Jacob Dillon’s article explained well many of the consumer relevant applications of the AI technology, but it overlooked several administrative applications of AI that go beyond fraud detection and AML pattern detection.
At a high level, AI technology is great at seeing patterns in data. For example, if I look at 1,000 bank statements, I know what information is relevant in these bank statements and where to find it. AI knows exactly where to look, too, but faster. Where AI provides additional value is both in the ability to structure the data to be easily digestible by a human reviewer, and by seeing patterns in the data that are impossible for a human to recognize.
Financial institutions have an exorbitant amount of information in their documents. Whether it be bank statements, loan applications, or credit card transactions, financial data provides a detailed profile of travel habits, diets, interests and the like. However, most financial institutions struggle to structure this data in a usable way.
Artificial intelligence enables lenders to extract information from these documents and structure it in a consumable format. Not only does this structuring of data reduce administrative time for the financial institution, it also reduces risk of manual error and maximizes the ability of the institution to generate detailed, accurate reports. Companies like Ocrulushave pioneered this technology to help financial institutions process documents with stunning accuracy.
The exciting result of structuring large amounts of data is that we can predict future scenarios based off of past trends. Past performance is an indicator of future results.
One of the earliest stories illustrating this type of insight is that couples start to buy more beer at the grocery store when the wife is expecting. That insight was generated from looking at the shopping history of millions of couples who bought diapers 6 months later.
Using AI, financial institutions can generate the same type of insights about loans that are likely to default, fees that are likely to cause attrition, customers who are shopping for a new financial product, and so forth. The insights from structured AI data help in everything from underwriting to sales for the back office of a financial institution.
AI provides a way for an institution to unlock more data and deeper insights, enabling them to provide faster and more accurate customer service and regulation compliance. Whether it is chatbots or construction draw processing, AI will greatly change both the front and back office of financial institutions over the next decade.
Will Mitchell is the co-founder and CEO of Contract Simply. As a former real estate developer, he oversaw $400M of construction loans while developing nearly 800 homes and millions of square feet of commercial real estate space. He writes as a thought leader on topics related PropTech, FinTech, and RegTech.
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