Use Case: Expense Appraisal Automation

Automating Expense Appraisals With Cognitive Analytics

  • Inspirient’s probabilistic reasoning technology was employed to automate the expense appraisal process for a world-leading professional services firm
  • Through machine learning, Inspirient’s Artificial Intelligence (AI) learns to classify the most probable next action from both structured and unstructured data
  • The result was a significant reduction in operational costs and faster payment of expenses back to its employees
Automated expense appraisal process

Innovation and Benefits for the Customer

Each day, our customer – one of the largest professional service providers in the world – is helping their clients, ranging from start-ups to Fortune 500 companies, succeed at each step of their digital transformation journey allowing their clients to serve their own customers better, while optimizing their processes along the way. And, what puts our customer in the best position to advise on such topics – they practice what they preach!

However, the benefit is not only limited to a deeper understanding of how to digitalise businesses, but also a significant reduction of their operational costs and happier employees, since they now get expenses paid back to them much quicker.

Usage of Automated Analytics

The travel expense appraisal process is at the operational heart of any professional services firm. To put the importance of this process into perspective -- alone, each of the Big 4 professional services firms employ more than 200,000 employees, most of which are travelling on a daily basis to provide their clients with a personal on-site advisory service and they're submitting an overwhelming number of expenses every day. Any issues arising in this process will have detrimental effects on daily operations, and, because of the sheer volume of new expense reports being submitted daily, blockages in this process could very easily create an insurmountable backlog.

This is where the value of AI can shine – through machine learning, Inspirient’s AI can be trained to perform human-like activities, such as deciding the outcome of an expense claim from both structured data, e.g. the expense amount, and unstructured data, e.g. the description of and reason for an expense. In addition, to fully integrate automated decision-making with the current expense appraisal tool, Inspirient’s AI was combined with Robotic Process Automation (RPA), to extract and populate data from the tool, in order to realize a fully automated solution.

Conclusion

The presented case is an example of how Inspirient’s Artificial Intelligence can be used to automate data-centric processes that, currently, rely heavily on human decision-making, such as appraising expense claims. The two key benefits for our customer are reduced operational costs and nearly instant decisioning, freeing up resources for more value-generating activities.

Further reading

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