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.
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.
SmartBanking AI from BCG 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.
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.
SmartBanking 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:
Through machine-learning algorithms, SmartBanking 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. Unique features accelerate the journey:
A Modular Approach. Speed and customization are not mutually exclusive. Prebuilt components—including ready-to-go libraries of algorithms, tools, and APIs—allow banks to launch an AI in financial services solution quickly. Modular building blocks—covering the spectrum of AI use cases in banking—let them prioritize business lines and functions and add new capabilities as needed. All components are fully customizable and can be tailored to meet the specific needs of every business
Two Engagement Models. SmartBanking AI is designed to work with—or even around—your existing IT environment. For maximum flexibility, we offer two engagement models. For organizations that prefer an internal capability and have the staff to maintain and refine AI in banking software, we provide an in-house build supported by BCG. For banks that don’t have the resources—or the desire—to bring AI banking in-house, our subscription-based analytics as a service implements SmartBanking AI on BCG’s secure cloud platform (allowing a fast “go live” while giving banks the option to “go local” at a later date).
Intuitive Insight. SmartBanking AI is customer centric, but it’s also banker centric, using dashboards and banker’s language to present insights in an easy-to-digest manner. Relationship managers get visibility but also transparency: insights are accompanied by the data observations that support them. So when the solution says a specific customer needs a specific product, it also says why.
Built for Mass-Market Banking, Too. While SmartBanking AI can transform one-on-one interactions, not every customer has—or needs—a relationship manager. So the solution also supports at-scale personalization capabilities, generating insights that can be applied on a broader scale (say, tailoring messaging or pricing for each individual customer of a large email campaign).
Across regions and markets, we’re helping leading players stay on the cutting edge. Dozens of global banks already rely on SmartBanking AI. Here are some examples:
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.
AUTOMATED RISK MONITORING FOR BUSINESS BANKING CUSTOMERS AT A NORTH AMERICAN BANK
Future bad clients were identified 12-18 months in advance thanks to newly developed predictive models and a full business logic and process redesign. Annual reviews were significantly streamlined as a direct result of this work, a savings of more than 30%.
CREDIT DECISION MAKING AND OPTIMIZED PRICING FOR A LARGE CANADIAN BANK
Predictive models and 360-degree data helped a Canadian bank automate its credit decision making for business banking customers—and achieve 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 or a light review. Meanwhile, a personalized pricing capability (optimizing pricing based on risk and customer characteristics) sparked a revenue boost of more than $75 million.
BIONIC 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.
REDUCING CHURN AND BOOSTING CROSS-SELLING FOR A SOUTH AFRICAN BANK
We leveraged 70 billion data points to build a 360-degree view of customers. Machine-learning algorithms then allowed the bank to zero in on potential churners—and take steps to retain them. AI also helped the bank identify cross-sell opportunities. The result: a 14% reduction in churn, a two-times-higher uptake rate, and a four-times-lower opt-out rate from bank communications.
Our AI banking experts help clients seize the full potential of AI in banking solutions by taking a holistic approach to building the right capabilities and operating model.
Managing Director & Partner
Boston
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