Case Study

Next Best Product Recommendation (Banking)

Next Best Recommendation (Banking)

Analytical Framework

A leading retail bank in North America serving 500,000 customers, generating USD 200 million in annual revenue, with 20 years of operational experience.

Type

Industry

Banking

Categories

AI GovernanceCollections & Recovery

Industry

Data AcceleratorModel Risk Management

The Challenge

Financial institutions are under constant pressure to grow revenue while reducing customer churn. On average, organizations lose USD 136.8 billion per year due to churn—much of which is avoidable.

This retail bank faced challenges in: – Understanding customer needs and preferences – Linking behavior data to actionable insights – Delivering relationship-driven, timely offers – Balancing customer experience with revenue growth Without a data-driven, proactive strategy, product offers often lacked relevance, leading to missed cross-sell opportunities and lower customer satisfaction.

The Solution

iTuring.ai enabled a customer-centric recommendation strategy using its AutoML platform.

By analyzing large volumes of customer data across multiple channels, iTuring: – Identified individual customer need and intent – Predicted propensity to buy – Estimated price sensitivity to recommend optimal pricing The bank used iTuring to build a Next Best Product Recommendation model, automatically engineering 4,500+ features to train multiple machine-learning models. These recommendations were integrated into the bank’s CRM system, enabling personalized offers across multiple customer touchpoints in real time.

IMPACT

Product Revenue

14% ↑

Customer Satisfaction Score

17% ↑

Time to Deployment

6 weeks

WHY ITURING.AI

iTuring enables businesses to move from reactive selling to intent-driven personalization.

The platform:
Makes highly accurate recommendations based on customer need and intent
Combines propensity scoring with price sensitivity insights
Integrates seamlessly into operational systems for real-time execution

FAQs

01

What problem was the retail bank trying to solve?

+

The bank wanted to reduce churn and increase revenue by offering more relevant, personalized product recommendations to customers.

02

How did iTuring improve customer understanding?

+

iTuring analyzed customer behavior and preferences to identify individual intent, buying propensity, and price sensitivity.

03

How were recommendations delivered to customers?

+

The recommendations were integrated into the bank’s CRM system and activated across multiple customer touchpoints in real time.

04

What business outcomes did the bank achieve?

+

The bank achieved a 14% increase in product revenue and a 17% improvement in customer satisfaction scores.

05

Why was price sensitivity important in recommendations?

+

Price sensitivity ensured that products were offered at prices customers were more likely to accept, improving conversions and experience.

Contact us to find out more

Unlock the power of AI with iTuring.ai!

Share this resource

Related Case Study

Tarika Bhutani

Senior Director – Sales and Marketing Operations

Tarika is a market development leader driving global growth through strategic partnerships and go-to-market initiatives.

 

She focuses on expanding enterprise adoption of AI solutions across international markets, working closely with partners and clients to enable data-driven transformation.

 

Her work centres on scaling enterprise AI through partner-led growth and direct customer engagement, supporting organisations in implementing impactful, data-driven solutions worldwide.

Vipin Johnson

Vice President – Customer Acquisition

Description Goes Here

Rajnish Ranjan

Vice President, Head – Data Science

Rajnish brings over two decades of experience leading data-driven transformation across Fortune 500 organisations.

 

His career spans senior roles at HSBC, Zafin, Cisco, TCS, Nielsen, iQuanti, Symphony, Supervalu, and Harman, delivering measurable cost savings, operational efficiencies, and revenue growth.

 

With experience across banking, retail, telecom, pharma, CPG, and digital marketing, he leads cross-functional teams at iTuring.ai to deliver advanced analytics, machine learning, and AI solutions.

Aishwarya Hegde

VP Operations & Content Head

Aishwarya has been instrumental in building iTuring.ai from inception and continues to manage core operations across the organisation. Her responsibilities span project operations, financial planning, and evaluating future expansion opportunities.

 

Prior to iTuring.ai, she worked with Market Probe and WNS Research & Analytics, delivering high-impact decision support and actionable analytics for IBM with a record of zero errors.

 

Aishwarya holds a postgraduate degree in Data Science and Machine Learning from Manipal University.

Bryan McLachlan

Managing Director – Africa

Bryan has 30 years of experience driving innovation and growth across technology, banking, insurance, and retail.

 

Prior to iTuring.ai, he held executive leadership roles at Instant Life, AIG, Nedbank, FNB, and TransUnion. He focuses on enabling enterprises to adopt AI and machine learning within trusted, governed, and risk-managed frameworks.

 

Bryan holds a Master’s degree in Commerce from the University of Johannesburg.

Mohammed Nawas M P

Co-Founder, VP Product Development

Nawas brings 20 years of experience in designing and delivering cloud-native software and data systems. He has held senior technology roles at HCL, Radisys, Kyocera, and Mindtree, leading large development teams and complex product builds.

 

At iTuring.ai, he oversees product roadmap and customer delivery, applying cloud-first thinking, deep systems expertise, and a focus on building robust, scalable AI solutions that challenge industry norms.

 

He is a graduate of Rajiv Gandhi Institute of Technology.

Amit Kumar

Amit is a technology architect with over 18 years of experience designing data-intensive systems and enterprise analytics platforms. He has built highly scalable products across open architecture models and virtualised infrastructure, aligning deep technical detail with business requirements for AI and ML solutions.

 

Prior to iTuring.ai, he held senior technical roles at Radisys and Aricent. Amit leads platform architecture with a focus on governance, lineage, and traceability.

 

He holds a First Class with Distinction BTech in Computer Science from Cochin University.

Valsan Ponnachath

President, COO and Co-founder

Valsan brings over two decades of global leadership across sales, professional services, and product operations in technology and SaaS enterprises.

 

Prior to iTuring.ai, he held senior executive roles at Fiserv, Cisco, and Sun Microsystems, most recently serving as Senior Vice President at Fiserv overseeing global system integration and international professional services. Based in California, he leads iTuring.ai’s growth in the Americas.

 

Valsan holds an MBA from the University of Nebraska and a BE in Computer Science from Bangalore University.

Suman Singh

Founder & CEO

Before founding iTuring.ai in 2018, Suman led analytics at Zafin and Fiserv as CAO and General Manager Analytics, delivering enterprise-scale solutions still running in production.

 

His work includes fraud detection systems saving clients over $19M, patented Customer Relationship Score methodology, and price optimisation recognised by the INFORMS Edelman Award (2014). He has authored multiple research papers and pioneered the data-to-value approach.

 

Suman holds a Master’s in Statistics from CCS HAU and a Bachelor’s in Agricultural Engineering from BHU.