Banks and financial institutions are looking for ways to innovate and solve the expanding pressure from multiple problems. One way to achieve these goals is to leverage the upcoming development in technology and automation, especially using Robotic Process Automation (RPA). When applied to KYC, RPA is fundamental for this change to accomplishing productivity via computerizing redundant, high-volume measures with numerous manual assignments and information assortment and subsequently permit employees to focus on other high-function tasks.
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Drivers requiring automation of KYC Process
A United States Government Accountability Office (GAO) study found that financial institutions spend between 0.4% and 2.4% of total operating expenses on anti-money laundering activity, while some of the largest banks in the study spent between 0.5% and 0.7%. According to Accenture Consulting, the costs of managing an AML program have increased by as much as 20.6% in 2020, and AML program violations ended 2020 with record fines. 2021 has been extremely active in dispensing AML violations.
Moreover, customers are suffering from the increased regulation in AML, which leads to a lengthy onboarding process. 24 days is the average customer onboarding time, where 30% of corporates reported onboarding >2 months. 9/10 customers said they did not have a good experience with their banks’ KYC processes and 13% have changed banks as a result.
Processes that RPA can be applied to
Setting up customer data
Robots can automatically scan customer’s information from documents and enter into the Customer Relationship Management system (CRM), which saves time, effort for employees and reduces errors.
Validating customer information
RPA can be used to perform validation of customer information (structured/unstructured) by accessing databases, extracting data from documents, collecting social media information, merging data from different places, and filling in forms.
Customer information gathering
This process is done both when customers are onboard and throughout the time they maintain as customers. There are multiple data and activities, such as creditworthiness, business/activities the customer is involved in, identity information, etc. needed to be collected. RPA robots can gather, input, and process these structured and unstructured data.
Compiling customer information
Customers have many different types of information spread across multiple services, e.g., savings account, brokerage. RPA bots can be used to compile customer information across these different systems, analyze and create a comprehensive view of customer data.
Customer screening
An integral part of KYC is to screen customers against government, internal, and external watch lists to identify any politically exposed personnel, negative/adverse news. This process can be automated by RPA as the bots can digitally verify customers’ information based on multiple databases and platforms.
Customer servicing
RPA enables banks to tend to customers’ requests faster with more accuracy, which improves customer experience. The bots can also navigate through large amounts of data, identify patterns, improve learning, and accelerate decision-making.
Applying RPA in KYC helps banks release both qualitative and quantitative benefits affecting the long-term success of financial institutions’ core banking processes and client relationships. Banks can expect to improve their employee, customer satisfaction, efficiency, productivity gains, quality, and compliance when adopting automation using RPA.
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