Article
Intuit AI, Knowledge Engineering Help Power Aid Assist
Principal Product Manager Yi Ng talks about Intuit's use of machine learning and natural language processing in its new Aid Assist tool.
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Use AI and emerging tech to solve the biggest financial challenges for 50 million customers
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Helping our self-employed customers save money with Machine Learning
ExpenseFinder is a feature that automatically pulls a year's worth of bank transactions and automatically finds deductible business expenses through our machine learning algorithm. On average, users find $4,300 average in business expenses.
Making small business accounting easier with Conversational UI
QuickBooks Assistant is a chatbot that combines data-driven insights and natural language processing to ease business operations by merely asking questions or stating requests, using a smartphone. The service understands intent and identifies context to uncover numerous financial data points – from tax obligations to expense tracking, cash flow, profitability and more.
Leveraging Natural Language Processing to power sentiment analysis
We created a natural language processing system to analyze the sentiment in a customer’s speech and text, identifying different emotions and then flagging those emotions to a customer care agent so that the care agent can respond to the customer appropriate to the customer’s emotional state.
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Reducing the time it takes to file taxes with Knowlege Engineering
We receive about 30M returns every year, each containing a very rich set of data points about demographic, economic and social trends that characterize our customers’ financial lives. By leveraging machine learning and combining it with the representation of the entire Tax Code, we are helping to reduce the time it takes to file taxes and increase a user’s confidence in accurately filing their taxes.
Using ML to answer customer questions efficiently
To connect customers to the right agent to meet their needs, we're using a data-driven pipeline to map the customer profile and question to an appropriate customer care agent. Using a machine learning algorithm trained with historical interactions between customers and agents, we've increased expert and customer sentiment, as well as material cost savings and efficiency improvements.
Eliminating manual data entry with Information Extraction
Using a shallow neural network with optical character recognition and image processing, we are able to perform automatic information extraction from document images, eliminating manual data entry and security issues in repetitive, manual data handling. This technology allows you to snap a photo of your W-2 or tax forms, and extract individual data field and upload the data automatically to TurboTax.
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