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Citi GPS: Global Perspectives & Solutions |
March 2018 |
Use Cases in Consumer Banking
AI implementation in consumer banking is an enabler of growth (via better targeted marketing) and efficiency improvement (higher volumes, lower risks). AI, particularly chatbots, is proving useful, with banks running pilots aimed at increasing automation and simplifying day-to-day transactions. AI is also finding use cases in real-time monitoring instances of fraud and cybersecurity.
Predictive analytics are being deployed in retail banking to study customer behavior and offer personalized products and investment advice. Several banks are embracing AI to target clients and offer personalized promotions. Many are piloting chatbot technologies or using voice biometrics to authenticate phone banking customers.
US Bancorp has enabled its customers to complete banking tasks, such as checking an account balance or making digital payments, by speaking a command to Amazon's voice-activated assistant, Alexa.
Figure 20. Artificial Intelligence Use Cases and Adoption in Consumer Banking
AI USE-CASES
Customer
Engagement
Operations
Risk & Compliance
•Target & personalize customer offers better, across channels
•Chatbots/ Digital agents for customer service & query support
•Secure Digital Identity with facial, voice & behavioral biometrics for smarter onboarding and servicing
•Automated spend and Investment advisory
•RPA for automating ledger reconciliations, automating tech support, IT automation etc.
•Detect fraud better, particularly for payments in real time
•Enhance Cybersecurity with ML techniques
Source: Citi Digital Strategy, Citi Research
MARKET EXAMPLES
DBS, Chase, RBS, BBVA, DB, Capital One
DBS, USAA, HSBC, BoA, CMB, Capital One
Barclays, Wells Fargo, HSBC, USAA, WestPac, CapitalOne
USAA, Capital One, Bank of America, Betterment, Wealthfront
WellsFargo, Chase, ICICI, Danske Bank, JP Morgan, Bank of America, DBS
Visa, Mastercard, Stripe, JP Morgan, Nordea Bank
CapitalOne, Barclays
TYPICAL VALUE BENEFITS
•2-3x+ better response rate
•20-30%+ revenue uplift
•Handle 1MM+ queries/ daily;
•Improve resolution time by 80%
•Reduce fraud by 70-80% and verification costs by 50-70%.
•Reduce costs by 80%+
•Increase clients/ advisor by 2X+
•Lower operating costs by 40%+
•Reduction in reconciliation time by 60-90%
•Reduce false positives in fraud by 60-80%
•Reduce time for detection by 30%+
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