AI in Financial Services

Banks have all the data they need to understand their customers, but they often struggle to uncover insights that can drive personalized service and deeper relationships. AI in financial services can close the gap.

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20%-30%

boost in profit

30%

savings

14%

churn reduction

About Smart Banking AI by BCG X

When it comes to being customer centric, banks have an advantage: a trove of data, everything from transaction histories, product usage, and risk profiles to online searches and campaign responsiveness. But they also have disadvantages: legacy technology, data scattered across the organization, silos instead of synergies. This makes it hard to create a comprehensive customer view—let alone to leverage AI in banking solutions.

Smart Banking AI from BCG X addresses these challenges head-on, making it simpler to bring data into a single platform, apply the latest technology for AI in financial services, and reach out to the right customer with the right action, when and where it matters.

1/5

Generative AI

Smart Banking AI employs generative AI to draft hyper-personalized emails, create summaries of key reports, produce investment memos, and identify high-potential clients.

2/5

Next Best Solution

Through machine learning models, Smart Banking AI reveals customers’ needs—and how they may be changing, suggesting products likely to resonate.

3/5

Retention

By spotting warning signs of churn, such as a drop-off in transactions, Smart Banking AI can identify at-risk clients and spur proactive engagement to retain business.

4/5

Analytical Risk Monitoring

Smart Banking AI leverages analytics to assign customers to one of three review lanes (in-depth, moderate, or light), reducing credit review costs by up to 30%.

5/5

Executive Dashboard

A mission control for relationship managers, Smart Banking AI’s dashboard provides an overview of customer leads and alerts, which can be filtered by region and product.

Benefits

The Benefits of Smart Banking AI

Financial services is about relationships. Bankers—in particular, relationship managers—continually strive to better understand and engage their customers. Deeper relationships are more effective—and more rewarding, for bank and customer alike.

Smart Banking AI creates visibility by consolidating customer information from different departments and systems (including data on products, transactions, behaviors, and interactions) onto one central platform. Then it leverages that data to do even more:

Identify Signals

Smart Banking AI mines the data for signals—a significant decrease in credit card spending, for example or a new loan with a competing bank. These signals provide clues about life events (such as a new job), actions customers may be contemplating (like leaving the bank), or trouble ahead (say, deteriorating credit).
Generate Insights

This is the heart of AI banking: What does it all mean? Smart Banking AI interprets and prioritizes the signals to generate insights—and a plan. For example: a customer at risk of closing her account might be receptive to a specific product at a specific price—but she dislikes contact by telephone, so use a different channel.
Take Action

Finally, Smart Banking AI helps deliver the recommended actions, creating a seamless workflow (through APIs and links) to existing systems (like CRM platforms) and channels (such as web, email, call center, and branches). Insights are readily accessible and are delivered in context so that relationship managers have the full picture every time they talk to a customer.

Through tailored machine-learning algorithms, Smart Banking AI unearths the treasure within your data, delivering qualified leads, attrition alerts, early credit risk warnings, and much more. It helps banks see patterns and respond with foresight and precision, working with—or even around—existing IT environments. Unique features accelerate the journey:

A Modular Approach

Speed and personalization are not mutually exclusive. Prebuilt components (ready-to-go libraries of algorithms, tools, and APIs) allow a quick launch of our AI in financial services solution. Fully customizable modular building blocks, covering the spectrum of AI use cases in banking, let banks prioritize business lines and functions while adding new capabilities.

Two Engagement Models

Smart Banking AI is designed for maximum flexibility. For banks that can manage an internal capability, we provide an in-house build supported by BCG. For those that cannot bring AI banking in-house, our subscription-based analytics service implements Smart Banking AI on BCG’s secure cloud platform.

Intuitive Insight

Smart Banking AI is customer centric and banker centric, presenting insights in an easy-to-digest manner. Relationship managers get visibility but also transparency: insights are accompanied by the data observations that support them.

Built for Mass-Market Banking, Too

While Smart Banking AI can transform one-on-one interactions, not every customer needs a relationship manager. Our solution also supports at-scale personalization capabilities, generating insights that can be applied on a broader scale.

A Modular Approach

Two Engagement Models

Intuitive Insight

Built for Mass-Market Banking, Too

Relationship Managers. By identifying emerging needs, revenue opportunities, and risks, Smart Banking AI helps relationship managers better understand their business and commercial banking customers, providing personalized, precise service that builds stronger relationships.

Marketers. For retail banks, a comprehensive set of AI and personalization capabilities—ready for deployment but easy to tailor—enable one-to-one marketing, so banks can better align offers with the needs and circumstances of each customer.

Senior Management. By providing full transparency across the client portfolio, Smart Banking AI gives managers better visibility into risks, opportunities, and progress towards goals—and lets them more quickly and more effectively adjust course.

Distribution Teams. Advanced AI banking technology enables near-real-time identification and prioritization of asset management opportunities. Smart Banking AI provides a ranked list of advisors to engage with, along with background information and recommended topics for discussion.

Sales Enablement for a North American Bank

Predictive modeling and a full 360-degree customer view were two components of a sales process update for the bank’s business and commercial banking clients. Optimized cross- and up-sell leads and retention alerts have led to revenue growth of more than 8% of annual run-rate.

growth in revenue

Credit Decision Making and Optimized Pricing for a Canadian Bank

Predictive models and 360-degree data helped a Canadian bank automate its credit decision making for business banking customers, achieving more than $25 million in annual savings. New algorithms were supported by new processes, including a steering mechanism to determine when decisions require manual assessment. A personalized pricing capability (optimizing pricing based on risk and customer characteristics) also sparked a revenue boost of more than $75 million.

$75 million

in revenue

Omnichannel Transformation at a European Bank

An end-to-end integration of data, analytics, content, and orchestration enabled a major European bank to shorten lead-processing times, deliver personalized messaging, and create more than 30 new triggers to identify sales opportunities. The bank expects its AI-empowered omnichannel approach (right customer, right product, right channel, right time) to have a €200 million revenue impact by 2025.

€200 million

in revenue