Is data collected from multiple sources making the reconciliation process difficult?

In today's digital age, data has become the backbone of businesses. Companies use data to gain insights, make decisions, and drive growth. However, with the increasing volume and complexity of data, reconciling it has become a significant challenge for many organizations. Let’s see what these challenges are and what a possible solution might be.

Data silos and fragmentation

One of the biggest challenges in reconciling data from multiple sources is the existence of data silos. Data silos are collections of data that are isolated from the rest of an organization's data, often due to the use of different software systems or data management practices. As a result, data may be fragmented across various silos, making it difficult to consolidate and reconcile.

Lack of data standardization

Multiple data sources, like internal financial records, bank statements, third-party payment processors, and point-of-sale systems, come into play while reconciling data. One of the primary challenges in reconciling data from these many multiple sources is the lack of standardisation.

When data is not standardized, it can have different formats, units, definitions, or labels, which can create confusion, errors, or mismatches in the reconciliation process. According to a report by Deloitte, 1 in 6 reconciliations are noted with some errors or exceptions.

Data Integration Challenges

It’s important for an organization to ensure the accuracy and integrity of financial data, which often involves reconciling data from various sources, such as different subsidiaries, departments, or systems. However, reconciling data from various sources can lead to data integrity issues due to differences in data formats, currencies, accounting practices, and other factors. These issues can make it challenging to accurately consolidate financial data and can potentially result in inaccurate financial reporting, which can have significant consequences for the organisation.

Data Security Challenges

Data from multiple sources may contain sensitive or confidential information that requires protection. Ensuring data security can be challenging when dealing with data from external sources, which may not have the same security protocols as internal sources.

The case of Kensington and Chelsea Council being fined £120,000 highlights the potential consequences of failing to ensure the security of data from different sources. The pivot table error in this instance led to the exposure of hundreds of property owners' data, which not only put the individuals affected at risk but also damaged the council's reputation.

The Role of advanced technologies in Reconciliation

Advanced technologies such as artificial intelligence (AI) and machine learning (ML) can play a crucial role in improving the reconciliation process.

A medical device manufacturer faced challenges with inconsistent processes, sources, formats, and structures across different business units. To address this, they integrated AI and automation, resulting in improved work allocation, reduced transactional tasks, and increased time spent on strategic initiatives. The integration also improved balance sheet integrity, leading to a $225 million reduction in inter-company balances within two years.