“Machine learning” and “financial services” are not two concepts that obviously go together—after all, financial institutions, particularly credit unions, rely and pride themselves on established trust with their members that traditionally stems from rapport built over time with one-on-one communications. However, the fast-evolving digital landscape has heavily influenced customer expectations across all industries, including how they choose and interact with credit unions.
Meeting widespread, real-time customer expectations for personalized communications (without getting drowned in data) is infinitely more difficult in today’s complex digital age, especially considering that 81% of consumer financial institution research now begins online, according to a report by Digital Growth Institute. Luckily, machine learning is an efficient solution to help marketers meet these expectations and subsequently nurture the member journey while saving valuable resources and reaching members in new meaningful ways at scale.
Machine learning has transformed how marketers process and apply data to optimally engage their audiences with the right message at the right time, via the right channel. It is an application of technology under the overarching umbrella of artificial intelligence, made up of algorithms that improve as they are exposed to more data over time. In other words, the algorithms learn and gain better accuracy with more available information.
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