AI & the Finance Professional: Managing Business in Digital Revolution

The advent of Artificial Intelligence

Artificial Intelligence is quickly becoming a part of everyone’s lives, both in the consumer and business spaces.

It is widely being used in the consumer space in the form of:

• Digital Assistants such as Siri, Google Assistant and Alexa
• Streaming platforms such as Netflix and Spotify
• Navigating tool such as Google Maps

The business space has gradually begun observing increased adoption due to the following reasons:

• Open-source tools have become commonly available
• Businesses have started realizing the cost benefits due to AI

Many cutting-edge technologies have used AI to speed up data processing and refine the processes. AI is extensively being leveraged by finance and treasury departments for:

• Fraud detection
• Collections
• Cash forecasting
• Qualitative asset and management
• Business finance
• Expense reporting
• Credit scoring and direct lending

Benefits from AI

There are various benefits to reap from Artificial Intelligence such as:

• Driving better cash related decisions since most of them are data-driven
• Providing greater insights to execute informed decisions
• Freeing significant time and providing cost savings

To start your journey to implement AI and reap the benefits, you need to identify the areas where it can bring the most impact.

How to get started with your AI journey

Identify the areas where the technology can bring a big difference before implementing it, and determine which problems are truly worth tackling.

Things to do before implementation: 

• Input data for training algorithms and utilize appropriate models
• Process data through efficient analysis of historical data
• Make sure you get consistent outputs and refer to previous results

Learn that AI is not capable of the following things:

• Start showing results from the start of implementation: Since AI learns from data and evolves with time, it takes time to show results.
• Predict accurately with limited data: AI needs to be fed with quality data, to learn from it and refine forecasts.
• Works on one-size-fits-all algorithms: The frequency of data reporting, the types of processes and systems is important to be taken into account.

To begin with AI implementation, 4 questions need to be asked:

• If it’s worth it and brings long-term benefits, and if the output is useful to the business.
• If there is enough data to train it on.
• If it will evolve with changing business environments and adapt to the dynamics.
• If it will depend on a specific resource such as IT team or finance team or a vendor to update, maintain, and validate it.

Watch this webinar to learn more on how to get started with AI for your business type.