Currently, the finance-securities industry is facing challenges such as a scarcity of high-quality resources, skyrocketing personnel costs, and increasing pressure to enhance efficiency and meet market demands. This creates an opportunity for applying process automation through Robots (Robotic Process Automation – RPA). RPA is a business process automation technology based on software robots. The ability of RPA to quickly and accurately perform simple and repetitive tasks helps increase efficiency and reduce costs for businesses. Surely, RPA will be a particularly important ally in the securities trading sector. In this article, we will explore the specific benefits that RPA brings to the securities industry.
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Automation’s Impact on Securities
Facing ever-increasing pressure from intense market competition, there is a noticeable trend: brokerage firms are striving to enhance their internal business operations through intelligent and digital transformation measures, aiming to establish more detailed management and bolster competitiveness.
In the securities industry, dealing with vast amounts of data is inevitable, including data on clients, transactions, and the market. Therefore, employees in brokerage firms must tackle the task of collecting and analyzing data daily with utmost accuracy.
A notable advantage of Robotic Process Automation (RPA) robots is their ability to handle data in repetitive processes without disruption. With easy deployment and low costs, they are becoming a crucial factor in the digital transformation journey of brokerage firms, promising significant efficiency and cost savings.
Advantages of Automation for Securities
1. Better Transaction Speed
RPA bots exhibit impressive capabilities in the realm of trade finance processing. They have the potential to significantly boost the number of concurrent transactions you can handle, thereby enabling your operations to scale without the need for a larger workforce.
Moreover, RPA can be seamlessly integrated into your existing workforce, enhancing their productivity and overall efficiency. This results in multiple advantages, including accelerated processing times, while simultaneously providing robust oversight of all transactions.
2. Faster Data Processing
Automation offers a powerful solution for managing unstructured data effectively, ensuring precise information tracking. These bots can extract data from various sources, including trade documents, application forms, and letters of credit.
They provide a versatile approach to accessing data from virtually limitless sources. Additionally, they deliver comprehensive process visibility, enabling you to monitor every facet of your trades with meticulous detail and receive real-time alerts.
3. Fraud Detection
IA algorithms can detect patterns of fraudulent behavior by analyzing transaction data and identifying anomalies. RPA can be used to automatically flag suspicious transactions for further investigation, helping to prevent financial losses.
4. Risk Management
IA can analyze large datasets to identify potential risks in securities portfolios, such as exposure to certain market sectors or concentration of assets. RPA can automate risk assessment processes, helping firms to respond quickly to changes in market conditions.
What specific cases are RPA, Automation, and IA used to?
1. Daily clearing
Everyday data clearance holds immense importance in the securities sector. Confronted with immense data loads, employees are tasked with data clearance duties across more than a dozen systems daily, subsequently engaging in a thorough review and validation process. This process is both tedious and repetitive, often consuming significant amounts of time. However, RPA facilitates the automation of the majority of these tasks, leaving human workers only to assess and authorize the results, resulting in substantial time savings for them.
2. Valuation
The valuation sector requires extremely repeated tasks from the appropriate workforce, such as data clearing against data files, product selection, button clicking to read data from the valuation system, cash transfers, etc. Additionally, the RPA robot is capable of simulating each stage of this process and gathering reports for human review and interpretation. In order to automate data-driven accounting and valuation, data processing can be done concurrently with valuation.
3. File Submission
Many business scenarios in the securities sector need a significant number of files to be submitted to regulatory bodies or made public, such as bond offers, legal opinions, bond application reports, and so on. These files may be several hundred pages lengthy and subject to complicated auditing standards. Manually reviewing the data might be time-consuming and error-prone. However, RPA robots can read the files in 5 minutes, compared to 5 hours for human laborers, and then send them to human workers for evaluation and approval.
4. Regulatory Compliance
Compliance with requirements like KYC (Know Your Customer) and AML (Anti-Money Laundering) necessitates extensive data analysis and reporting. RPA can automate data collecting and validation operations, while IA can discover suspicious trends or abnormalities in transactions, helping to assure compliance.
5. Trade Execution
Automated trading programs carry out purchase and sale instructions according to preset conditions, such as price shifts, trading volume, or various market signals. Robotic Process Automation (RPA) can automate regular trade executions, while Intelligent Automation (IA) can scrutinize market information to refine trading tactics.
6. Customer Service
Intelligent Automation (IA)-enabled chatbots can manage standard customer queries like checking account balances or transaction histories, allowing human agents to concentrate on more intricate matters. Robotic Process Automation (RPA) aids in the onboarding of new clients by automating verification and documentation procedures.
Wrap up
In conclusion, Robotic Process Automation (RPA) is increasingly popular among securities firms, banks, and financial institutions. Successful RPA implementation requires evaluating workflows and the feasibility of applying RPA to each department. RPA targets repetitive tasks, freeing up human resources for higher-value work. Collaboration between business and IT teams is essential. Looking ahead, integrating RPA with advanced technologies like IA can further enhance operational efficiency and decision-making. RPA not only offers immediate benefits but also serves as a foundation for ongoing digital transformation efforts in the securities industry.
Reference
Application of RPA in The Securities Industry
RPA in Financial Markets: Everything You Need to Know
Securities Services Get a Robot-Speed Boost
