New Solution Allows Financial Institutions to Easily Switch RPA Tools

While still a relatively new development, Robotic Process Automation (RPA) is fast becoming the industry norm for banks, credit unions, and a host of others in the financial services sector to automate a wide range of repetitive, rules-based processes formerly handled by employees.

By successfully implementing RPA, these organizations have been able to significantly decrease the amount of time employees spend on manual tasks – and with it, the potential for human error – while simultaneously improving productivity, lowering costs, and enabling workers to focus on more meaningful tasks.

As a result, the financial industry is now well-positioned to capitalize on the next wave of automation enhancements, led by intelligent automation. Blending the rules-based automation capabilities of RPA with the cognitive capabilities offered by artificial intelligence (AI) and the learning capabilities of machine learning and natural language processing, intelligent automation enables end-to-end automation of complete business processes and orchestration of work across teams comprised of both humans and bots.

While automation and RPA will continue to radically change the financial services industry, banks, credit unions, and others are already capitalizing on a wide range of concrete benefits resulting from RPA adaptations. These include: 

A Focus on More Value-Added Activities – By freeing employees from routine, repetitive tasks, RPA has enabled them to focus on the real value humans bring to any business, namely creativity and problem solving. For banks and credit unions, this has helped to foster innovation and provide analytical insight as workers leverage their critical thinking skills to drive key business objectives forward.

Improved Fraud Detection – As organizations within the financial services industry actively embrace automation, it should come as no surprise that they are also investigating and adopting intelligent automation to strengthen fraud detection, quality, and accuracy. Deloitte, for example, details a use case where machine learning is used alongside databases that include the date, time, merchants, prices, etc., from credit card transactions to better predict when fraudulent transactions are made.

Automated Security – Given the number of security incidents that occur in the financial services sector – Verizon's Data Breach Investigations Report identified 1,509 such incidents and 448 confirmed data disclosures in 2020 alone – banks and credit unions are adopting RPA to strengthen data security and defend against the growing frequency of cyber-attacks and internal errors, leading to vulnerabilities. Automation has also proven to be invaluable in automating event management, reporting automated health checks and vulnerability testing, and security patch management.

Faster Customer Onboarding – The customer onboarding lifecycle historically has been a challenge for large financial services organizations. This is because a compliant and secure onboarding performed with due diligence demands significant time, manual effort, and resources. According to a Deloitte report, onboarding new customers for commercial banking clients typically takes between 20-90 days and incurs a maximum of $25,000 of revenue lost because of delays. The same study indicates that 89% of respondents claimed to have had poor onboarding experiences previously with their financial institutions.

To address this and reverse the trend of lost revenue, financial services companies have jumped headfirst to automate and transform the customer onboarding lifecycle to improve risk analysis and execution speed. Common onboarding processes automated with RPA include a range of both front-office and back-office tasks like KYC (know your customer) processes, customer information verification, legal and background checks for risk analysis, and both agreement and contract management.

Improved Compliance Handling – Major compliance operations in the financial service sector are rapidly being automated. These operations include customer due diligence, trade surveillance, risk analysis, variance tracking, and compliance audit analysis. To date, these automations have not only enhanced the output of these processes by removing the introduction of human error, but also made them quicker and more accurate.

Because regulations are also constantly evolving, however, RPA and automation in financial services can be extremely complex. Such changes produce new controls and policies that complicate the lives of compliance teams and must be adhered to in order to avoid penalties. As a result, each change that is introduced must be cross-referenced with all of the bots in production in order to identify what is impacted and where.

Fortunately, automation solutions now exist that deliver the ability to visualize change instantly. By connecting all of an institution’s automated processes to all dependencies (such as regulations), these solutions allow organizations to immediately zero in on....-->

While still a relatively new development, Robotic Process Automation (RPA) is fast becoming the industry norm for banks, credit unions, and a host of others in the financial services sector to automate a wide range of repetitive, rules-based processes formerly handled by employees.

By successfully implementing RPA, these organizations have been able to significantly decrease the amount of time employees spend on manual tasks – and with it, the potential for human error – while simultaneously improving productivity, lowering costs, and enabling workers to focus on more meaningful tasks.

As a result, the financial industry is now well-positioned to capitalize on...


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