How Intelligent Technology Helps Banks Compete Against FinTechs

How Intelligent Technology Helps Banks Compete Against FinTechs

Making faster, better decisions in the onboarding process can help retail banks stay relevant

I still remember the day my mother took my brother and me to the bank to open our very first savings accounts. It was the first time I got to sign my name in an official capacity, and sure, the whole process took forever, but at the end of it, I got my very own blue passbook to take home.

A lot of things in the banking industry have changed over the years, but many of the underlying processes are the same. The question now is how can intelligent automation in the banking industry increase productivity and profitability while also increasing customer satisfaction.

Making Better Decisions, Faster: Intelligent Technologies And Client Onboarding

The new client’s goal is to open a new account, whereas the banking system’s goals are more complex: they need to collect and assess customer data for the purposes of risk management, fraud detection, and to provide the best client service.

There’s a four-step process for onboarding a new banking client which has been in place for a very long time:

  1. The potential client manually gathers documentation proving their identity, address, and income source(s); the bank’s agent then keys that information into the system.
  2. The provided data is verified against government databases and other sources.
  3. The bank’s agent assesses the risk of fraud or insolvency using mostly static, external data sources.
  4. Finally, the client is guided through the new account creation and any questions are answered (only during business hours, of course).

Historically, all this information is handled and processed by a bank employee, with the decision to accept the applicant as a bank customer requiring manual input, review and approval. The time spent engaged in this old-fashioned vetting and onboarding process means upstart FinTechs that can accept and onboard a new user in literal minutes have the competitive edge.

With the application of artificial intelligence and machine learning, traditional banks can increase the speed at which they can make these same decisions, without disrupting their already complex technology platforms and data reserves, which are subject to particularly stringent governmental oversight.

A wide range of technological capabilities can support the automation of a large portion of the onboarding process. Put the pieces together and the result is a seamless, modernized solution:

  • Artificial intelligence chatbots answer questions and initiate onboarding 24/7, saving manpower and ditching the “only during business hours” constraints.
  • Application programming interfaces (APIs) continuously share data between government databases and other sources and the bank.
  • Analytics and machine learning estimate and constantly update risk factors.
  • Computer vision and natural language processing enable intelligent processing of documents such as bills, contracts, and other paperwork.

Implementing intelligent automation in these ways reduces the onboarding process time by 90%, with a cost savings of 80%. The outcomes are entirely positive: customers report a better experience when automation is in place, and retail banks are better positioned to compete with FinTechs and better able to serve their customers.

Chatbots: Jamie’s Ready When You Are

ANZ Bank in New Zealand decided to pilot a fully automated digital banking assistant back in 2018. You cananytime, and she can solve most of your banking issues independently, answering common questions and creating work tickets as needed. While most chatbots can also do this, Jamie added the experience of speaking with another person by appearing human and – get this – performing sentiment analysis via webcam, too. For those who worry about automation losing that all-important personal touch, Jamie’s ability to sense and respond to your frustration may surpass the empathy you’d get from an actual human!

Jamie proved so popular during her initial pilot, she quickly became an integral part of ANZ Bank’s customer service strategy. She was a crucial tool in pivoting to meet customer needs during COVID-19 shutdowns, and an incredible example of leveraging automation to meet changing conditions with continued customer support.

No Job Losses Here

When Sumitomo Mitsui Banking Corporation (SMBC) implemented enterprise-wide intelligent automation, they successfully eliminated the equivalent of 800 full-time positions. The company could have simply laid off the associated workers and pocketed the savings.

But SMBC – like other companies recognizing the need to think out-of-the-box to stay “future fit” – opted, instead, for reskilling those employees. After skills assessments, workers were retrained and transferred to SMBC Value Creation, where intelligent automation expertise and methodologies are offered to other financial institutions seeking similar gains in productivity.

SMBC’s journey showcases a great example of how jobs will continue evolving and smart businesses will capitalize on their existing talent to meet new needs.

Banking Automation = Big Boons

When the business of banking incorporates intelligent automation, everyone wins. Goals are accomplished faster and at lower expense, and the entire business becomes more agile and creative. Customers experience better service, too. We’ve come a long way from that little blue passbook.

Want to know more about how cognitive automation helps accelerate decision-making across the enterprise? Start here.

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