Understanding the Path to Purchase in Financial Services Through Deep Learning
Authored by: Lisa Toth, Global Head of Regulation and Risk at Hatstand, a Synechron Company
All purchase decisions go through a myriad number of steps before we pull the trigger to buy. Depending on the purchase, these steps may be done so quickly that they do not even register in our conscious mind. For larger and more complex purchases, like homes, durable goods, insurance or financial products like investments, wealth management, credit cards, and loans, we will typically go through a web-based research process to find the right product or service to meet our needs.
The steps that an individual goes through in this process are typically the same across all consumers for a specific product or service and map the journey to conversion as a client. Intercepting and influencing the potential client along the way to guide them towards your products or services is where machine learning can come into play in a very effective manner.
Machine learning is a type of Artificial Intelligence that provides computers the ability to learn without being explicitly programmed. Deep learning is a sophisticated form of machine learning that is exceptional at learning patterns by deploying algorithms to derive meaning out of data by creating self-assembling collections. Joining this computing power with internal product and client data and supplementing it with an external behavioral data base provide firms with all the data needed to chart the purchase journey and impact the outcome.