AI-Driven Banking: Personalization and Fraud Prevention
Key Points
- IBM Operational Decision Manager Advanced leverages real‑time location and historical data to deliver personalized offers—such as a Broadway show recommendation—to customers during mobile‑banking interactions.
- Predictive analytics within the platform identify churn risk, prompting the bank to proactively send a dinner‑voucher incentive that enhances customer loyalty.
- By capturing events and maintaining contextual information, the system instantly flags a fraudulent ATM withdrawal in Los Angeles that conflicts with the customer’s recent New York activity, triggering an automated warning and card disablement.
- Automated, split‑second decision making reduces the need for manual fraud investigations, cutting operational costs while preserving a seamless customer experience.
- The combined personalization and fraud‑prevention capabilities improve customer satisfaction and drive increased revenue and reduced fraud‑related losses for the bank.
Full Transcript
# AI-Driven Banking: Personalization and Fraud Prevention **Source:** [https://www.youtube.com/watch?v=IManbRY97S4](https://www.youtube.com/watch?v=IManbRY97S4) **Duration:** 00:03:05 ## Summary - IBM Operational Decision Manager Advanced leverages real‑time location and historical data to deliver personalized offers—such as a Broadway show recommendation—to customers during mobile‑banking interactions. - Predictive analytics within the platform identify churn risk, prompting the bank to proactively send a dinner‑voucher incentive that enhances customer loyalty. - By capturing events and maintaining contextual information, the system instantly flags a fraudulent ATM withdrawal in Los Angeles that conflicts with the customer’s recent New York activity, triggering an automated warning and card disablement. - Automated, split‑second decision making reduces the need for manual fraud investigations, cutting operational costs while preserving a seamless customer experience. - The combined personalization and fraud‑prevention capabilities improve customer satisfaction and drive increased revenue and reduced fraud‑related losses for the bank. ## Sections - [00:00:00](https://www.youtube.com/watch?v=IManbRY97S4&t=0s) **Context‑Driven Banking Decisions** - The bank uses IBM Operational Decision Manager Advanced to analyze location, purchase history, and risk signals, delivering a personalized Broadway offer and dinner voucher to George while simultaneously detecting a fraudulent ATM withdrawal by correlating real‑time transaction data. ## Full Transcript
[Music]
banks can provide personal line services
and reduce fraud by gathering and
applying contacts to their operational
business decisions let's have a look
George and Sarah Smith decided to spend
the weekend in New York City on the way
to the hotel
George checks their account using the
bank's mobile app the app displays his
balance and features an offer for a
Broadway show behind the scenes IBM
operational decision manager advanced
was able to collect and analyze location
and historical data to choose an offer
that would best resonate with George and
Sarah it identified that George is in
New York he recently bought tickets for
another show and he hasn't received
similar offers recently at the same time
IBM operational decision manager
advanced recognized patterns based on
previous interactions and use predictive
analytics to identify that George is
potentially at risk of moving his
accounts from the bank in an attempt to
provide a better customer experience the
bank uses this insight to send him a
voucher for dinner for two at a nearby
restaurant in New York while George and
Sarah are at the show an identity thief
attempts to withdraw cash from an ATM in
Los Angeles using a copy of George's
card because the bank uses IBM
operational decision manager advanced to
capture events at the time of
interaction and maintain relevant
context they are able to correlate the
time and location of this transaction
against the time and location of
George's earlier balance check and
detect fraudulent activity a text
message warning of suspicious activity
and requesting review and validation is
automatically generated and sent to
George's mobile since George doesn't
respond the ATM warns that his card will
be disabled if he doesn't call within 10
minutes when the show is over
George turns his phone back on and
receives a text message from the bank
indicating that his card has indeed been
disabled this caused minimal disruption
as George was able to call the bank to
resolve the matter while still enjoying
dinner with his voucher
IBM operational decision manager
advanced dynamically monitors
transactions in real time gathering data
in motion at the time of interaction and
using that data to build and maintain
relevant context it leverages that
context and even allows the application
of predictive analytics to make the best
operational decision the bank then is
able to detect fraudulent activities
taking split-second systematic action to
initiate additional card validation
flagging George's account and disabling
the card
George has peace of mind and the bank
prevents costly manual resources to
investigate George is happy with his
bank's responsiveness personalization
and protection of his finances his bank
is happy with the enhanced capability to
increase customer loyalty to drive
revenue and SATA associated with fraud
[Music]