RBI has made mandatory to comply with the Bank Secrecy Act and should implement Anti-Money Laundering (AML) rules. The purpose of the AML rules are to help detect and report suspicious activities including the predicate offenses to money laundering such as securities fraud, market manipulation, etc. The latest technologies like Robotic Process Automation (RPA), machine learning, analytics and report generation for their AML compliance programs will help realize the efficiency and productivity gains and effectively reduce the cost of compliance.

More focus for financial organizations now is improving risk profiling and beginning to use AI to meet that problem while at the same time they are trying to optimize in order to close more and more fraud investigations to find out suspicious activities.

Advance technologies include analytics report, anomaly detection, network risk intelligence and machine learning which covers regulator investigation and internal risk management for the organizations. The activity which can perform in AML is AML compliance, AML transaction monitoring, trade surveillance, anti-fraud case management and operational risk, Investigation, Due Diligence, entity matching, suspicious activity detection tuning, etc.

With suspicious transactions report one can do detection and investigations of suspicious data. As a result, alert quality will increase, false positives will reduce. The data tuning, testing, acquisition of data and model deployment are fast and efficient so the organizations can ensure that they comply with risk management

According to Thomas Reuters’ know your customer survey the average financial firm spends US$60 million per year on KYC/AML, Customer due diligence (CDD), and client onboarding. RPA solution helps organizations to reduce the cost pressure by automating manual, high volume, repetitive, rule-based tasks.

Below are some of the use cases for Robotic Process Automation in Financial Services industry.

KYC/AML processes

Setting up customer data – The RPA can automate the process of Identifying and entering customer identification information in CRM.

Collecting Customer information - Bots can collect customer data at the time of on-boarding and regular updating of the data. Additionally, bot can collect customer information from the public database.

Validating existing customer information - RPA can validate customer information from different documents, from social media etc.

Compiling customer information - RPA can be used to compile customer data across disparate system to get the complete history of customer data.

Customer screening - RPA can verify customer information against standard database for existing or new customer

Customer servicing - Intelligent Bots are enabled to serve customer quickly which improves speed and accuracy. These bots navigates through large data, identify patterns and accelerates to make the decisions.

Regulatory monitoring and data collection - To keep an update of changing regulatory requirement is time consuming and complex task. RPA can use for getting the update more efficient manner.

Risk Assessments - To do the customer assessment need to collect customer information from different websites and internal database. This includes collecting data from regulatory bodies, government websites, FBI etc. Bots can collect data from these websites and also maintain the audit trail under due diligence.

Account closure processing - High risk customer account needs to be closed. RPA can be used to complete the process of account closure.

[Also Read: What is RPA in Banking and Finance ? Use Cases, Benefits, and Challenges in 2024]

As Financial Institutions continue to evolve their process to stay updated with the ever-changing AML landscape, digital transformation and automation should be a key part. Through RPA, we have seen organizations bringing down operational costs, maintaining quality and remaining compliant with rules. With proper RPA implementation roadmap and governance through the selection of processes that are well-suited for automation, financial institutions are realizing a major operational uplift from RPA in a relatively short amount of time. AutomationEdge being a major player in RPA solution provider has helped organizations like HDFC Life, ICICI Lombard, American Express, Yes Bank, Capital First in automating processes to improve quality with reduced costs.

Automating Deduplication Process in the Bank using AutomationEdge