Dynamic Data Streamlines Customer Experience, Fights Fraud in Digital Bankingby Fintech News Singapore July 17, 2023
As the digital economy continues to surge and expand, consumer expectations for fast, secure access to products and services seem never-ending.
Furthermore, when it comes to financial services, there is an entire generation of consumers cropping up who have barely stepped foot inside a brick-and-mortar bank.
In fact, in its Online Banking Market Outlook, Allied Market Research expects the online banking market to grow from US$11.43 billion in 2019 to US$31.81 billion by 2027, representing a compound annual growth rate (CAGR) of 13.6%.
To stay competitive in this explosive market, banks must not only meet the ever-growing demand for a seamless user experience at both onboarding and transaction, but they must also ensure their platforms are safe and trustworthy.
To meet both demands, banks must have an effective fraud management strategy in place, backed by a fraud management platform capable of streamlining and automating the account opening and transacting process.
Identity verification is key
A key component of truly effective fraud management in digital banking is customer identity verification.
Specifically, the right solution will answer the two very important questions of whether the transaction requestor is a real person and whether they are who they claim to be.
In order to answer these questions, it is important that banks have the tools and technology required to uncover the person behind the request by linking their digital identity back to them.
Assessing fraud risk and streamlining processes with dynamic data
According to Ekata, a Mastercard company providing digital identity verification solutions for businesses worldwide, nothing is more fundamental to an organisation in this digital economy than its data.
Specifically, how it is used to improve business; in this instance, how the right complementary data adds context and drives differentiation by enabling banks to create stronger machine learning models for the purpose of identity verification and fraud prevention.
In the recent e-book “Achieving effective fraud management in digital banking”, Ekata details the workflow of a best-in-class identity verification solution that examine data using two key analytic methods to make a probabilistic assessment of fraud risk.
For example, to appropriately validate an identity and assess fraud risk, the solution needs to be able to examine how the dynamic identity data elements of email, address, phone number and IP address are linked to an identity – and for how long.
Specifically, the right identity verification solution– fueled by unique, global, third-party data sets – should be able to accurately answer the questions of whether an email belongs to the customer and when it was first seen in a digital interaction.
In turn, the solution should present a risk score determined via the answers to the above questions. Following this, the bank can then confidently make an informed decision regarding the appropriate workflow of each application or transaction.
For example, should the data determine an identity has a high-risk score, extra friction, including manual review is necessary. Meanwhile, a low-risk score means this consumer can enjoy a streamlined, friction-free onboarding or transaction.
To learn more about how the Ekata Identity Engine is helping banks worldwide scale up their online offerings to meet the demands of the digital banking market while ensuring a frictionless yet secure customer experience, read their latest report.