An incredible amount of data is available on the Internet, which increases second by second. For example, nowadays, smartphones have the same capacity to process data as NASA had when it sent the first man to the moon. The analysis and processing of such an amount of data, available almost immediately, create whole new possibilities for both existing and new processes.
Currently, the financial sector is one of the many beneficiaries of Big Data solutions, especially when it comes to fraud detection and prevention, with the help of powerful predictive models, minimized reaction time, and greater effectiveness.
Moreover, the big data platform also allows the financial sector to identify risks and opportunities with the help of emerging technologies to provide efficient and sustainable financial services.
What is Fraud?
Fraud is one of the most significant problems that arise with the advent of technology. It is more challenging to detect fraud when rules or laws are being violated in information systems and the banking world. This is why businesses around the world have begun to devote efforts to developing high-volume data analysis processes to understand complex processes and prevent criminal activities.
According to the World Economic Forum, fraud and financial crime is a trillion-dollar industry, and businesses spend trillions of dollars on anti-money laundering (AML) controls. As per the US Department of Treasury’s Financial Crimes Enforcement Network, businesses across the US lost more than US$1 billion each month because of financial frauds and cybercrimes.
Big Data in fraud investigation
Big Data is rapidly evolving. This set of techniques allows businesses to perform deep analysis on an incredibly complex and extensive set of different types of data. With the help of big data solutions, structured and unstructured data can be understood simultaneously and at high speed, even in real-time, without compromising the reliability of the analysis.
Various big data solutions are combined to perform complex analysis processes to deeply understand the data generated by the companies and their users. Whether it’s formal data belonging to study bases or third-party data of any kind, big data analysis helps anticipate actions before they happen in real-time.
Recent corruption scandals and fraud cases have forced authorities to apply robust big data solutions in their study process. They help authorities start legal processes with substantial evidence to take decisive action against businesses involved in money laundering or defrauding taxes.
One of the most notable cases of using big data solutions to uncover complicated corruption and money laundering plots is the case of the Panama Papers, where a renowned group of journalists had access to several terabytes of confidential information from a law firm. Many politicians, artists, soccer players, and famous personalities from all over the world were exposed thanks to these complex operations.
Big Data Analytics Offers Capabilities Such As:-
- A permanent monitoring of transactions: Big data solutions allow businesses to identify patterns based on the historical activity of a client or entity. In this manner, alarms are generated promptly in case of questionable actions.
- Monitoring of capital flows: This allows virtualizing funds circulation between a central entity and other relevant parties. It also includes detecting variations in the volume of funds that circulated between them.
- Transparency in the generation of reports for the authorities: By providing timely follow-up to all transactions and entities, businesses can show, with absolute clarity and precision, their monitoring tasks and the actions they perform in the face of a suspicious operation. Such a level of information also facilitates compliance with anti-money laundering.
- Generation of knowledge and best practices: With the help of necessary information, a business can also simulate money laundering scenarios, experiment with various action plans, and validate the effectiveness of hypothetical strategies. In addition, when faced with the risk of money laundering, businesses can make better decisions with an improved speed.
- Far-reaching risk management: Thanks to big data solutions, businesses can easily develop or import lists (based on risk or penalty criteria) to pinpoint individuals, companies, and jurisdictions that pose a high level of risk.
How to Choose the Big Data Solutions to Combat Fraud
The big data solution must integrate the following elements:
- Data Management: It allows businesses to address several data challenges, from big data processing to accessing and integrating legacy sources, all on a single platform.
- High-performance analytics and visualization: Big data platform allows businesses to quickly provide insights with an infrastructure that allows them to test hypotheses, ask questions, and simulate scenarios.
- Suspicious Activity Monitoring: Big data solutions allow businesses to automatically detect suspicious activities and generate alerts for events that do not comply with parameters and regulations using a robust and flexible scenario engine.
- Watch list: It helps identify high-risk individuals, businesses, or jurisdictions that pose a regulatory threat using fuzzy matching algorithms, smart scoring, and alert consolidation.
- Investigation and Alert Management: Big data solutions also provide business investigating agencies with a holistic view of work items and easy access to databases with the help of a web-based interface.
- Peer Anomaly Detection: It uses data analytics solutions to rapidly detect peer group anomalies by comparing an entity’s behavior to historical data.
- Search Tools: It includes reliable, scalable, and fault search capabilities that enable distributed indexing, duplication, queries, and automatic failover.
- Multipurpose: Offers an enhanced architecture that allows a single big data platform to serve multiple customers.
Benefits of Implementing Big Data Solutions in Business:
- They allow identifying irregular and unusual patterns, business issues, or risk areas where activities or processes could result in fraud.
- Helps save costs and maximize revenue.
- Detects various anomalies between several channels, comparing data from information sources to find discrepancies, such as social media networks, databases, call centers, etc.
- Predict suspicious activities before they cause damage to a business’s assets or merchandise.
- The Big Data platform also provides an internal view of the processes. It identifies where there is more opportunity to commit fraud, developing better-adapted strategies for business operations.
The advent of big data solutions, which are dynamic, changing, and mutating in their multidisciplinarity, allowed the advancement from static business rule systems to automatic but evolving feedback methodologies for fraud detection. Big data analytics can help businesses generate revenue by embarking on various projects or models that complement each other to attack the phenomenon from multiple fronts that allow businesses to detect and prevent fraud which helps in loss reduction and safeguard the business.