Trainer-IT

Dynamics 365 Finance now officially offers finance insights
AI in finance.
There has been a lot of talk about the prospects of AI, machine learning and robotization of processes in recent years, including in the financial sector. However, the discussions were not supported by concrete examples and explanations of how to apply these technologies in order to achieve better results and improve performance. Financial analytics allows you to predict cash flows and put forward intelligent budget proposals.
The outline of customer payment
Traditionally, companies have had a problem predicting when customers will pay bills. Lack of understanding breeds inaccurate cash flow forecasts. What would be the situation if companies could predict whether a customer would pay their bill on time or if they would delay payment?
Information about customer payments allows you to build forecasts by applying machine learning to financial data. This Dynamics 365 Finance functionality allows you to draw conclusions from already known customer payment data and analyze it for predictive purposes.
Information about customer payments very effectively changes the process of collecting and analyzing data. As a result, companies can make decisions based on predictions to automate tasks and track customers at risk.
Feature of forecasting the cash flow
For any business, cash flow is of great importance. Even companies with large profits can become insolvent if they fail to maintain the cash flow needed to fund operations. Cash flow forecasting allows companies to avoid adverse outcomes and manage their cash balances more effectively.
Cash flow forecasting allows for automatic integration with various external systems and reports. Machine learning allows you to make these predictions more accurately. This enables managers to make better decisions and optimize the company's capabilities.
Overall accuracy is improved when cash flow forecasting and time series forecasting are combined. You can also measure the effectiveness of forecasts by storing forecasts and comparing them with actual financial performance. This will allow more accurate forecasts to be made in the future.
Intelligent budget proposals
A large amount of time and resources are spent by organizations preparing the budget. Part of the time is spent cleaning up the historical data so it is possible to provide an accurate representation of the process history. The role of budget proposals is that they provide a streamlined mechanism for preparing a multi-year history, analyzing data, and changing over time.
What can be transformed
Financial analytics brings AI and automation functionality to Dynamics 365 Finance. These developments are a sensational breakthrough that is changing the perception of transactional finance. As you can see, this is achieved through the use of AI, Machine Learning and Intelligent Automation. It is the interconnected set of these tools that makes it possible to analyze payments and predict cash flows.
With these tools, financial institutions can make their business decisions much easier. Their ideas are based on clear data provided by AI. As a result, they will be able to increase operational efficiency through the use of intelligent automation. Microsoft is making these transformational opportunities available.

Article publication source:
https://cloudblogs.microsoft.com/

Dynamics 365 Customer Insights helps to enhance consent management.
When we talk about customer-owned data, confidentiality and compliance are first and foremost taken into account. In today's privacy-critical world, consent funnels are just as important as shopping sequences. Working to create a focused and personalized experience, customer consent for all processes, without exception, where data is used.
Dynamics 365 Customer Insights offers new consent features that can be considered by marketers and business analysts. Administrators have rights to connect and configure the use of rules. You don't need to write any code for this. The features described are available in preview in wave 2 of the 2021 release.
Segmentation and the rules of consent
Additional consent enablement capabilities enable Customer Insights to provide rich data management. Namely, their collection, unification, enrichment. Working with data begins in the self-service data preparation services in the Consent Center. Users can map the integrated consent data with the actions and rules of inclusion or exclusion. Then these rules can be used to control business processes.
Data analysts also have opportunities to capitalize on innovation. They will have the ability to include consent data for training and help improve the predictions and accuracy of machine learning models. For example, this will affect metrics such as customer churn and customer lifetime value (CLV).
Article publication source:
https://cloudblogs.microsoft.com/