What new features could Curinos add to its Deposit Intelligence solution to help banks better understand customer behavior?

Introduction

To improve Curinos' Deposit Intelligence solution for banks, we need to focus on enhancing features that provide deeper insights into customer behavior. I'll analyze the current product, identify key user segments, pinpoint pain points, and propose innovative solutions to address these challenges.

Step 1

Clarifying Questions (5 mins)

• Looking at the product context, I'm thinking Curinos' Deposit Intelligence solution might be primarily used by bank executives and analysts. Could you confirm the primary user base and their key use cases?

Why it matters: Determines the depth and complexity of features we should consider. Expected answer: Primarily used by bank analysts and product managers for deposit strategy. Impact on approach: Would focus on advanced analytics and visualization tools.

• Considering the evolving financial landscape, I'm curious about the current data sources for the Deposit Intelligence solution. What types of data does it currently incorporate, and are there any limitations?

Why it matters: Identifies potential areas for expansion in data collection and analysis. Expected answer: Currently uses transactional data and basic demographic information. Impact on approach: Would explore integrating alternative data sources for richer insights.

• Given the competitive nature of the banking industry, I'm wondering about the current market position of Curinos' solution. How does it compare to other deposit intelligence tools in terms of market share and feature set?

Why it matters: Helps determine whether to focus on differentiation or catching up to competitors. Expected answer: Strong market position but facing increased competition from fintech startups. Impact on approach: Would emphasize innovative features to maintain market leadership.

• Considering the rapid changes in customer behavior, especially post-pandemic, I'm interested in understanding the update frequency of the current solution. How often is the intelligence refreshed, and what's the latency in data processing?

Why it matters: Determines if we need to focus on real-time capabilities or batch processing improvements. Expected answer: Monthly updates with a 2-week data processing lag. Impact on approach: Would explore ways to reduce latency and increase update frequency.