AI, Robotics and Data Analytics Makes the Banking Industry Ripe for Change

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Data Analytics

by Karen Kesner

Artificial intelligence, robotics and big data are often talked about with reference to futuristic dystopian visions, but their near-term usefulness can be clearly seen in the banking sector. Banks are already preparing to take advantage of these complementary and overlapping technologies.

The rise of robotic process automation (RPA)has provided banks a way to automate repetitive clerical tasks such as requests for replacement credit cards or loan applications.

After they are trained, these systems can perform tasks in a fraction of the time, with greater accuracy and at much lower cost than would be the case with people involved, allowing banks to slash back-office function overheads. And of course, bots are already well established as ways to handle phone/website queries and service issues. 

Analytics complement this automation by delivering insights based on querying of vast data sets and using pattern detection to identify better ways of working, see where roadblocks occur and provide a software-driven way to detect fraud, avoid the risk of non-compliant activities and spot the next wave of opportunities. 

The savings on these operational costs needn’t equate with reduced headcount and the savings can often be passed on for human-driven innovation projects and more rewarding, differentiated tasks, often in the IT shops of these banks.

That is a game-changing advantage at a time of massive disruption in banking and financial services where incumbents are under threat from digital-native startups.

The issue is huge. A Capgemini report found that back-office employees spend about four-fifths of their time on manual tasks that are ripe for automation. Banks are leveraging RPA to achieve productivity gains of 35-50%, translating to return-on-investment paybacks in three to six months.

Cases AI

Banks are using machine learning to analyze mainframe operations, resulting in it optimizing code to save the time taken to process transactions. And, Bank of New York Mellon says it has achieved perfection with 100 per cent accuracy in account-closure validations, as well as 88% improvements in processing time and 66% improvement in trade-entry turnaround time.

Banks can also improve their customer relationships by tapping into the insights offered by AI and automation. For example, Royal Bank of Scotland uses their customers’ account transactional history and personal information to determine what products or services would be most useful to specific clients.

The bank uses analytics-based CRM software to deliver real-time recommendations to branch staff and call centres about how to best help individual customers.

Making technology a differentiator

Using technology better than rivals is central to success in banking today. CEO Lloyd Blankfein is known for his mantra that Goldman is a tech company. But analyze the staffing and IT spend of any bank and it’s clear that that is more than mere bluster.

Over a quarter of Goldman’s 34,000-plus employees are engineers and programmers; that’s more than the total number in many well-known Silicon Valley firms. And Goldman is at the forefront when it comes to financing technology startups, an activity that it helps it stay abreast of the latest trends and opportunities as well as netting the gains of successful IPOs.

It recently launched Marcus by Goldman Sachs to deliver personal financial services over digital channels.

Goldman’s old rival JP Morgan Chase & Co. takes much the same view, seeing itself as software-enabled, investing endlessly to replace manual processes with algorithms, recruiting extensively from the tech pool, investing in startups and recently launching COIN, a loan arrangements service that replaces lawyers and legal experts with bits and bytes.

This heavy-duty automation obviously saves costs but it also boosts quality as binary code doesn’t tire, have off-days, lose concentration or decide to switch jobs without passing on knowledge.

It’s hard to think of many banking operations that don’t stand to be improved with the triumvirate of AI, robots and data analytics and it’s a fair bet that the winners in the current turmoil in the banking sector will be those that have best taken advantage of IT. Maybe we can run a script to find out…