The rest of the financial services industry is now catching up with the adoption of RPA. The industry traditionally relied on outsourcing labor-intensive business processes to cheaper, overseas workforces. This model still works but it is exposed to risks such as wage increases and regulations regarding sending data overseas.
Robotic process automation has matured in recent years. RPA is now capable of keeping all financial services processes in-house. RPA can handle any repeatable process in retail banking, commercial lending, consumer lending, and wealth management. Furthermore, it yields a better return on investment than any international outsourcing solution. Used properly, RPA can speed up processes, clear bottlenecks and enable your team members to use their creativity and innovation for the benefit of your customers.
Retail banks invest resources into laborious back-office administration. Those resources could otherwise be used to improve the quality of the banks’ offerings.
During loan origination, both commercial and consumer lenders spend time and money on collating data from a wide array of disparate internal and external systems.
All financial services providers invest resources into verifying the identity of their customers, evaluating their suitability for financial products, and weighing the risks of doing business with them.
Employees can both intentionally and unintentionally misrepresent their working hours on timesheets. All types of organizations need to continuously monitor for inconsistencies to investigate further.
Financial services providers are required by law to provide regulators with reports of fraudulent transactions called suspicious activity reports (SARs). Conventionally, compliance offers of financial services providers compile these reports manually by referencing lengthy compliance documentation and extracting information from internal datasets. An RPA robot can now use natural language processing to comprehend the compliance documentation and extract the required information automatically.
Credit card companies and retail banks that issue credit cards are exposed to the risk of losing money when their customers’ credit card information is stolen. Credit card providers race to freeze affected accounts when retailers reveal that they suffered a data breach. Traditionally in these time-pressured situations, human support agents manually lookup and process the affected credit card accounts based on the information provided by the retailers. RPA can automate the freezing process, saving credit card providers from labor costs as well as the costs associated with reversing or absorbing fraudulent transactions.
Wealth management organizations frequently order trades of securities according to a predetermined set of rules or conditions. Humans have to place the trades manually because few trading software platforms support the level of custom automation needed. An RPA robot is capable of taking over the menial, repetitive task of ordering trades, freeing up more of wealth managers’ time to spend on client relations and strategic planning.
It is a common belief among executives that outsourcing to cheaper human labor overseas will cut costs in half. While hourly rates may be lower, executives don’t consider the hidden costs that come from factors like the loss of in-house business knowledge, the consequences of 3rd parties failing to deliver, wrong assumptions made from cultural misalignments, and uncontrollable management turnover.
Robotic process automation delivers clear-cut cost savings and returns on investment with none of the hidden costs above.
CIO, $6B+ Credit Union
Let robots handle the tedious and repetitive back-office financial services tasks so that your organization can invest more into new products and services.
Robots can relieve a bank’s back-office staff by automating administrative tasks such as the updating of customer information, reconciliation of transactions, and closure of accounts.
Robots can automate the checks required by law for commercial and consumer mortgage lending. Robots can fetch, collate, and analyze data from sources such as credit reports, tax returns, and employment history.
Optezo can train robots to perform identity checks, background screenings, financial fraud searches, and anti-money laundering checks in the same way that a human can, pulling data from multiple external sources.
Robots can automate the management of employee data, identify timesheet omissions and errors, and flag inconsistencies between employee scheduled hours and reported hours.
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