Financial spreading refers to essentially creating a spread of information about a client. It works like a chart showcasing your client’s credit status and capacity, based on statement records. Financial spreading is necessary for a financial institution to determine its client’s creditworthiness. The finance market is currently undergoing a digital revolution like the rest of the world, with automated financial spreading taking centre stage.
Financial spreading is essential to risk management. Every time an institution has a new borrower or client, they invest in someone and risk their credit. Financial spreading helps them ensure that this risk is worth it and not in vain. It gives them insight into what interest rate to ask and the ideal tenure and repayment capacity of the client.
Collating and analysing all the necessary data before determining the risk a client poses can be very lengthy. When done manually, it may also be prone to human error, further influencing the outcome. With automation, such shortcomings are easily sidestepped since machine learning and AI come into the picture, improving outcomes.
The Benefits of Automated Financial Spreading in Risk Management
There are many types of financial risks institutions incur. The most common ones you might hear about include credit risk, liquidity risk, operational risk, speculative risk, asset-backed risk and currency risk. Every endeavour automatically also has an associated risk simply by being an endeavour – purity risk.
Automation can help in most of these risk types by giving immediate, real-world updates on risk status through financial spreading. Understanding risk requires an intimate comprehension of how internal and external factors play a role in determining the extent of risk. Automated financial spreading ensures that you see how these factors like company dynamics and economic trends affect your client’s finances in real-time.
This factor brings us to the first benefit of using financial spreading automation for risk management.
Guaranteed Accuracy and Speed
One of the biggest drawbacks to manual spreading was the lack of efficiency. Since the process took so long to ensure accuracy, everything had to be on-hold until the spreaders and analysts could finish their part. Automation solves this, especially in a multilingual industry like finance.
Financial statements are in various languages, and hiring the necessary resources in these languages can be a challenge for large-scale, multinational financial institutions. This is the first area automation solves with auto-translation. The immediate increase in speed is unparalleled, except for the simultaneous increase in efficiency. Additionally, institutions can now divert resources to more analysts and external reviewers for better, more accurate interpretations of data.
Many of these analysts and third parties are checking for weak links and areas with potent risk. Therefore, companies can take a more proactive approach, preventing the risk before it occurs. Automated financial spreading enables such precision and actions.
Centralised Approach
Today, many financial institutions want to centralise the financial spreading function, which is impossible in the manual method. Especially when they open branches in multiple countries, having a shared services model is the only scalable way to move forward. Automation helps in this regard, reducing manual intervention by introducing systems for centralisation and cost-efficiency.
Additionally, the introduction of AI into automated spreading improves this significantly. Institutions can leverage AI in financial spreading, achieving accuracy, especially for repetitive activities. Introducing AI into repetitive tasks further improves the likelihood of understanding if and when something out of the ordinary occurs.
Therefore, risk management and mitigation are much easier. Especially when we consider that every business decision is risky, minimising risk is often the goal. Automated financial spreading also helps show the client areas of speculative risk (i.e. risk within a financial model) to understand possible weaknesses. The lender and borrower can then work together to strengthen the spread with insightful analyses and long-term strategies for business growth.
Using financial spreading automation, therefore, also boosts the company-client relationship. One of the biggest risks a company takes when giving a loan is defaulting. Although speculative models can help mitigate this to an extent, these models prove far more effective when combined with automation and financial spreading.
Models also allow clients to see the outcome of certain divisions within real-world simulations. Therefore, both them and you can make more educated decisions towards maximising financial security and boosting growth.
