The services sector around the world is shifting to digital engagement with clients. New marketplace platforms are appearing. From food delivery and vacation rentals to dating apps. People are taking advantage of managing their financial activities via mobile banking, saving time during online appointments at hospitals, and making a purchase in 3 clicks. All of these actions require personal data. Thus, the number of leaks, frauds, cybercrimes, and hackers attacks is increasing. The challenge for every company in every industry is to apply comprehensive fraud prevention techniques to protect their customers’ personal data.
In this article, Inoxoft’s expert dishes on how big data development & analytics services can secure your business from possible frauds.
Big Data Analytics in fraud detection
Fraud detection process with big data development & analytics services is a set of multidisciplinary techniques (machine learning, business intelligence, data mining, and AI) that can predict and prevent online scams. Companies in every industry can take advantage of technologies and apply advanced algorithms to detect suspicious behavior more effectively.
The reasons of digital frauds these days may be different:
● Payments moved online. More and more consumers are using eWallet applications, online marketplaces, and peer-to-peer payment platforms more often: from paying for service to splitting restaurant checks with friends. The more transactions taking place between a client and an unknown vendor, the higher is fraud risk.
● COVID-19 crisis caused chaos in a lot of industries. Thus hackers took advantage of the situation and committed fraud attacks. According to the Federal Trade Commission, Americans have lost $145 million to fraud related to COVID-19
● Today financial institutions offer their clients more and more online and mobile services. Banks are going digital: from transaction approvals to account onboarding online. As a result it became difficult to verify identities and caused a risk of fraud.
● Companies are moving to the public cloud and increasing IoT devices usage but don’t pay proper attention to security.
● Since the spring of 2020 the whole world started working remotely, and lots companies’ ve never returned to offices. Thus, a lot of employees started using personal devices to access corporate information.
● Home Wi-Fi networks can’t ensure the same level of cybersecurity as an office environment. But also, employees often neglect antivirus, use weak passwords,, apply dangerous online tools, etc.
Last but not least, fraud tactics have become more sophisticated. Fraudsters can more easily access personally identifiable information and use it against organizations and specific people.
Here are some examples. Fraudsters combine fake data with a real one to create synthetic identity that is almost impossible to detect. Then, they open bank accounts acting like a real person. Once they’ve established strong credit scores, the fraudsters ask for higher credit limits or larger loans and simply stop paying. Fraudsters can use passwords and credentials obtained via data breach and make fraudulent online purchases. These transactions can be as minor as buying groceries on a debit card or as severe as using someone else’s account to take out a mortgage. According to research, account takeover fraud will cause losses up to $200 billion before 2024.
Inoxoft provides big data development & analytics services extract valuable insights from data and apply top-notch solutions to secure your company from any vulnerability.
How Big Data Analytics can help you in fraud prevention
Business across industries taking advantage of detecting fraud with help of data analytics. Benefits of using are following:
Identify Patterns
Since traditional approaches can miss some important details, data analytics predict trends, identify new patterns, and suggest scenarios under which frauds can take place.
Data Integration
Fraud analytics can combine data from different sources and public records that can be integrated into a ML model.
Enhance traditional methods
Data analytics doesn’t replace the traditional approaches but instead strengthens bringing improved and more efficient results.
Value from unstructured data
Unstructured data is the place where most illegal scams take place. Fraud analytics help by reviewing it and gain the most insights to prevent any risks.
Best-fit approach
Big Data analytics technologies let your company try and establish best practices that will work for you in terms of detecting fraudulent activities
And also fraud prevention analytics can
● Handle enormous amounts of data at once when traditional approaches and humans can’t.
● Help determine the area that may be affected the most
● Identify what approaches are working for your company and what are not
● Fix weaknesses in the business flow.
● Automate the repetitive tests and decrease human errors
● Merge data from different systems
● Speed up analysis and eliminates manual work
● Predict and calculate the impact of possible fraud
● Automatically search for fraud indicators.
Methods of fraud monitoring analytics
Comprehensive fraud detection system requires using a combination of the following methods. Inoxoft often combines traditional and novel approaches.
Traditional fraud analytics methods are based on discrete analysis, structured data and human expertise. Specific algorithms detect suspicious actions and then reviewed manually by specialists. One of the disadvantages of such an approach is the rule-based algorithms that are based on manually set rules. What makes it almost impossible to detect unusual patterns and predict fraud.
With a global digital transformation machine learning algorithms and AI revolutionized fraud detection techniques. Big Data leverages and analyzes huge data sets to prevent security breaches. Here are a few modern methods that improve the efficiency of companies’ fraud detection processes:
● Ad-Hoc
● Sampling
● Competitive or Repetitive Analysis
● Natural Language Processing
● Connected analysis
● Advanced Behavioral and Cognitive Analytics
● Continuous analysis
Final Thoughts
Data is one of the most valuable integral parts of any business. Thus, every organization requires a high level of cybersecurity to protect not only their internal information but also their client’s personal data. From fraudulent activity Today it’s impossible without relying on modern fraud detection solutions and implementing comprehensive protection to minimize possible risks. Big Data Analytics is a useful tool that detects security risks and prevents them in a most efficient way.
Don’t underestimate the power of data-driven decisions that will secure your business.
