use this information to takeover victims’
accounts or create new bank accounts
in their name.
Account takeover fraud (ATO) and new
account fraud (NAF) saw a major spike
last year, increasing 119%. After the
2018 Marriott attack which saw 5.3
million unencrypted passport numbers
exposed, the hotel chain provided
victims with free identity theft monitoring
services, highlighting the threat PII can
pose if left in the wrong hands.
Despite the increase in identity fraud,
banks and financial institutions are
still relying on legacy methods of
identity verification, such as manual ID
verification and static credit agency data
checks which are putting customers at
risk. Once this data has been exposed,
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Issue 19
it’s near impossible to prevent it
spreading and using it to successfully
commit identity fraud becomes an easy
task for fraudsters.
Identity verification: Moving away
from legacy solutions
Given the serious implications
associated with identity fraud, banks
must keep pace with attackers and
adopt more modern ways to verify their
customers’ identities. But how do they
achieve this in a constantly shifting
cybersecurity landscape?
Legacy verification methods blended
with Artificial Intelligence and Machine
Learning techniques can offer banks
extensive, context-aware identity
verification. This includes a multitude
of checks, such as real-time account
checking, ID document capture,
biometric comparison verification (using
a ‘selfie’ to cross-reference with an ID)
and device geolocation.
This means organisations can analyse
in real-time an array of information from
several different data sources and digital
The days of tediously
visiting bank
locations to open
new accounts
are fading.
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