forecasts for ongoing adjustments.

Provide dashboard tools that allow businesses to compare actual vs. projected cash flow in real-time.

Data Silos

Financial information is often spread across different departments and systems, making it difficult to get a full view of a business’s cash flow. Incomplete or even inconsistent data complicates lending decisions, and risk assessments are equally affected. It will be nearly impossible to make the best offers when global median interest rates for SME loans stand at 50% above the average.

Solution:

Encourage businesses to adopt cloud-based financial management systems that consolidate data from different sources.

Use APIs to pull data from various financial tools into a single platform for a holistic view.

Promote financial software that allows multiple stakeholders to collaborate on cash flow planning.

Complex Data Integration

Businesses often struggle to integrate financial data from ERP systems, bank statements, and investment portfolios. This eventually leads to delays and errors in cash flow forecasting. This fragmented data limits lenders’ ability to assess financial health accurately.

Solution:

Offer businesses guidance on selecting integrated financial software that seamlessly connects banking, accounting, and ERP data.

Develop partnerships with fintech providers that offer automated data aggregation and forecasting tools.

Encourage businesses to work with accountants or financial advisors to streamline their data integration process.

Lack of Automation

Most businesses depend on spreadsheets and manual math for cash flow forecasting. A very time-consuming and error-ridden process, to say the least. Otherwise, lenders tend to receive non-consistent reports that are always unreliable.

Solution:

Endorse the shift to AI forecasting tools that allow for no possibility of human calculation errors and better efficiency.

Invite businesses to lend through digital portals that are tied to their current financial software package for automatic feeds.

Provide educational content on how automation improves forecasting accuracy and saves time.

Forecasting Method Selection

Choosing the right forecasting method (e.g., direct vs. indirect forecasting) is critical for accuracy. However, businesses often lack expertise in selecting the best approach, leading to unreliable projections.

Solution:

Guide businesses on choosing forecasting methods suited to their industry, cash flow volatility, and financial structure.

Provide templates and best-practice frameworks for different business models.

Offer advisory services to help SMEs refine their forecasting techniques.

Trend and Pattern Identification

Accurate forecasting requires identifying cash flow trends and patterns, but many businesses lack the analytical tools or expertise needed. Without this insight, their projections may miss key financial risks or opportunities.

Solution:

Recommend AI-driven analytics tools that detect cash flow trends and provide predictive insights.

Offer reporting dashboards with visual trend analysis to help businesses spot patterns.

Conduct training sessions on using financial analytics to interpret cash flow trends effectively.

How Pulse Can Help Lenders

Pulse provides a set of robust modules and features that aim to solve common cash flow forecasting challenges lenders encounter. Advanced technology and real-time data integration provide the Pulse platform to lenders as tools for enhanced decision-making and minimising the risks of inaccurate forecasts. Here’s how it can make a real difference:

Real-Time Financial Insights

Pulse connects to Open Banking and accounting software for real-time financial data so lenders have the most accurate cash flow projections at any given time.

How it helps: Lenders can receive a comprehensive view of cash flow projections, including incoming payments, loan repayments, and expenditures, without waiting for manual updates.

AI-Driven Analytics

Using AI, it cross-checks forecasts with historical data, identifying inconsistencies and providing predictive insights for more accurate credit assessments.

How it helps: Lenders can assess the viability of a business’s cash flow forecasts by evaluating past performance against projected trends, enhancing their ability to manage risk and structure loans accordingly.

Data Integration Across Systems

A major challenge among lenders is the integration of shattered financial data stored in unrelated systems. Pulse answers this by tying ERP, accounting, and banking data into a single frame. This gives lenders a holistic 360-degree view of the financial status of a borrowing entity.

How it helps: With historical financial data available to the lender through an amalgamated view, it is easier to validate the cash flow forecast and, thus, lead to sounder lending decisions.

Proactive Risk Mitigation

This data analytical platform is designed to spot potential shortfalls and financial risks before they occur. Pulse detects potential cash flow shortfalls early, allowing lenders to take action before issues arise, reducing risk, and improving loan performance.

How it helps: Lenders can take early action to address potential defaults, mitigating the risk of financial instability and ensuring better loan performance.

Collaboration and Customisation

The pulse supports collaboration among the lenders, borrowers, and financial advisors to facilitate a shared approach to forecasting and financial planning. It can be customised, depending on the specific needs of different lenders and businesses so forecasts fit well into particular goals and financial structures.

How it helps: By fostering better communication and customisation, Pulse ensures that lenders have the flexibility to offer more tailored and relevant loan terms to clients, resulting in mutually beneficial relationships.

Ready to see how Pulse can transform your lending process? Contact info@mypulse.io for a demo today!