Data Science

The Banking Industry Has a $1 Trillion Opportunity with AI

There are about 7.5 billion people on the planet, give or take a few. But that number pales in comparison to the number of connected devices worldwide. According to Autonomous, a financial research firm, people are outnumbered three-to-one by their smart computing devices — an estimated 22 billion in total. And the number of smart devices will continue to explode, with venture capital firms pouring $10 billion annually into AI-powered companies focusing on digitally-connected devices.

For financial institutions, their slice of this massive AI pie represents upwards of $1 trillion in projected cost savings. By 2030, traditional financial institutions can shave 22% in costs, says Autonomous in an 84-page report on AI in the financial industry. Here’s how they break down those cost savings:

  • Front Office – $490 billion in savings. Almost half of this ($199 billion) will come from reductions in the scale of retail branch networks, security, tellers, cashiers and other distribution staff.
  • Middle Office – $350 billion in savings. Just simply applying AI to compliance, KYC/AML, authentication and other forms of data processing will save banks and credit unions a staggering $217 billion.
  • Back Office – $200 billion in savings. $31 billion of this will be attributed to underwriting and collections systems.

These numbers align with what other analysts and research firms have forecast. Bain & Company has pegged the savings at around $1.1 trillion, while Accenture estimates that AI will add $1.2 trillion in value to the financial industry by 2035.

In the U.S. banking sector, 1.2 million employees have already been exposed to AI in the front-, middle- and back office, with almost three-quarters of workers in the front office using AI (even if they don’t know it). If you include the investment and insurance industry, there are 2.5 million U.S. financial services workers whose jobs are already being directly impacted by AI.

Use Cases for AI

Autonomous sees three primary ways in which artificial intelligence will transform the banking industry:

  1. AI technology companies such as Google and Amazon will add financial services skills to their smart home assistants, then leveraging this data+interface via relationships with traditional banking providers.
  2. Technology and finance firms merge/collaborate to build full psychographic profiles of consumers across social, commercial, personal and financial data (e.g., like Tencent coupling with Ant Financial in China).
  3. The crypto community builds decentralized, autonomous organizations using open source components with the goal of shifting power back to consumers.

AI-enabled devices are already using vision and sound to gather information even more accurately than humans, and the software continues to get more human-like.

“Not only can software understand the contents of inputs and categorize it as scale,” Autonomous explains, “it has exhibited the ability to generate new examples of those inputs. Artists are now as endangered as lawyers and bankers.”

But AI still has a way to go before a computer will become the next van Gogh or Pollock. Today’s AI is “narrow,” meaning that the machines are built to react to specific events and lack general reasoning capability. That said, there are plenty of practical applications for AI that banks and credit unions are taking advantage of today.

The most mature use cases are in chatbots in the front office, antifraud and risk and KYC/AML in the middle office, and credit underwriting in the back office.

Financial institutions can use AI to power conversational interfaces that integrate financial data and account actions with algorithm-powered automatic “agents” that can hold life-like conversations with consumers.

Bank of America has announced that it is aggressively rolling out Erica, its virtual assistant, to all of its 25 million mobile banking consumers. Using voice commands, texts or touch, BofA customers can instruct Erica to give account balances, transfer money between accounts, send money with Zelle, and schedule meetings with real representatives at financial centers.

Biometrics and workflow and compliance automation are other strong use cases for AI. To improve the consumer experience, AI can allow a bank or credit union to authenticate a mobile payment using a fingerprint or replace a numerical passcode with voice recognition.

In the middle office, AI can perform real-time regulatory checks for KYC/AML on all transactions rather than rely on more traditional methods of using batch processing to analyze only samples of consumers.

Perhaps the most promising application, says Autonomous, is using AI to incorporate social media, free text fields and even machine vision into the development of lending, investment and insurance products.

Read the source article at The Financial Brand.

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