Artificial intelligence (AI) is at the core of the digital transformation that is set to redefine the financial services industry.
It will no doubt cut jobs, but AI has the potential to catalyze further growth.
Every new report on artificial intelligence (AI) released into the market paints the same picture: the financial services sector is ripe for a lot more automation. Already robotics process automation (RPA) has seen leading banks and financial services institutions implement automated processes that have cut costs, enhanced customer experience, and improved overall efficiency as resources go to value-adding functions.
Other than that, greater automation is what institutions are looking out for as they seek better regulatory compliance as well as developing a competitive edge over business rivals. Now we see more and more fintech leaders invest in automation products set to transform operations and functions as we know them.
Several technologies in AI, RPA, and machine learning (ML) are all deployment-ready. However, what is not so easy is how to identify where to start or what services to automate. Large banks and leading fintech firms may have an edge, but for small institutions, the first in line for automation should be any repetitive processes that can be handled without direct human labor.
Here are the top 5 financial services processes ready for automation:
- Anti-money-laundering analysis
- Know Your Customer (KYC) processes
- Claims processing
- Quote generation
- Back-office tasks
1. Anti-money-laundering analysis
Banks spend huge amounts of money on anti-money laundering (AML) processes, with hundreds of analysts doing the AML checks. The huge staff expends billions of dollars yearly dealing with post-transaction investigations.
But one thing automation can improve significantly is the time to spend pooling data from different sources. With automation data, collation and case investigations will take less time, cost less, and generally be less dreary for workers.
2. Know Your Customer (KYC) processes
KYC is another financial service process ready for automation. Know your customer employees have to carry out tiring checks, often looking into multiple databases. It takes a huge team and money to have an effective KYC process. Artificial intelligence and robotics process automation make it easier, with the focus shifted from large teams and huge costs that arise from these often repetitive processes.
Automation provides for use of multi-skilled virtual workers, which banks can look to speed up KYC as well as reduce costs. Automation also allows virtual workers to operate within set rules. Here the system can flag any sensitive or bizarre-looking cases for review by analysts. Like in AML checks, virtual workers can handle KYC checks even during holidays or out-of-office hours.
3. Claims processing
Insurers currently employ huge teams to handle claims review and processing. Challenges like having so many claims to review at a go often prove tiring to workers. This, typically, affects the subjective processing of claims.
Automation not only drastically increases the total number of claims processed, but also allows for the highest levels of detecting potential fraud. If a company automates its data extraction then speed and accuracy increase manifold.
4. Quote generation
I have interacted with many people who said they could not complete a form-filling process for one or the other quote generation. One drawback of the process is the time and effort needed, which some customers don’t fancy and which ends in lost sales for businesses.
Automating software that uses machine learning to process documents solves this problem. Customers simply submit their current policy documents and the inbuilt tech extracts the unstructured data. It sorts the information and processes the relevant quote, noting differences in pricing to offer quotes according to customer needs.
5. Back-office tasks
Automation isn’t only meant for processes aimed at regulatory compliance or customer experience. Automated systems allow for use of process-agnostic virtual workers, which means virtual workers within a system can handle various back-office tasks. This essentially removes the burden of too much work across systems, an aspect that can boost a company workforce and contribute to productivity.
For example, software bots can look into operations like data re-entry, sending emails, downloading files, financial reconciliations, client account management, statement generation, trade reconciliation, employee on-boarding, and data reporting among many others.
Automation is allowing companies to optimize operations that have so far solely relied on manual human input. The result is more cost and time-saving, aspects helpful to both the institutions and their clients. According to analysts, AI implementation has the potential to cut global financial sector operation costs by 20-40 percent by 2030.