Winning the Deposit War

AI-Driven Growth Strategies for Banks: ABA On-Demand Webinar

Deposit growth has become harder and more expensive. Rate-led strategies attract balance-chasers who leave the moment a better offer appears. The institutions holding and growing core deposits are doing something different: they are reading behavioral signals early enough to act on them. This on-demand session, presented by iTuring at the American Bankers Association, brings together two practitioners who have built and deployed governed AI for deposit growth in regulated environments, alongside a moderator with two decades of institutional financial services experience.

On-Demand Recording

60-minute session

AI for Deposit Growth and Retention

Presented at the American Bankers Association

Your Benefits

What This Webinar Covers

Why does rate-led deposit growth stop working at scale?

Every rate increase you make to win a new deposit is a rate you carry on every deposit you already hold. The session opens with the data behind this dynamic and explains why the institutions growing core deposits at pace are competing on relationship and behavioral depth, not basis points.

How does behavioral segmentation change deposit economics?

The session walks through a real deployment: a two-by-two segmentation model built on net interest margin and non-interest income, producing four distinct customer groups, each with a different retention and offer strategy. The result for one institution was $18 million saved within six to nine months and a 1.5 percentage point reduction in quarterly deposit attrition.

How do autonomous agents orchestrate deposit retention at scale?

Predictive models identify who is at risk. Agents decide when to contact them, through which channel, with what offer, and in compliance with every relevant rule. The session covers the full multi-agent architecture: data ingestion, prioritization, personalized outreach, response handling, and the self-learning loop that improves outcomes over time.

What does governance actually look like in a production deposit AI system?

The session covers audit trails, explainability, model risk management, and bias detection in the context of deposit use cases. Regulators and auditors can review exactly how every model was built, deployed, and adapted. The session explains what that infrastructure looks like and why it matters before a model ever goes live.

How does a bank get started, and what does the four-week path look like?

The session lays out iTuring’s proof-of-concept approach: one use case, four to six weeks, success criteria agreed upfront, results visible before any production commitment. It also covers the build-versus-buy decision and why an enterprise platform approach avoids the spaghetti that comes from stitching together point solutions over time.

Meet the Speakers

Valsan Ponnachath

Co-Founder, President and COO, iTuring

LinkedIn

Suman Kumar Singh

Founder and CEO, iTuring

LinkedIn

Moderated By

Kristen Castell

Managing Director, Fintech CAFE

LinkedIn

Who is this for?

Who Is This For?

If you lead retail deposit growth or head a consumer banking team and are trying to move beyond rate-based acquisition, the session covers the behavioral and AI-driven approach that is producing measurable results at comparable institutions. If you are a risk or compliance leader responsible for model documentation and fair lending, the session covers what governed AI infrastructure looks like in deposit contexts and what auditors are looking for when AI is involved in customer outreach and offer decisioning. If you run an AI or data science team and are trying to move deposit models from pilot to production, the session shares a structured methodology for getting to value in four to six weeks without creating governance debt. If you are an executive making technology investment decisions, the session makes the case for an enterprise platform view of deposit AI rather than assembling point solutions by use case, and explains what the long-term cost of the latter approach tends to be.

Frequently Asked Questions

01

How do I access the recording?

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After submitting the form, you will receive an email with a private link to stream the full session.

02

Is this only relevant to large banks?

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No. The examples in the session are drawn from community banks and credit unions as well as tier-one institutions. The $18 million case study comes from a 500,000-member credit union. The governance and segmentation principles apply at any deposit portfolio size.

03

How technical is the session?

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This is a strategy and operations discussion. It assumes familiarity with deposit banking and general awareness of AI terminology but does not go into code, mathematics, or model architecture in detail.

04

Do I need a data science background to follow along?

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No. The session is built for deposit leaders, risk officers, and executives who work with AI systems or are evaluating them, not teams who build models from scratch.

05

Can I watch only the section that is most relevant to my role?

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The full recording is available as one continuous session. Timestamps for each topic will be included in the access email so you can navigate directly to the sections most relevant to you.

06

What if I have a follow-up question after watching?

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Send it to info@ituring.ai and the team will follow up directly.

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