Can AI Really Help Fight Financial Fraud
Advancements in technology led to these financial institutions implementing new software applications to process transactions. However, fintech solutions are still far away from completely protecting financial activities and preventing fraud. The use of AI tools can provide protection to payment gateways and initiate early detection of potential fraud.
Identification of Financial Fraud with AI
Financial fraud needs to be predicted and eliminated even before it becomes an actual threat. AI tools, through the application of machine learning and specific algorithms, can protect money transfer systems and monitor financial activities. In recent times, banks have transferred their processes to completely digitized systems and are relying on new forms of technology to prevent fraudulent activity. AI can identify financial fraud and prevent them from compromising the safety of banking services in the following ways:
- A network of stakeholders involved in financial services is analyzed. The analysis reveals variables that can be monitored to understand when fraud can be committed.
- AI tools can analyze specific words present in a financial transaction. This is known as “natural language processing”. The metrics received after analyses can be used to calculate the probability of it being a fraudulent transaction.
- If several frauds have occurred in the past, certain patterns can be observed. Establishment and analysis of these patterns cannot be done by manual processes as that would increase the chances of human error. AI can efficiently analyze these past frauds. The insights obtained from historical data on past frauds can be applied to real-time transactions. This makes it easier to accurately predict if these transactions can be fraudulent.
The accurate prediction of fraudulent financial transactions is based on analyzing patterns in data. Automated processes can do within a very short period and without any human intervention.
The application of AI allows banks and financial institutions to involve the usage of cyber security and compliance services. These services protect user information, availability of sensitive data, confidentiality, and integrity of the institutions. Cyber security compliance is enacted by regulatory authorities like a law firm or an industry group. Compliance is necessary to establish that the financial institution is investing in systems that are according to all security regulations. These services also protect the interests and assets of the bank in the event of a security breach of fraudulent transactions. Client information and banking days stay protected through AI security tools.
How can AI stop accounts payable fraud?
Accounts payable departments are often targeted by scammers because the protection for these is limited. When the payments are processed, the channels lack security making them vulnerable to third-party attacks and theft. According to a report by the Association of Certified Fraud Examiners (ACFE), most companies lose approximately 5% of total revenue due to accounts payable fraud. Such fraud can be of various types:
- Vendors Sending False Invoices
Most businesses work with numerous vendors to create and supply products. These purchases are part of everyday activities and after a while companies may choose to not conduct any further checks with the vendors or suppliers. Since these are routine payments, they are done through usual gateways that do not have multiple layers of security. However, this also increases the risk of fake vendors. These vendors create false invoices and if the company does not conduct regular inspections, it is very difficult to detect them. The fraud continues and is only identified after a significant amount has been lost.
- Overpayment
Often vendors take advantage of the lack of protection on accounts payable and bill for more items that are actually purchased. If the bills are processed manually, these additions are bound to go unnoticed. Companies unknowingly pay vendors more money and the fraud continues for quite some time. There may even be multiple copies of the same bill that are paid by different employees.
To avoid such fraud, human processes need to be eliminated. It is difficult for employees to process such large volumes of data without making a mistake. Once the errors add up, the fraud can be too extensive to recover from. To prevent accounts payable fraud, businesses need to invest in IT Automation with AI. Processing of all kinds of data is automated and machine learning is used to analyze and initiate responses. If the payments are automated, there is a minimum chance of any financial fraud going unnoticed.
Understanding AI Use Cases in Financial Security
AI can be used for the detection of anomalies in regular activities like financial transactions. It can also be used to develop security analytics that can predict future outcomes accurately. AI tools are capable of augmenting existing cyber security features. Several companies outsource security services. They use cyber security MDR services or Management Detection and Response to protect financial data and sensitive information. These services are able to monitor and assess threats to the entire organization.
There are companies that use technology other than AI for the analysis and prevention of financial fraud. But these software solutions are not as advanced as AI tools. With the use of security analytics and data automation, AI can find even minor threats. All threats are prioritized so that the immediate ones can be addressed first to eliminate chances of financial fraud. While AI is able to find more threats, it can also reduce false alerts. Financial institutions often spend a lot of resources trying to detect potential fraud that later turns out to be a false claim. With AI, such issues are resolved. Detection of fraud is quicker through machine learning. A combination of manual processes and technology can slow down the process of identification and elimination of threats. Implementation of AI solutions can detect potential fraud quicker and assign an appropriate response to it.
Conclusion
If elementary processes are used to protect financial institutions, then it will be very difficult to prevent the evolving forms of fraud. This is why AI automation and machine learning are necessary. Such technological solutions are capable of adapting and can modify existing methods of fraud detection depending on the security requirements of a particular bank or organization. Since no other method can predict fraud and adapt to the nature of the fraud, AI is essential for fighting financial fraud.
