Prepared for nigel | Delivered October 22, 2019
AI + Human Banking Personalization
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To explore how AI/digitalization can be combined with a human element to make the banking experience more attuned to individual customer needs to inform the client’s continued research.
AI/Digitalization for Personalization in Banking
Across the financial services sector, many banking institutions utilize AI/digitalization as cost-savings
only, and have yet to develop more institution-wide uses for the technologies.
In fact, very few banking institutions (about
have actually considered consumer preferences when considering AI implementations, and only about
see the customer experience as the top priority in these types of implementations.
Research has proven that top-value customers at financial institutions “
AI-assisted interactions the most,” with experts recommending implementing AI across the customer spectrum to “
efficiencies and better satisfaction ratings,” as well as a higher ROI. They warn, however, that taking a fully-ROI-focused approach is the wrong way to go, and that prioritizing the customer experience is key to greatest success.
Deloitte’s research showed that, “
companies are recognizing that [AI] technologies are most effective when they complement humans, not replace them.
Experts at Technology Record note that “capturing customer needs and owning personalized
” can be key to “an AI-driven end-to-end customer journey” that’s “seamless, engaging, and frustration-
.” AI can be used to complement and encourage visits to bank branches at just the right time for each customer, which can lead to increased business for the bank. AI-powered facial
technologies can contribute to serving the right solution to the right customer at the right time.
Banks can benefit from AI-powered interactions in many ways,
: through chatbots and virtual assistants, which utilize natural language processing/generation and voice/facial recognition
; for profiling customers in order to present more-personalized options and interactions (through machine learning and behavior pattern analysis); for streamlining internal
, like having AI-powered back-up for laws and regulations, which could help determine which issues require human interaction; for spotting patterns utilizing machine learning to reduce
; as well as others.
of financial services institutions utilizing AI successfully include JPMorgan, which using AI-bots to execute trades and Morgan Stanley, which “has an AI fraud detection
Consumer Preferences in AI-Assisted Interactions
Multiple experts agree that financial services institutions that incorporate consumer preferences into their AI-implementations are most successful, as noted previously. Research into consumer preferences in these interactions show specific inclinations. Capgemini research showed that about
of consumers felt that “AI-assisted engagement gave
control over their interactions,” with the same percentage believing that the 24-hr/7-days-a-week availability of AI-bots offered great convenience.
The same study also found that more than half (
) of consumers prefer AI-bots to sound more like humans (than bots), and
liked it when they could hold “a sensible
” with a bot. Just over half of consumers (
) want their AI-bots to have personalities, and
of them want the bot to be able to display the quality of empathy.
Nearly three-quarters (
) of financial services consumers want to be made aware when they are dealing with an AI-bot, while only
of general consumers share this concern. Financial services consumers want complete transparency in their financial institutions, including with whom (or what) they are dealing during transactions, as well as how the data collected will be used.
Notably, with decisions of greater importance, consumers prefer a
level of human interaction (over AI-bot interaction). Also of interest, the younger the consumer, the greater the preference for AI-human-