Value Stream:
‍Deepen

Product usage, transaction volumes, engagement data, channel interactions, and revenue metrics, including customer activity trends and performance insights.

Overview

Growth doesn’t stop after onboarding. Banks need to turn data into deeper relationships. Centric empowers financial institutions to use AI for customer insights, product recommendations, and profitability modeling—enabling smarter cross-sell, retention, and revenue growth.

Key Statistics

60–70% of existing customers are more likely to buy new products from their bank (Harvard Business Review, 2023).

Personalized offers can increase cross-sell conversion by up to 25% (McKinsey, 2024).

AI-based customer lifetime value (CLV) modeling can lift retention by 10–20% (Accenture, 2023).

Current State / Pain Points​
Triggers for Urgency​
Future State with Centric AI

Low Product Adoption

Customers use limited services, reducing wallet share and revenue potential.

Generic Campaigns

Marketing pushes are broad and reactive, leading to low conversion.

Manual Relationship Management

Relationship teams rely on static data and intuition to manage portfolios.

Poor Revenue Insights

Disconnected systems obscure visibility into product profitability and customer value.

Missed Growth Timing

Outreach and upsell often happen too early or too late in the customer journey.

Stagnant Growth

Customer engagement plateaus despite new offerings.

Low Response Rates

Campaigns fail to resonate with specific customer needs.

Limited Visibility

Hard to identify at-risk or high-value customers proactively.

Profitability Pressure

Leaders can’t easily tie engagement to ROI.

Low Conversion

Timing mismatches lead to missed opportunities.

Product Affinity Modeling

Selects the right product for each customer based on behavior and need.

Personalized Outreach

Centric AI targets each customer with data-driven, context-aware offers.

Relationship Health Scoring

Centric AI continuously tracks engagement and alerts teams before churn risks emerge.

Portfolio Profitability Analytics

Centric AI links behavior, usage, and margins to highlight where to grow value.

Predictive Growth Modeling

Centric AI determines when to engage each customer for maximum response and retention.

Top AI Workflows (Centric-Powered)​

Lead Scoring​

Predicts conversion likelihood and risk based on behavioral and source data.​

Smart Offer Match

Dynamically assigns best-fit product (e.g., checking vs. loan vs. insurance) based on inferred intent.​

Engagement Risk Detector​

Identifies drop-off patterns to trigger re-engagement or simplified paths.​

Bot + Synthetic Detection

Flags fraud signals using device ID, form fill velocity, and data inconsistencies.​

Channel Source Optimizer​

Identifies which acquisition sources generate the best customers.​

Auto Qualification & Routing​

Filters and routes leads based on eligibility or intent signals.​

Pre-KYC Fraud Flagging​

Flags high-risk leads before triggering costly identity/KYC checks.​

High-Churn Risk Identifier (Early)​

Predicts risk of disengagement in the first 7–14 days to trigger save actions.​

Application Abandonment Predictor​

Predicts which users will drop off mid-application and when to intervene.​

Underserved Applicant Identifier​

Uses alternative signals to qualify thin-file or unbanked customers.​