Unlocking Efficiency with Automated Bank Statement Extraction.

Time-Consuming

Manually entering data from bank statements is a labour-intensive process that consumes a significant amount of time and effort. This is especially true for organisations that deal with a high volume of statements daily. Employees need to painstakingly input data, often line by line, which not only slows down the process but also diverts human resources from more value-added tasks.

Error-Prone

Human errors are prevalent when transcribing financial data manually. Typos, transposition errors, and miscalculations can easily occur during data entry. These errors can have serious consequences, such as incorrect account balances, financial discrepancies, and customer dissatisfaction. Detecting and correcting errors can also be time-consuming.

Limited Access

Retrieving and distributing information from manually transcribed bank statements involves physically handling paper documents or searching through digital files, which may not be well-organised. Limited access to the data can delay important financial decisions, customer inquiries, or auditing processes.

Inefficient Data Analysis

Traditional manual methods of data entry do not provide data in a structured and easily analysable format. Data may be disorganised or inconsistent, making it challenging to derive insights from it. This inefficiency can hinder organisations' ability to perform data-driven decision-making, risk assessment, or trend analysis.

Enhanced Efficiency

Automated bank statement extraction significantly accelerates the document processing workflow. Gone are the days of manually sifting through piles of bank statements; by automating this process, you can swiftly and accurately extract relevant data from a multitude of documents in mere seconds. This increased efficiency allows employees to focus on more value-added tasks, leading to better resource allocation and improved productivity.

Accuracy and Reliability

Human error in data extraction can be costly and time-consuming to rectify. An automated solution minimises the risk of errors by leveraging advanced machine learning and optical character recognition (OCR) technologies. It can read and interpret even handwritten or poorly scanned documents, ensuring the highest level of accuracy in data extraction. This reliability is crucial for decision-making processes, risk assessment, and compliance requirements in the financial sector.

Improved Data Analysis

Automated extraction produces structured data that is easier to analyse and interpret. Financial institutions can use this data for various purposes, such as trend analysis, risk assessment, and customer profiling.

Cost Reduction

The cost of manual data extraction is not limited to labour expenses alone. It also includes the potential costs associated with errors, delays, and inefficiencies. By automating bank statement extraction, organisations can realise substantial cost savings, as they require fewer human resources, experience fewer errors, and can process documents faster.

Scalability and Customisability

Automated systems are scalable, making it easier to accommodate a growing customer base or increasing transaction volumes. Automated extraction systems can also be customised to meet the specific needs of financial institutions and their customers.

Reduced Risk of Fraud

Automated processes can include fraud detection mechanisms to identify suspicious transactions or anomalies quickly. This helps financial institutions and customers mitigate the risk of fraud by detecting and responding to it more rapidly.

Compliance and Risk Mitigation

In the highly regulated financial industry, compliance with strict rules and regulations is non-negotiable. A proper solution ensures that extracted data is compliant with industry standards and regulations. This not only mitigates the risk of non-compliance but also enables organisations to maintain a robust audit trail, facilitating transparency and accountability.

It Improves with Time

Using computer vision our OCR extraction is powered by deep learning OCR, which means it is not just another regular OCR or text extraction tool. Together with a human feedback mechanism, our neural networks allow us to get the most accurate reads and ensures that our system gets better and better over time as it learns.

Our natural language processing (NLP) algorithms help automate any business process which involves processing natural language data, while our predictive, text, and behavioural analytics derive high-quality information from any text format.

It is Fast, Trainable, and Configurable

Aside from an increased ROI, Sybrin can offer you out-of-the-box pre-trained IDP solutions which can be easily reconfigured to suit your requirements, while also streamlining your document tracking by providing you with the ability to view records anytime, anywhere.

Customer Onboarding

In the process of onboarding or updating customer information, businesses often need access to bank statement data, especially when conducting know your customer (KYC) procedures.

Banking and Financial Services

Financial institutions can use Sybrin's IDP to streamline the processing of customer bank statements, loan applications, and credit assessments. The solution allows for faster credit approvals, reduced processing times, and improved customer experiences. Additionally, it aids in fraud detection by quickly identifying suspicious transactions.

Accounting and Auditing

Accounting firms and auditing companies can benefit from automated bank statement extraction by expediting the reconciliation process. This ensures that financial statements are accurate, up-to-date, and compliant with accounting standards. Auditors can also use the extracted data to perform detailed financial analysis efficiently.

Government and Public Sector

Government agencies dealing with financial documentation, tax records, and compliance reporting can enhance their efficiency and reduce paperwork with Sybrin's IDP solution. It ensures accurate data extraction, aiding in budget management, financial transparency, and compliance with regulatory requirements.