Identifying and mitigating the risk of fraud has become one of the prime concerns of most businesses, and understandably so. Fraud can create legal issues, financial problems and other unwanted consequences. Many companies are adopting emerging robotic process automation (RPA) technology to eliminate the chance of fraud ever occurring in the first place.
An effective RPA implementation can help businesses identify and resolve fraud cases in many different ways. Check out how you can use RPA for fraud prevention when you want to ensure that your business is secure.
1. Redesigning the Current Process
An RPA implementation requires companies to thoroughly understand, document and evaluate the current processes that present high cost-benefit potential and high financial risk. This evaluation helps businesses redesign their processes (with RPA) to avoid anyone manipulating data and concealing the fraudulent activity. Proper implementation of the RPA will enable companies to identify or better supervise the vulnerabilities in their business processes.
2. Speeding Fraud Investigations
Every investigator needs to access many data sources to begin a fraud investigation. The more time an investigation takes, the more difficult it will become to recover funds. RPA can be extremely efficient in pulling information to augment fraud cases. It gathers all necessary data in a faster manner, allowing investigators to spend more time resolving fraud cases and recovering funds. Thus, the RPA can speed up the investigation process without compromising the qualitative aspects.
3. Identifying Vulnerabilities
RPA bots can be automated to review current and previous financial transactions on a timely basis to identify uneven patterns that reveal illegal (often fraudulent) activities and piracy. Thus, the RPA assists business investigators and financial professionals in identifying vulnerabilities and preventing fraud within the business processes.
4. Minimizing Human Interactions
Fraud is a crime of opportunity, typically the result of human interaction to manipulate the data for improper gain. When you strategically integrate RPA into a well-designed process, it significantly diminishes interaction with the relevant data. Thus, the RPA shifts data processing to the review stage, in which humans have less ability to manipulate the information. By limiting human interaction, the RPA also reduces human errors in your business processes.
5. Examining for Anomalies
With the increase in speed and volume of financial transactions, it has become gradually more challenging to review transactions for irregularities. However, RPA can process high-volume transactions in a short amount of time. Accounts payable or receivable and payroll are examples of functions where you can implement RPA as a fraud detection tool. RPA can analyze business transactions for anomalies like policy and approval limits, contract amounts, payment schedules, bank account details and much more.
6. Automating Temporary Block and Removal
An RPA can set temporary blocks on accounts when suspicious activity requires immediate safeguards, while simultaneously informing the customers. You can use RPA in combination with artificial intelligence or expert rules to deal with breached accounts that might have no risk or very high risk. They can automatically initiate the block and reissue process in such situations. RPA can also identify temporarily blocked accounts, access their past activities and then remove the restrictions according to predefined criteria.
7. Updating Negative Lists from Websites
Banks may have files or watch lists, such as warning lists, blacklists or licensing information – that they use for fraud detection processes. You can use RPA to automatically scan for updates on these lists.
8. Reviewing High-Risk Accounts
The use of RPA can help during the high-risk account review process to pull in additional information like the customer’s prior transaction history. Using RPA, you can send updates to the appropriate internal stakeholders as well as to customers. You can create communication templates and extract data from the case management system to quickly review and communicate with the necessary parties.
9. Improving Investigative Results
The RPA can automate many of the investigation’s manual tasks, significantly improving outcomes. The RPA processes can gather the facts of the case so the investigator could save time on every fraud case analysis. Once RPA provides the data, the investigator can quickly review the fraud case to understand the events and identify the location of stolen funds, when applicable.
10. Implementing Compliance and Regulations
RPA is a good solution for compliance and implementing regulations. It can record all data actions in a log, even when data leaves the line-of-business application to a web portal or another third-party software or app. Every click and data entry log allows businesses more complete audit trails.
11. Encrypting the Information
RPA can help you secure your business processes vigilantly and tirelessly. It enforces business policies to reduce risk while notifying customers about unusual activity. It also provides you with data encryption to prevent unauthorized users from accessing and manipulating your sensitive information. RPA only allows people with specific login credentials to access confidential data in the system.
12. Enhancing Trade Monitoring
Most RPA bots are able to prevent copyright infringement by quickly monitoring suspected websites for your patents, trade secrets and other crucial data. In some cases, other companies might sell your products at a lower price. The RPA bots collect and aggregate pricing data to check if your offerings are being unethically sold online or below the set prices.
13. Integrating with Machine Learning
Integrating your RPA technology with machine learning algorithms enhances its cognitive abilities to decipher and report financial anomalies as fraudulent activities. This integration helps businesses gain better efficiencies in the fraud identification and prevention processes. The RPA bots that leverage machine learning not only can help companies solve complex fraud cases, but also come with self-learning capabilities to analyze newer patterns. Thus, this solution can provide explanations on alerts it detects, and will maintain audit logs.
Implementing RPA for fraud detection and solving fraud cases requires in-depth subject matter knowledge, expertise and rigorous monitoring. The better alternative is to hire the RPA implementation experts and let them assess automation opportunities for your business processes. Most successful RPA projects start with the right process design. Therefore, having skilled fraud management practitioners designing the process is a strong foundation for success.
