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Banking on Bots: The Move towards Digital Labor in Financial Services

Over the last two decades, banks and financial institutions have achieved significant efficiencies through outsourcing, offshoring and labor arbitrage. Those levers can only go so far, however, when it comes to further cutting costs and simultaneously growing revenues — particularly at a time when disintermediation is increasing and budgets are diminishing.

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Over the last two decades, banks and financial institutions have achieved significant efficiencies through outsourcing, offshoring and labor arbitrage. Those levers can only go so far, however, when it comes to further cutting costs and simultaneously growing revenues — particularly at a time when disintermediation is increasing and budgets are diminishing.

To address this, enter the “bots”: Financial services institutions including retail banks, investment banks, custodians, commercial banks and insurers are turning to digital labor, which represents a new wave of technologies such as robotics process automation (RPA) and cognitive automation. “Bots” are not the electromechanical robots with arms and legs one may have seen in sci-fi movies.  Instead, this refers to software configured to interact with computers and applications just like a human would, performing high-volume, repetitive processes and tasks.

Of course, automation is not a new notion — financial services have been automating processes for decades (think of ATMs, for example). But, the new wave of technologies are making it easier, quicker and cheaper to automate, says KPMG’s Managing Director in the Financial Services Consulting practice, Kiran Nagaraj, and that’s why bots are taking hold in the financial services industry. In addition, machine learning and cognitive capabilities have opened the door to automate even more processes such as goal-based wealth management planning, regulatory rule interpretation and determination of commercial loan risk rating. Processes such as these were previously not great candidates for automation. While many banks are in discovery and pilot phases, others have already moved to using larger numbers of bots to execute business processes — including those that keep the lights on. “The technology works and banks are starting to have more confidence in them,” he says.

In addition to the tantalizing prospect of using bots to cut costs by more than 50% in many instances, bots can also help manage risk, says Nagaraj, who points out that outsourcing never addressed risk management and in some cases, actually increased risk. Bots, on the other hand, can greatly reduce some risk — like the threat of anything that contributes to processing inaccuracies. “Human error goes away — there is simply better control with bots,” he says. 

How Banks Are Using Bots

It’s no exaggeration to say that nearly every major process in the world of financial services will present candidates for bots, from the front, middle and back-office to enterprise services such as finance, compliance, and risk management, across all business units including investment banking, wealth and asset management, retail and commercial banking and insurance.

At one bank, for example, bots are being used in trade settlement. According to an article in American Banker, the bank has programmed bots with rules that let them perform research on the orders, resolve discrepancies and clear the trades. While it takes a human five to ten minutes to reconcile a failed trade, the bot can do the same task in a quarter of a second.

Another popular candidate for bots is finance and accounting. For example the preparation of journal entries to post to the general ledger involves a great deal of manual work and reconciliation with multiple data sources, and could be easily automated by a bot, says Nagaraj. 

Risk management, a key process within Financial Services, also lends itself well to automation with activities such as risk reporting and controls testing already being automated at various banks. 

Even IT is a candidate — for instance, if you need a password for an app, you can send an email or text to a bot to give it to you rather than having to build a custom connector for use cases such as last mile provisioning.  “Across the board, there are tons of opportunities, but the key is in prioritization, which is a necessary first step that we are helping our clients with,” he says.

Challenges of Using Bots

There are several challenges for financial services companies getting into the business of bots, says Nagaraj. Here are the two key ones to keep in mind:

1.    It’s a whole new workforce model. Botsrequire an entirely new operating model to manage and operate your business, which organizations need to embrace and manage, he explains: “Who will maintain the robotics estate, how will freed up capacity be utilized, can you terminate or re-negotiate the outsourcing contract, what new skills does the workforce need — there is not always an easy answer.”

2.    “Bots gone wild.” No matter what, at the end of the day you can’t tell investors, auditors or regulators that a bot did something wrong, or a bot is why something bad happened. CIOs and CISOs need to think about governance, security and risk, says Nagaraj. “There are tangible actions you can take throughout the lifecycle – as you are planning the bot, building the bot, running the bot – to keep them from going ‘wild’”, he says. Using unique User IDs for each bot, encrypting communication channels and creating backup copies of critical bots are all examples of such tangible actions.

Succeeding with Bots

There are several steps an organization can take to successfully bring in digital labor: 

One, it should think about the end-to-end process before configuring individual bots. “One step of the process may need an RPA bot, another may need advanced data analytics and a third may need machine learning. There is a portfolio of technology options available and you don’t want to end up with a zoo. Considering the end-to-end process needs upfront will help”, he says. 

Two, organizations can help employees embrace these changes and emphasize it’s not just about cost-cutting and reducing headcount, but also about freeing up capacity to help the workforce focus on higher value issues and projects. 

Finally, on the IT side, CIOs also shouldn’t think about digital labor just in terms of cost cutting, he cautions. Instead, it should be embraced as a lever for cost avoidance and business enablement. “I’m working with a couple of clients using bots on new audit issues,” he says. In the traditional IT model, a technology solution with a drawn out implementation process would have been pursued. “But if a CIO actively brings robotics into the organization, it’s a new lever to pull. If the process is a good candidate for a bot, you can easily build one and use the savings to self-fund more bots or other transformation programs,” he explains.

 The Future of Bots in Financial Services

Bots will impact the entire financial services model of using offshore providers and outsourcing services — a significant shift from a longtime trend, says Nagaraj. “There will be wide-spread adoption. Companies might bring some operations back onshore. Outsourcing providers will get squeezed and they are already applying robotics themselves to stay relevant,” he explains. Also, regulators will have to determine how comfortable they are letting core processes and critical business operations run on bot farms, he adds:  “Ironically, increased regulatory spending is pushing banks towards this in the first place, but how much?”

Finally, the industry may see a coming age of self-learning robots that become smarter by looking at how underlying process and data changes can cause them to reconfigure themselves, and in turn become more resilient to business processes and technological change. As Nagaraj points out: “The technology continues to get better. Vendors are adding more and more features as many products look to move up the chain towards cognitive automation.”