Advanced Analytics: Supports your decision-making

Predictive modeling uses historical data and statistical algorithms to predict future outcomes. In finance, this can be used to predict customer behavior, sales trends, cash flow or potential risks. For example, by using predictive analytics as part of the financial statement preparation process, finance teams can anticipate potential discrepancies or problems. This enables them to close the books faster and more accurately. Regression, decision trees, neural networks and time series analysis are common tools in predictive modeling.

Prescriptive Analytics geht noch einen Schritt weiter, indem konkrete Handlungsanweisungen auf Basis prädiktiver Modelle vorgeschlagen werden. Dabei geht es nicht nur um eine Vorhersage was passieren könnte, sondern darum die besten weiteren Schritte abzuleiten. Finanzteams können dies nutzen, um Transaktionsprozesse zu optimieren, indem sie den idealen Arbeitsablauf vorschlagen oder Anpassungen bei der Ressourcenzuweisung zur Optimierung der digitalen Prozessautomatisierung empfehlen.

Machine learning and artificial intelligence (AI) enable systems to learn from data and improve themselves over time without explicit programming. In finance, machine learning can automate workflows as well as process designs and make real-time adjustments and optimizations to improve ongoing financial processes, such as identifying errors in accounting or suggesting cost savings during month-end closing.

Unstructured data processing techniques, such as natural language processing (NLP) and sentiment analysis, are essential to gain insights from different types of data such as emails, reports, contracts and customer feedback. These techniques can significantly modernize the finance function through:

• Compliance monitoring: automated scanning of documents for compliance issues.

• Sentiment analysis: Understanding sentiment in employee or customer feedback.

• Audit optimization: Identifying relevant sections in large financial reports.

Optical Character Recognition (OCR) is a key technology that converts unstructured content, such as scanned documents, PDFs or handwritten notes, into structured, machine-readable data. Once converted, this data can be analyzed for pattern recognition, sentiment analysis or other relevant insights. This enables finance teams to automate various processes, for example:

• Invoice scanning: Automated extraction of data from invoices.
• Data extraction: Extraction of relevant information from contracts and financial reports.

OCR serves as a fundamental tool that supports the broader text analysis within Advanced Analytics. By converting unstructured data into a structured format, OCR enables the application of advanced analytics techniques.

WTS Advisory has already gained experience with OCR keyword search in the context of reading supplier invoices in various projects, improving the workflow and accuracy of invoice processing.   

Advanced analytics techniques are only as effective as the tools used to implement them. Whether it's the integration of multiple data sources or the in-depth analysis of transactional data, scalable tools that can handle large volumes of data play a critical role in providing clear insights in a timely manner.

Advanced Visualization uses complex data and presents it in clear, interactive formats that facilitate decision-making. In finance, these visualizations can be used to monitor KPIs and compare business results. Teams can use dashboards to monitor the real-time status of the closing process, identify bottlenecks and ensure on-time closing. Interactive charts and graphs make it easy to spot trends or variances, enabling timely corrective action and more informed financial reporting.

This includes creating models to simulate various scenarios and evaluate possible outcomes under different conditions. Simulations and scenario analyses provide added value, particularly in risk management, strategic planning and the development of target operating models. In particular, various variables such as the financial impact of different market conditions or the effects of regulatory changes on a company's profitability can be tested in this context.

Data mining is a broad, exploratory process that aims to discover hidden patterns, correlations and trends in large data sets. It can reveal both expected and unexpected relationships and help analysts to better understand the underlying structure of the data. An example: In credit risk management, data mining can be used to analyze the past behavior of borrowers and identify characteristics that correlate with loan repayment. By examining patterns such as income level, credit history and spending behavior, more accurate risk profiles can be created for potential borrowers.

Anomaly detection techniques help teams identify unusual patterns or outliers in data that could indicate errors, fraud or other significant events. By using anomaly detection, finance teams can promptly identify areas where workflows deviate from the norm and optimize their processes accordingly, prevent fraud or improve transaction accuracy. Techniques include clustering, statistical process control (SPC) and outlier detection algorithms.

Data integration combines data from different sources to provide a comprehensive overview, while data enrichment increases the value of this data by improving its quality. For example, integrating data from different sources provides holistic insights into workflows and process designs, helping to align processes and ensure consistency in reporting.

Real-time analyses process data as soon as it is available. This enables teams to react in real time to market changes, regulatory adjustments or operational problems.

To summarize, advanced analytics goes far beyond simply describing past events. It uses advanced techniques to enable predictions, targets and optimizations across large and complex data sets, often in real time. This enables companies and organizations to make more informed, strategic decisions - often automatically and with a higher level of accuracy and understanding.