Presented by Envestnet
Personalization at scale is a key strategy for fintechs to deliver hyper-relevant products and services to meet customer demands. In this VB Spotlight, learn how top companies are using AI-enabled technology to deliver experiences that delight customers and build lasting relationships.
A wealth of data has long been available to fintech companies in the past, but the ability to process it quickly and structure it in useful ways has unlocked tremendous potential. Structured, tagged and enriched data has changed the game, taking product development and marketing to the next level of personalization and engagement.
“Being able to use and apply machine learning and AI logic on top of transactional data, and combining that with other experiences or information we know about a customer, has changed the way companies can relate to individual customers in a way they have yet to understand. never have been. sooner,” said Eric Jamison, head of D&A product — banking & tech product & design, Envestnet. “The ability to make better use of this data and target consumers based on that information is growing by the day.”
Banks are still using cookie sessions, email and banner campaigns because they have been effective in bringing in new customer signups in the past. But problems remain – the same product marketing campaigns appear to both current customers and potential leads, resulting in a waste of resources and the potential to annoy a customer who is tired of being forced to buy products they already have or not. apply to them.
But new technology doesn’t push those strategies out of the spotlight, they enhance them with data intelligence, making them much more targeted, personalized and effective. Data processing technology, combined with the ability to interpret it in more depth and detail than ever before, helps businesses identify opportunities, analyze consumer behavior patterns, and compare consumers across segments in ways not previously possible, improving campaign success rates .
Creating truly personalized experiences
Sure, FIs provide a business and a service, but companies that personalize experiences that are relevant, emotionally resonant, and genuinely helpful to consumers cut through the confusion. This is especially true for the generations now at the start of their careers or just entering the labor market. They have a more transactional view of their data and are actively seeking companies to better understand and interpret their personal information. Whether proactively seeking investment insights or generating alerts that draw attention to financial matters that need to be investigated, such as higher-than-normal spending.
“Being able to interpret that information and make it available to an individual in a very personal way endears those service providers, whether they be banks or technology or asset managers, to that customer,” says Jamison. “Clients will work with the financial services provider that seems to understand them best, and has gained the greatest insight from its own customer base.”
It’s about leveraging the information they have about their customers to become that primary source of financial management, he adds.
And when it comes to cutting through the noise, especially for a self-managing banking relationship or technology provider, it’s about bubbling up the most relevant issues that matter, bringing them to consumer attention and getting feedback. The relationship evolves as the technology learns what matters most to customers, tailors the experience to what the customer wants, but perhaps most importantly, uncovers new areas of potential interest, or needs the customer didn’t realize they had. had.
“One of the fears we’ve always had is that if you bombard a consumer with warnings, it can be overwhelming and they start ignoring them,” says Jamison. “However, relevant kinds of insights are really starting to engage the consumer.”
AI, machine learning and scale
AI’s ability to use and interpret standardized data powers the kinds of insights and information that power self-banking product experiences and advisor relationships. It can help advisors optimize portfolios and strategies for their clients, develop short- and long-term plans, and visualize scenarios to make timely, intelligent decisions.
Generative AI will take this scale even further, by driving the ability to take data from a variety of widely disparate sources, synthesize and process that information. But the human element will always be crucial in making sure these tools are properly tuned, from ensuring data is unbiased and as clean as possible, to fine-tuning algorithms and catching unavoidable AI model anomalies as an algorithm goes along.
“Our data scientists will need to make sure it’s focused on the right scenarios for us, aligned with the right kinds of experiences that we or our customers want to drive,” says Jamison. “For me, it’s only a matter of time before it starts to affect financial services.”
To learn more about the power of hyper-personalization at scale, a look under the hood of the AI powering the platforms used by financial services firms, and how to launch your own strategy, don’t miss this VB Spotlight!
- How fintechs are using personalization at scale to gain a competitive advantage
- Various AI-assisted technologies to securely collect, enrich and analyze financial data
- How advanced analytics and transactional data can provide valuable customer insights
- Ways to identify customer acquisition, cross-sell and upsell opportunities
- How to create personalized experiences that are relevant and emotionally ‘sticky’
- Bala ChandrasekharanVP Product Management, Chime
- David Goodgame, Chief Operating Officer, Tricolor
- Eric JamisonHead of D&A Product — Tech & Bank Product & Design, Envestnet
- Mark KolakowskiModerator, VentureBeat