How banks deepen their relationships with SMBs with AI-Driven Customer Analytics
TCS Digital Software & Solutions
DS&S is a Strategic Growth Business within TCS, helping large businesses navigate critical digital transformations.
Today, there are over 31 million small businesses in the US according to the Small Business Administration and more than half of these small and mid-sized businesses business (SMBs) do not feel their banks understand their needs.
To engage with SMBs and benefit from the untapped opportunity this segment represents, banks must build deeper relationships and deliver unique value, or risk losing these customers to other financial institutions or fintech's that can meet their unique needs.
So how do banks broaden and deepen their relationships with SMBs?
The key is to make better use of the data already available within the enterprise, augment it with external data, and use AI and ML to generate actionable SMB customer insights in real time.
Success depends on a bank’s ability to understand, and respond to, the precise needs of each SMB, equip relationship managers with timely information, and effectively engage SMBs throughout their financial customer journeys.
AI-driven customer analytics
SMB customers want information and services that go beyond selling products and services. Instead, they’re looking for genuinely personalized experiences that address their changing needs. To deliver this kind of personalization, you need an agile, AI-driven customer analytics solution that enables you to:
Unify disparate online and offline data sources from enterprise systems (customer, account, and transactional data), first party (behavioral clickstream and intent data) and third-party (firmographic, intent, and other data) to create a single, 360° customer view of SMB customers in real time.
Understand the SMB ecosystem by linking associated entities including owners, contacts, and related companies with an option to enrich and augment data from third-party sources.
Consolidate key details from core banking and other backend systems including accounts, balances, and transactions that is enhanced with insights from balance trends, held away accounts, and cash flow analytics. ?Use these account insights to create contextual alerts and actions.
Generate AI-driven, personalized product and service recommendations based on first party data, behavioral data, and third-party intent data.
Connect meaningful data from internet and external sources including intent, social, and segmentation data to create ranked leads and recommendations to attract new customers and retain existing customers.
Ensure you have a journey tracker that is updated continuously to display key interactions, events such as intent signals, next best actions (NBA’s), and customer’s response to those NBAs in real time. Track and analyze data including activity--online banking login, mobile banking login, calls to your call center, and duration of calls. Use AI to analyze Intent signals including online behaviors such as when an SMB customer is looking for a business loan, a business real estate financing, or small business lending on your site to predict a customer’s intent.
Analyze risk based on several predictive scores including payable-through-draft (PTD), early pay-off, churn, and other additional scores to take corrective action.
What does personalized SMB banking look like??
Based on data-driven, actionable insights, you build lasting and profitable SMB relationships by delivering experiences, services, alerts, recommendations, and information tailored to their unique needs.
Time-sensitive alerts enable you to proactively engage with your SMB customers with information reminders such as when they face a potential low balance issue, their line of credit renewal date is comping up for review, their business CD is maturing in the next few weeks, etc. In addition, alerts let you know when an SMB customer’s churn score is trending upward so you can take preventative action.
Your SMB customers receive relevant recommendations at the right time via their preferred channel based on intent data. Examples include recommendations for business loans, business retail estate financing, small business lending, business credit cards, business funding, and more – delivered via email, mobile app, text, phone (or however each customer prefers to do business).
Based on journey tracking, you deliver bespoke customer experiences. ?For example, let’s say an anonymous customer visits your website and explores information about commercial real-estate (CRE) loans. The visitor views the CRE details and performs some calculations using your online calculator. These are good intent signals, and the browsing data is instantly analyzed for intent topics and scores. ?
The journey tracker is updated, and the intent topics and scores are associated with the specific company profile. Relevant recommendations are analyzed using AI and ML models that evaluate several attributes including account activity, first party behavioral data, and third-party intent data and generate personalized recommendations in real time.
Using these insights banks can orchestrate contextual, real-time offers across channels at scale. For example, the next time this customer visits the website, a personalized, limited time offer appears for an interest rate discount on CRE financing and waived closing costs. ?
These are just a few examples of how an AI-driven customer analytics solution can help you deliver truly personalized experiences and build stronger SMB relationships.
One such solution is our AI-driven customer analytics software, TCS Customer Intelligence & Insights?. To learn more, please visit: ?https://www.tcs.com/customer-analytics-hyperpersonalization-banking
About the author
Kathleen Holm is Marketing Director of the TCS Digital Software & Solutions (DS&S) Group. She has more than 25 years of experience marketing technology software and services to enterprises worldwide.