The use of AI has revolutionised financial reporting, shifting from traditional dashboards to conversational interfaces that enable real-time strategic action.
Traditional finance reporting relied on dashboards, which are visual interfaces that gather a business’s data into one central place.
Conversational AI builds on traditional dashboard usage as it acts as a personal assistant that can, through advanced data processing, pull out structured results, which are then converted into ‘conversational’ insights that can be implemented by a business.
This has many positive implications for financial reporting workflows, as it can lead to faster reporting and less dependency on technical teams.
Industries that have a large quantity of transactional data need ways of transferring this into reports so that they can then transform it into actionable KPIs. From this, they can make high-stakes decisions that will expand the business or improve the customer experience.
This occurs in a variety of different industries such as finance, e-commerce, and online gaming platforms, including UK casino operators. All these industries need structured financial reporting so they can make operational-level decisions.
Financial reporting is specifically complex because they have to process data from multiple different sources, ensuring accuracy across real-time and historical datasets.
This is why they have made use of dashboards that bring key business metrics into one place, including things such as revenue, profit margins, sales performance, and costs. This data can be displayed in an easily digestible format, such as graphs or charts.
They were used to give a snapshot of a finance business's performance, aiming to ask questions about what is currently happening in a business, such as whether revenue is down X%, etc.
Tableau, Power BI, and Qlik are all tools that contain dashboards that finance businesses could utilise to react to data. Since most dashboards were updated daily, weekly, or monthly, some of the decision-making could be reactive or based on historical data.
The advancement of AI technology has changed BI tools, adding a new level of insight into traditional reporting.
So, what is conversational AI, and how does it work? Conversational AI is the technology that enables humans to interact with data services using natural language, as if talking to another human.
In finance reporting, this means that businesses, instead of using dashboards to examine datasets, can simply ask questions to conversational AI and get real-time responses.
For example, company leaders can ask, “Why did our revenue drop in May?” which is an advancement on traditional dashboards, as they only serve to ask what is happening, not why something is happening.
The way it works is that the conversational AI will pull relevant data out of sources (such as Tableau, Power BI, and Qlik) and then analyse these results by identifying patterns or anomalies. It can then come up with a human-readable answer that is easy to understand and can be used to come up with a high-level strategy.
While traditional BI tools rely on humans to interpret the data, conversational AI will automatically analyse data for you and summarise any insights into plain language.