Banking's AI Leap

The pandemic jolted the financial industry into recognizing the growing need for artificial intelligence and big data transformation. The next chapter in the story? Embracing opportunities opened up by the AI leap

When Covid-19 reached the US, lifelines that millions of families had long taken for granted risked being cut. Access to everyday services was compromised, from doctors to grocers – and banks.

Can I access my pension? Are my assets safe? Do I need to refinance my debt? Such questions became urgent, even scary, and authorities had to act quickly to support citizens in need, with emergency loans to small businesses and other financial aid.

As people endured eight-hour call center waits — only then to hear the line go dead — bureaucrats struggled to figure out who was eligible for loans or debt relief.

It was a watershed moment, propelling artificial intelligence and data analytics to the forefront of the financial industry (FI). The urgent need spurred banks to adopt AI for a radical capacity upgrade in everything from customer support and regulatory compliance to fraud detection, credit underwriting and more.

“Covid brought a critical speed dimension and uncertainty dimension,” says Michael Goodman, vice-president of business insights at NTT DATA. “The pandemic accelerated FI adoption of AI and data-driven solutions by several years.”

AI’s reach goes beyond financial fire-fighting. Covid-19 has highlighted its ability to boost revenues, acquire customers and drive business models based on the new paradigm of the Digital Business Platform (DBP) — product ecosystems that smash traditional, vertically integrated banking structures.

NTT leverages world-class R&D and big data resources to build tailor-made AI solutions for FI players. Niraj Singhal, NTT DATA vice-president and head of international banking practice, calls it “a business-first approach” that identifies the client roadmap — before building the AI highway.

The potential rewards are great. “For global banking,” says a McKinsey report, “McKinsey estimates that AI technologies could potentially deliver up to $1 trillion of additional value each year.”


Automation may sound like a dry concept, and robots a little heartless, but just as innovators discover that AI enhances — rather than replaces — human creativity, businesses are realizing that AI can often understand people better than people, opening doors to the so-called “segment of one”.

Goodman describes AI’s essential power as hyper-customization applied across multiple business priorities, from customer relations to credit underwriting and due diligence.

“We’ve always had this vision of the ‘segment of one’, and AI takes us a lot closer to achieving it,” he says. “AI is approaching the point where machine learning models remember every interaction with every customer — and operate at that level of granularity — better than the highest-paid personal banker.”

Among the most agile FI players, the vision finds expression in DBPs that allow multiple individualized services — often from outside the platform owner — to be supported on a single framework.

Enabling partnerships between established banks and fintechs, DBPs harness AI, blockchain, the Internet of Things and other tools to drive hyper-segmentation of customer data. This in turn enables hyper-personalization of a stream of new products and services.

“One of the start-up banks we’ve worked with just has a checking account — that’s the only thing it does,” says Singhal. “Everything else is through the DBP ecosystem. The card is from MasterCard, the loan from HSBC. We’ll see banks use this competitive AI-enabled advantage more to distribute personalized services and focus on what they’re good at — customer relationships.”

McKinsey has identified more than 25 use cases in which AI and data analytics sharpen the financial industry's edge, bringing the “segment of one” closer. These include boosting revenue through the personalization of services and uncovering business avenues through customer data insights.

The common thread is a capacity to achieve a level of granular intelligence that brings three-dimensional views of unique entities, be they customers, business partners or new markets.


NTT has been providing advanced digital transformation to the financial industry for decades, and its “business first” philosophy delivers concrete solutions to FI players, whatever their stage in AI adoption.

Click here to download NTT’s new research: Banking on AI to Help Customers Reach Their Hopes and Dreams

NTT’s capabilities were also bolstered by the 2019 launch of its Artificial Intelligence Center of Excellence, as well as by ground-breaking AI innovations from NTT’s "corevo" suite of solutions. These include global, super-distributed, real-time processing, which has FI applications from customer acquisition to fraud prevention.

Here are some specific ways in which NTT empowers the Financial Industry with AI solutions:


Hyper-segmentation also applies to preventing fraud and ensuring compliance. NTT builds KYC (know-your-customer) and AML (anti-money-laundering) solutions for FI customers that go beyond rules-based approaches that detect wrongdoing based on a static set of criteria.

Singhal explains that in traditional methods "the biggest problem is false positives”, but AI approaches that forgo knee-jerk assessment in favor of data analytics that identifies behavioral patterns allow NTT to reduce false positives from 86 percent to 40 percent — saving time and money.


NTT is a leader in customer support systems that combine natural language processing (NLP) and superior data quality to yield surprising solutions.

In one case, a global financial services company wanted to figure out why more customers were not using its online channels. NTT built a machine-learning model based on the NLP of the company’s chat logs. That enabled the business to re-engineer automated support to drive more traffic to its online assets.

NTT has also developed a Japanese AI chat engine called Cotoha for SMBC Nikko Securities that may soon help foreign FI players make Japanese inroads.


AI-driven credit underwriting promises to help millions achieve their goals while boosting lender revenue. AI-driven data quality unleashes new sources of non-traditional credit data, such as telecom bills and social media interaction.

By migrating from rules-based data quality, AI-based underwriting enables higher loan approvals with fewer credit losses. In one case, NTT developed an AI engine for a major bank that enables it to consider 80 data sources in evaluating loan applications, making traditional Fair Isaac Corporation (FICO) credit-risk scores seem somewhat crude.

“With these advanced solutions, our mission at NTT is to help financial services see a future that’s innovative, but also achievable,” says Goodman. “We partner step-by-step to help you understand the roadmap. Because it’s really a series of steps you need to believe in — and understand — to achieve the innovative vision.”

Banking’s Digital Revolution

Banking on cloud 9.0

The cloud revolution empowers financial services players with the agility, resilience and innovation toolkit to succeed at a time of unprecedented uncertainty and creative competition.

Banking’s Digital Revolution

Staying ahead of the criminals

Financial criminals are becoming more daring and sophisticated in the Covid-19 era. Global finance must pursue advanced strategies such as AI-based encryption and anomaly detection to stay ahead of the hackers.