AI Agents Enhance Invoice-Bank Transaction Matching. Mentally Robot’s Potential to Rival Seasoned CPAs’ Reliability 

Imagine a practice associate who, with the speed of a computer, can complete a first note in seconds. For professional firms and companies, this scenario might seem utopian, especially in the context of bank reconciliation. Every day, businesses issue, send, and receive various types of documents—invoices, tax payment documents, credit card reports, payroll coupons and so forth.

Typically, at the end of the month, it is necessary to match these documents with specific bank transactions, a process that can be quite laborious. This is particularly true when transaction totals must be split and allocated across multiple documents or different expense and revenue accounts—an operation that many accountants find tedious.

Is there a machine that can understand this matching concept? 

Hard to say. In the past, this problem has been addressed by various software houses in Italy by allowing users to enter more or less complex registration rules depending on the ERP system. However, these rules come with significant limitations:

1. It’s not always feasible to have someone on staff with sufficient computational thinking skills to create and consistently apply a strategic set of rules.
2. Rules are inherently limited and, inevitably, some fail. On average, an estimated 25 percent of transactions remain unaccounted for by such rules.

Moreover, ERP systems and accounting software for accountants are primarily designed to ‘chase’ tax and regulatory compliance, often neglecting aspects of productivity and the number of hours worked, and particularly failing to track workflows and optimize them. This focus adds another layer of inefficiency and wasted time to the reconciliation process.

There are real difficulties in applying A.I. to bank reconciliation.

First, banks and companies often record transactions under different names and on different schedules. This discrepancy is the core reason for bank reconciliation: to harmonize two disparate methods of recording transactions.

Second, there are various modes of transaction and payment. For instance, how can we trust a computer to accurately distinguish between payments made by check or credit card?

Additionally, there is a matter of timing: the notations for different transactions may need to be aligned on significantly different timelines. For example, there can be a time lag between the issuance of an invoice and its payment. Even just considering monthly, quarterly, or semi-annual timelines for accounting entries complicates the scenario for a hypothetical “smart computer.” In short, matching a document with a bank transaction can be even more challenging for AI than simply recording an invoice.

Current ERP systems do not alleviate these challenges. Many have outdated architectures that burden users with unnecessary and cumbersome steps, sometimes just to import data from the bank. Moreover, managing a data import does not equate to reconciliation, though the two are often conflated by sales staff of ERP software companies.

At this point, many firms may wonder: Why not just use Excel? While Macros provide an improvement over manual operations, they are not sufficient. This is partly because initiating such operations requires time and computational resources. Furthermore, Macros struggle with the distinctions and large data volumes mentioned earlier. Additionally, work psychology suggests that our brains are reluctant to engage in mundane and tedious tasks, such as loading an Excel file into a management system, even if the transactions are already reconciled.

Mistakes, as accounting firms know, cost money. And employees’ time even more so.

Result:

Reconciliation and the initial compilation of notes are often largely manual processes. This is primarily due to the wide variety of information that must be processed by a human employee.

But what if this employee were digital?

Mentally’s solution

The Mentally.ai robot, a valuable ally to accounting firms for the past three years in recording invoices, now has a counterpart: Mentally Reconcilia, which specializes in bank reconciliation.

How does Mentally Reconcile work?

Essentially, the AI available in the market today cannot always be relied upon for accurate predictions. It is prone to producing hallucinations, incorrect data, and errors that can significantly skew the final results. Such inaccuracies are unacceptable for entities needing to enhance their accounting management, whether they are companies or professional firms.

Clients require a reliable collaborator, not just a basic program that needs constant rechecking to prevent errors. Mentally Reconcilia addresses this issue by combining two advanced technologies: robotics and artificial intelligence.

Mentally Reconcilia recognizes 4 types of banking transactions:

1. Transactions that can be predicted and categorized using simple user-side rules with zero chance of error.

2. More sophisticated transactions that can be predicted with artificial intelligence and have zero or negligible chance of error.

3. Transactions that can be predicted with artificial intelligence but have a small probability of error.

4. Transactions that necessarily require interaction with the customer, or in the case of a company, accessing and checking its documents.

The robot autonomously handles the first two categories, while the third and fourth categories are subject to user feedback. This feedback process is where the revolutionary nature of Mentally Reconcilia shines: the robot learns from each customer interaction, gradually becoming as reliable as a trusted, experienced coworker who understands the firm’s specific realities and rhythms. This level of personalization is unique to Mentally Reconcilia.

Initially, it may be necessary to adjust the robot’s predictions by adding new rules and exceptions. However, after a preliminary phase of 3 to 7 weeks, the Mentally robot achieves full autonomy. It can then directly match invoices to bank transactions, or F24 to bank transactions, etc., and seamlessly integrate these into the management system—an ideal setup for compiling initial notes.

What do we mean by Process Robotization? ?

The primary advantage of the Mentally Reconcilia robot in bank reconciliation lies in its ability to create rules and exceptions, giving AI the necessary boost to make machine intervention genuinely effective. On its own, artificial intelligence might waste time and resources, as it depends on rules that are obscure and beyond our control. This is particularly counterproductive for many accounting firms, especially those using outdated management systems where AI can seem like a “black box.”

However, Mentally Reconcilia changes the dynamic by placing you in the control room. It enables businesses and firms to not only harness the vast potential of AI but also to guide and “educate” it effectively through a systematic feedback process. Thus, the AI doesn’t just “learn on its own”; it learns from your specific instructions, much like a skilled accounting associate, and avoids repeating the same mistakes.

It’s important to note that while Mentally Reconcilia was first designed for italian accounting firms, it is also perfectly suited for companies managing their own in-house accounting.

Act now to leverage these capabilities before your competitors do!

Mentally Reconcilia is ideal for businesses that:

• Are current users of Mentally.ai for invoice recording: Integration of the two functions is seamless and hassle-free.
• Have a budget of at least $2000: Making it accessible for those ready to invest in efficient solutions.
• Require a scalable product: For firms with fewer clients, Mentally Reconcile offers cost-effective options.
• Have a project leader with technological proficiency: Especially beneficial for those who possess logic-deductive skills for analyzing and optimizing processes.
• Use or plan to use Teamsystem Pay: It is fully compatible and enhances the utility of Teamsystem Pay.
• Aim to increase profitability by reducing labor hours: Mentally Reconcile significantly cuts down the hours spent on bank reconciliation, fostering more efficient staff utilization.

Interested in maximizing your practice’s efficiency and exploring the features of the Mentally Reconcilia robot in more detail?