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It’s easy to get caught up in all the excitement with artificial intelligence (AI) and lose sight of the reality of what it can deliver. This is because debate usually focuses on the ambitious uses of AI technology, rather than what it can effectively offer today.
It’s time for those in financial services to get smart with AI, which means not attempting to get AI to ‘do it all’ and instead leverage it to deliver efficiencies and value at low cost and with minimal risk.
What financial institutions need to understand is that it’s AI technologies, driven by machine reasoning, that are set to have the greatest impact on their business. It’s this technology which can improve data quality, the identity verification process and also deliver ‘informed’ decisions on the products and services offered to customers.
Semantic technology, a form of AI which has machine reasoning at its core; and has proven its worth in the pharmaceutical and healthcare sectors; is set to have the greatest impact on the financial services industry. Semantic technology, or semtech, associates words with meanings and recognises the relationships between them. It’s this approach which enables it to apply context and make inferences with data, which helps to deliver properly validated identities as well as broader data quality and integrity.
Semtech can identify possible fraudulent applications, in real-time, because of the machine reasoning and automated pattern recognition it provides. This enables those financial institutions who integrate this technology with their existing software platforms to deliver a seamless customer onboarding experience. Importantly, this ensures that those who use it are not only know your customer (KYC) and anti-money laundering (AML) compliant, but have a clear competitive advantage over those that don’t.
A further critical role of semantic technology is its ability to deliver for financial services companies of any size, in-depth intelligence on existing customers by making powerful, real-time connections between the data in their records. Using machine reasoning built into the technology it’s possible to combine the missing pieces of customer data to support an informed decision about whether to provide a product, for example, a loan to a customer. This is because machine reasoning helps fill in any gaps left by the customer as part of the application process or via other communications.
There are many advantages for those in financial services who use semantic technology. It delivers vital real-time decision making around ID verification, while addressing important issues in data quality and data completeness along the way; enabling a faster and improved customer onboarding process. Equally as important, financial institutions gain big picture visibility on their customer base to derive better understanding around which additional products and services customers may be interested in. Overall, errors are reduced and insights from the data are more sophisticated and quickly generated, freeing staff to focus on other important areas such as providing a standout customer experience and developing innovative new products.
AI offers real value for those in financial services who avoid all the hype around it and focus on where it can deliver maximum value. This means implementing machine learning semantic AI technology solutions that are proven to increase efficiency at low cost.
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