5 uses for RPA in financial services

RPA in financial services

Why should RPA be used in finance?

In the world of finance, even small errors can cause significant results. You need only look to Santandar, who paid out £130 million on Christmas Day 2021 in error due to a scheduling issue that resulted in roughly 75,000 accounts being paid a second time from the bank’s own reserves.

Robotic process automation (RPA) can be a powerful asset for automating repetitive tasks, meaning it seems perfectly suited for the financial industry – it’s estimated that there are over 1 billion purchase transactions around the world every day, all relying on technology infrastructure to do two essential tasks – transfer money and, most importantly, do it quickly. How, then, can RPA help financial institutions?

Use #1: Achieve growth without compromising older systems

Financial companies are often long-established and have made many changes in their systems over time. In some cases, these systems have become monolithic and are essential to the mission critical operations of the organisation. Downtime of these systems, either planned or unplanned, risks consumer irritation and can detrimentally impact confidence in an institutional brand. Due to the often global customer base that relies on these systems, financial companies can feel torn between growing their capabilities and putting older code/functionality at risk, which has given rise to leaner, challenger banks who have dominated consumer score tables in recent years.

RPA offers a tactical solution for introducing the benefits of a modernisation programme, whilst maintaining the core systems and architecture that the organisation runs on. In the absence of APIs or clean, back end processes, bots can perform tedious and repetitive tasks on the front end of existing internal systems. This allows the organisation to achieve KPIs previously thought to be years away in a fraction of the time, whilst providing IT teams with the necessary breathing room to continue with modernisation with reduced risk and time sensitive pressures.

Use #2: Maintain regulatory compliance

Another byproduct of the size of many financial companies is the volume of regulations and guidelines they must remain compliant with to continue operating in their many international markets. Compliance is a notoriously laborious task, though essential to business operations and requires analysis free of bias, making it a prime candidate for automation.

Advanced logging can also be applied to an automated process to confirm with, or expand on the required audit trail, by introducing business-readable checkpoints through email, scheduled reports, or long-term achieved robot activity logs which can be made accessible at any time should an audit be required. Bots will not deviate from programmatic tasks, nor will they make mistakes (assuming they have been programmed to a high-quality). As such, you can be confident that your automated workforce is diligently working away to ensure processes remain accurate, compliant and auditable within specified timeframes.

Use #3: Increased efficiency

Automation can be a great tool for removing inefficiencies in people’s workflows – this can have a massive impact in the world of finance as companies regularly have many departments and carry large headcounts.

Utilising attended automation, regular tasks such as running audits and system reports can be carried out by a bot overseen by a small number of human supervisors. Staff time can therefore be redeployed and remove inefficient workflows. This means everyone from senior staff to more junior team members can focus on higher value tasks where automation would be unsuitable or a human touch is required.

Use #4: Burst capability

A significant advantage to investing in an automated workforce is the comparatively low cost for each hour of productivity. For example, assuming 24/7 utilisation, an unattended robot licence available from UiPath has an operational runtime cost of around $1.17 USD per hour.

A properly-configured automated workforce would not be restricted to any specific task or function. Instead, bots can operate across an organisation, focusing on tasks according to a multitude of specified business logic such as job priority, SLA or specified completion time targets. This allows the organisation to automatically reallocate and scale its resources according to the greatest need of the business at short notice, with no additional training requirements or configuration necessary, whilst de-prioritising tasks with a lower importance until the burst capability is no longer required.

Use #5: Improved customer experience

Many financial companies already have two features in place to carry out the bulk of their customer service work: call centres and chatbots. However, there is great potential for RPA to improve how these two functions work.

Consider the volume of customer requests that require quite rudimentary actions:

  • Checking account contact information is correct
  • Checking account balances
  • Resetting account passwords or PINs

RPA can be used to improve chatbot functionality and allow customers to complete a greater number of tasks by themselves and with 24/7 access. As mentioned previously, human supervisors are still needed for issue resolution and to complete more sophisticated tasks that cannot be completed by an automated process. However, RPA can monitor call centre conversations and populate pages with information to speed up tasks that require a supervisor.

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