Why Data Aggregation Is Essential for Effective Treasury Management
As the volume of transactions increases, treasurers must determine how to manage it. Is it more efficient, for instance, to recruit more staff and manage them with spreadsheets? Or is the solution automating treasury management? Previously effective manual methods are no longer ideal or scalable.
But the transition to automation need not be frightening. In contrast, the shift toward digital transformation might provide new business prospects and advantages.
Not only can automating treasury management minimize laborious, manual operations, but it also improves the accuracy of cash reports and predictions, increases talent retention, enhances cash visibility, and decreases fees. Kayenta can help you navigate this critical issue. kayenta.io
Treasury Management automation reduces manual processes
In the previous decade, treasurers had limited access to automation technology. However, banking APIs have changed this, making data management automation more accessible.
APIs allow banks and third-party fintechs to share transaction data between their respective accounts. This has eliminated the need to sign in to numerous portals. Banking APIs connect to your banks in order to collect your banking information into a single format. Automating the download and processing of data enables you to make better judgments in real time.
Additionally, open banking APIs create a single source of truth for your data. Treasury can have insight across all accounts by combining bank data. You no longer need to aggregate separate spreadsheets and question whether your data is accurate. By establishing a cloud-based single source of truth, everyone has access to the same data.
Automating Treasury Management Improves Stakeholder Visibility
Establishing a single source of truth benefits more than just the Treasury and Finance departments. With access to enhanced intelligence, company decision-makers can make smarter choices.
When everyone gets access to the same information, problem-solving is expedited. Treasury is able to provide CEOs with insightful information so that course adjustments may be made swiftly. This can assist your organization in becoming more nimble and adaptable.
Treasury management automation provides opportunities beyond data aggregation. By combining this technology with machine learning (ML) algorithms, your treasury can uncover insights that were previously concealed. Machine learning can examine vast volumes of data and identify patterns much faster than humans can.
Automating Treasury Management Enables More Reliable and Consistent Reports and Predictions
Treasurers may feel assured that their reports and projections are based on reliable data because the data is pulled straight from the bank via an open banking API into a protected and managed database. Additionally, banking APIs standardize data and input it into reports and projections, lowering the likelihood of human error.
The advantage of machine learning in a financial data platform is that it can learn from past data. The more data it can access and the more iterations it can complete, the more it can comprehend. This makes machine learning predictions increasingly accurate over time.
Automating Treasury Management improves Talent Retention and Engagement.
By automating treasury management, tiresome manual tasks can be eliminated and they will be more engaged when they spend less time on tedious duties and more time examining data. By becoming cash management advisers, they can contribute more effectively to the firm.
Treasury Management Automation Reduces Fees
Fees might accumulate with frequent use. By using APIs to automate the aggregation of bank data, you may reduce the need for repeated data requests and thus reduce your costs.
