2021-09-14 | Jatin Patel
Banking operations can rapidly become complicated, time-consuming and costly when they need to hire extra staff just to keep up with the growth. However, some tools can help make a banking and finance company’s operations much easier.
Client Lifecycle Management or CLM is one such tool which is an analytical process that helps manage the banking clients’ lifecycles, encourage client retention and boost the bank’s profitability. CLM focuses on a complete chain of client transactions and is designed to generate easily-digestible results. While CRM helps preserve clients’ data, CLM helps preserve the client itself.
CLM covers the banking operations overseen by a Relationship Manager (RM), who interacts with various departments across the bank for the client if needed. It creates a 360-degree client lifecycle view by capturing data points to generate insights into client preferences at any point in time while associating with the bank.
Automation of Banking Operations
Customers engage with a bank across institutional banks. But siloed systems and lack of transparency can create gaps in customer servicing. However, clients expect an experience similar to global standards, so banks are trying their best to eliminate legacy systems and manual processes and bring in automation in their banking operations.
The banking sector, through automation, intends to streamline its processes. As a result, some banks are looking at a new generation of regtech (regulation technology) solutions as a silver bullet to ease the log-jam of data and processes. But regtech must be supported by proven technology that is part of a larger fintech strategy.
The main aim is to ensure that identification, client onboarding, and verification processes use end-to-end applications that allow picking up desired components and plugging in seamlessly into an existing CLM set up in the bank.
This is where Robotic Process Automation or RPA comes into play.
The RPA can be fully embedded in the CLM and KYC applications of fintech organisations to coordinate and automate how KYC and CLM processes work. The main aim is to activate multiple data sources and applications in such sequences that help augment the work to be done by the client onboarding team.
RPA captures data from legacy systems and collates it to form a single customer view across geographies and lines of banking business. Banks are turning to the robotic approach as part of a cybersecurity setup to reduce FTEs, cut down errors to zero and speed up the time needed to implement them as part of banking operations.
Automation within CLM and KYC applications enables the banking sector to intelligently optimise how the work is carried out by humans and robots. The use of a centralised and globally scalable end-to-end solution helps seamlessly infuse robotic automation within the banking operation for onboarding and KYC transformation.
Fintech organisations like banks and finance corporations can run tasks unattended, thereby ensuring that all extenuating risks are taken care of and that these meet all regulatory requirements as mandated by the government and regulatory authorities.
In addition, this automation helps banking and finance sector employees be more productive by freeing them from somewhat tiresome processes linked to KYC verification and focusing more on delivering better customer service.
Why NextGen CLM
NextGen CLM helps banks automate and scale up their banking operations and boost efficiency by providing a centralised view of all their banking activities across various accounts and countries.
In addition, NextGen CLM provides finance companies with a comprehensive and secure system that will help them acquire more customers and manage KYC requirements in compliance with banking regulations.
NextGen CLM has been developed by Areteans Technology Solutions, a provider of business services and solutions to help transform them and evolve digitally by executing Pega implementations. In addition, Areteans focuses on developing solutions that help clients proactively collaborate with customers.