By PYMNTS | September 14, 2018
PYMNTS examines the latest threats to digital banking platforms, and how FIs are looking to stop fraudsters in their trackers.
Connected devices’ popularization and widespread adoption have given businesses in all industries access to an abundance of behavioral insights. After all, more than 4 million connected devices produce more than 2.5 exabytes — equivalent to 2,500 kilobytes — of data per day, according to recently published research. That’s a greater amount of data generated over the past two years than ever before.
Banks and FIs can now tap into this data to learn about the services customers value most and how they can keep consumers happy. It gives them a deeper look into who their customers are, too, including where, when and how they typically interact with bank interfaces. The data further allows FIs to build personalized profiles based on customer habits, then use said profiles to authenticate and validate identities and transactions — which will only be more helpful to customers as personalization has become an expected experience.
Using data to build a profile
Customer profiling has become an essential asset of an FI’s security and authentication suite. Banks begin building profiles using internal data, like revenue generated by the customer, products and channels used most often and how quickly he or she responds to notifications. They then supplement this information with third-party data, which helps them understand how a customer interacts with other companies or organizations.
Financial firms can create a rich, full picture of a customer’s habits, both online and offline, in that customer profile. Profiles can then be analyzed and used to make tailored decisions, including which promotions to offer a customer, which products to push most heavily and how legitimate his or her transactions look.
These processes are typically automated, helping FIs more quickly identify suspicious transactions and often catching fraudsters in the act. Automation also allow consumers to enjoy a seamless experience while benefiting from strong security and authentication. In addition, consumers avoid frictions like security questions or long, complicated authentication checks because data is automatically collected and analyzed.
Analyzing and authenticating
Customer profiles can also be used to protect money. Each time a customer logs into an online or mobile bank account, for example, or attempts to complete a transaction, that action is compared to his or her profile. If the transaction falls outside typical habits, it is flagged for further authentication and evaluation.
More than 2.5 exabytes per day might sound like a colossal amount of data, but banks will likely have more of it coming their way before too long. Consumers are increasingly using connected devices to view their bank account balances, send money to friends and family via P2P apps like Zelle or Venmo and even apply for loans or other bank products — all of which becomes usable data. This additional data should allow FIs to build deeper consumer profiles and better understand their habits and preferences.
Stringent security and protection will be crucial for companies in the financial services space as FIs and their customers continue to conduct more business via online, mobile and other digital channels. Seventy-five percent of companies have been fraud victims in the past year, according to McKinsey and Company data, and 73 percent of financial professionals reported being targeted — a noticeable increase over previous levels.
It appears investing in developing and analyzing customer data and digital profiles may hold the most promise for firms looking to protect themselves against cybercriminals and improve efficiency in the banking space.
See More In: AI, authentication, big data, CA Technologies, Cybersecurity, data, FinTech, fraud, machine learning, News, Omni Security And Authentication Report, Open Banking, Security
FAQs
Using data to build a profile
How do banks profile customers? ›
The "Customer Profiling" subsystem is responsible for analysing the customers' banking-related interactions (e.g. monthly cash flows, loans, cards) and their legal information (e.g. demographics, employment, marital, financial and household information) for improving the decision-making process (Wangler et.
How do banks use customer data? ›
Banks can apply analytics to customer data such as income, credit history, and current debt levels to generate credits, which help them determine the risk associated with lending to a particular individual.
How are banks using customer data for personalized experiences? ›
Financial institutions are increasingly focused on new ways to interact with consumers and are now leveraging large swaths of data to do it. Technologies like cloud computing and open banking are already helping banks improve digital experiences and connecting client data to all parts of their business lines.
What are the three common fields from a customer database used by a bank? ›
Bank Fields
Identification: These fields are used to identify the bank and the account holder. Accounting: These fields are used to track the financial transactions associated with the account. Transaction: These fields are used to track the specific details of a transaction, such as the date, amount, and recipient.
What are the variables for customer profiling? ›
Find out more about the range of factors you should be calculating in order to launch targeted marketing initiatives that can help increase promotional ROI.
- Key customer profiling factors. ...
- Address. ...
- Age. ...
- Household income. ...
- Family status. ...
- Purchasing history. ...
- Attitudes. ...
- Combining all factors.
Market segmentation categorizes the broader market into different groups or segments based on shared characteristics. Customer profiling dives deeper, focusing on creating a more intricate, individualized picture of potential customers, reflecting specific preferences and behaviors.
How do banks use big data analytics? ›
Big data and statistical computing empower banks to detect potential fraud before it even occurs. Specialized algorithms track and analyze spending and behavioral patterns, allowing banks to identify individuals who may be at risk of committing fraud.
How is data used to improve customer experience? ›
Data impacts the customer experience by enabling businesses to understand customer behavior, preferences, and pain points. This knowledge leads to better-targeted marketing, improved products/services, and enhanced overall satisfaction.
How are banks improving customer experience? ›
Banks must invest in agile support software and CRM solutions that offer better customer visibility, make it easy to collaborate across sales and support teams, and give agents access to personalized context to offer appropriate services.
Most banks utilize “relational” DBMS for good reason. ACID stands for the four qualities any RDBMS prioritizes: * Atomicity: When several modifications are part of a single transaction, they all fail or all succeed; never a portion.
What is CRM data in banking? ›
Customer relationship management (CRM) is a necessity in any customer-focused industry. For banks, it's an especially useful tool for meeting sales and marketing goals and exceeding customer expectations. CRM software is a tailored solution that helps banks implement customer-centric strategies.
What are the top three types of analytics techniques widely used in banking? ›
Data analytics is crucial in various domains, including banking, by providing valuable insights. Moreover, understanding consumer behavior, predicting future performance, optimizing operations, and enhancing decision-making. The most common types of data analytics are descriptive, predictive, and prescriptive.
How do banks classify customers? ›
Some basic segmentation criteria include geography, income and spending habits.
How do banks verify customers? ›
Customer identity verification is the process banks use to confirm a customer's identity. This customer verification process ranges from traditional manual checks to modern, AI-driven solutions that make the process secure, fast, and straightforward.
What is a bank client profile? ›
Customer profiling allows businesses to understand the key demographics of their customer base, including age, gender, income levels and purchasing habits.
What does a customer profile look like? ›
A customer profile is a detailed description of your ideal customer. It provides demographic information, such as age, gender, income, education and location, as well as customer behaviors and interests.
