Data Enrichment turns raw data into valuable sources of information. Apart from providing more context, data enrichment leads to agile fraud management and more accurate risk assessment. The more enriched data your business has, the better will be your fraud prevention and detection decisions.
If estimates are to be believed, average losses to online frauds have increased by 88% globally, over the last decade. Frauds have become a massive industry and they are flourishing like never before. Globally, enterprises lose around $5.38 trillion to fraudulent activities, of which around $187 billion is lost only in the UK. To add to it, losses due to fraudulent activities are projected to rise to $10.5 trillion by 2025.
What is Data Enrichment and why is it essential for your business?
The terms data aggregation, data collection, data augmentation, data appending, data analytics and many more are mostly overlapping or tightly associated processes. While data aggregators, data selling companies, and fraud managers can understand them, it’s not so easy for business owners, who are not directly part of the data management and processing industry. Data enrichment is all about gathering additional information, authenticating it, and adding it to your database to make it more accurate and comprehensive.
Data sources used for collecting information in near real-time include search engine results, publications, social media, subscriptions, application logs, first-party company data, third-party records, and many more. The quality of sources plays a critical role, especially for companies who lack crucial data or are using inaccurate or outdated data, while:
- Looking to improve targeting
- Moving to a new market
- Starting a new business (like moving from brick-and-mortar to online)
- Trying to keep up with trends
- Trying to reduce customer friction by only collecting the essential info
- Reducing fraud rates
Detailed information ensured through data enrichment helps you protect your customers from unwanted risks and fraudulent transactions. Data enrichment techniques empower you to complete client profiles, without having to bother users or people needlessly for information available otherwise.
What is the Role of Data Enrichment in Fraud Detection and Prevention?
Data enrichment by data management experts improves risk-based decision-making. It helps entrepreneurs with efficient data enrichment schemes for fraud detection, to apprehend scams before they can run the course.
If data enrichment is comprehensive, you can verify a customer’s identity against the email ID or the IP address recorded in your internal database, and also check it against third-party data to find out if the ID was ever involved in a data breach or fraud. You can temporarily suspend critical services to the ID until thorough verification is done.
With data enrichment services becoming integral to fraud prevention solutions, their demand is on the rise, with the growing market size expected to hit $2.67 billion by 2027.
Common Types of Data Enrichment for Fraud Detection and Prevention
Fraudsters consistently are targeting customers’ data through deception, impersonation scams, sophisticated malware, and data breach attacks. Approaches may vary, but the consequences are costly. They arrive not just in terms of disruption and financial losses, but in terms of loss of reputation and business relations.
Here are some of the common types of customer data enrichment that help in detecting and preventing fraud.
Email Address Data Enrichment
With a mobile-first economy fueling fresh data in the markets, today every user has an email address. This simple data can reveal a lot when compared to external databases.
- Is the email address paid or free?
- Is the email ID single-use and disposable?
- Does the email ID belong to a registered domain?
- Has the email ID been actively involved in any data breaches?
- Is the email address used to register on social media platforms like Facebook, Instagram, Twitter, etc?
IP Address Data Enrichment
Apart from email addresses, the IP addresses of users can reveal a lot of information about the user – but only if they are tracked back to the source effectively.
- Where is the user based?
- Are the IP addresses connected through open ports to communicate with other servers?
- Is the IP address using any proxies, VPNs, or TORs?
- Is the IP listed on any spam blacklists?
- Does the IP belong to a data center or is it a residential connection?
BIN Number Data Enrichment
BIN (Bank Identification Numbers), aka IIN (Issuer Identification Numbers), is an example of enriching simple data points with help of external data.
- Is it a debit or credit card?
- Which bank issued the credit/debit card?
- What is the card issuing bank’s phone number?
- Is it an ATM only, Gold, Platinum, World Elite, or Infinite card?
Device Data Enrichment
Enrichment of device data is critical for organizations. The device a user uses to connect to sites or do fraud reveals a lot about the user.
- Which sites did the user connected to using the same device before?
- Does the user use the same device to connect to different sites?
- Is it running a virtual machine?
- What kind of browser is installed?
- Is it a mobile or desktop?
Businesses/Functions using Data Enrichment for Fraud Detection
- Retail: Ever wondered how Amazon suggests similar products to you? The data Amazon collects from you is simply on the page you are browsing; however, they enrich it with their voluminous database of customer purchases, which, in turn, recommends products for upselling or cross-selling. Amazon’s ability to collect and enrich product data at pace and scale helps them upsell and stay ahead of competitors.
- Financial Institutions: Data enrichment is pivotal in loan approval processes, account creation, and building credit scores. Banks and financiers leverage third-party data to create a complete profile of the customer they intend to lend money to – and reject potential default or fraudulent customers.
- Fraud Prevention: As mentioned above, a data point like an email address, IP address, etc. can be leveraged at the onboarding stage to create a profile of a user. It can be easily detected if it is connected to social media sites, if the domain given by a user as a website address is valid, how old the address is, etc. and all this helps to block fraudulent users.
- Insurance: Data enrichment works as a segmentation and targeting tool for insurance companies. They enrich a wide variety of datasets to categorize their customers and provide relevant insurance deals or products based on the risk related to the customer. Enriched data helps to detect and deal with high-risk profiles, lessening the risk of fraud.
- Sales & Marketing: Data enrichment helps marketing companies, and marketing divisions of enterprises, to know their audience better. Data aggregators collect cookies and enrich them to be leveraged by advertisers and third parties. It helps them to segment customers and target individuals with more relevant offers and advertisements.
Data Enrichment is gaining center stage
The pace of data generation and decay are making data enrichment crucial for data wrangling, data analysis, and every other data process. However, enriching data manually for short-term findings is no more feasible. The only way out is to enrich and turn data into insights with help of machine learning tools.
Combining data enrichment with machine learning has proved its worth in terms of identifying who your users are, making risk-based decisions, optimizing resources to fight against fraud, and outsmarting malicious activities that can dent your business brand. Moving forward, existing data enrichment modules will be improved, refining their algorithms, and expanding their sources. And continuous data enrichment for end-to-end fraud prevention will be the only safeguard for data-driven businesses and the chance of losing their competitive edge.