Case Study
Analytical Framework
Industry
Categories
Industry
The Challenge
Over time, the business began facing serious cash-flow challenges:
Payment delays exceeding 365 days
– More than 20% of dealers turning into defaulters
– Difficulty prioritizing which dealers to pursue for collections
– Increased risk of revenue leakage and losses
The company needed a data-driven way to:
– Predict dealer defaults in advance
– Segment dealers by risk and value at risk
– Design targeted, efficient debt-collection strategies
The Solution
The models:
– Predicted dealer defaults by product, region, and segment
– Tracked dealer risk transition from low → medium → high
– Provided behavioral insights to strengthen collection strategies
– Recommended tighter credit limits to prevent further revenue leakage
With an overall default rate of ~20%, iTuring developed AI models that:
– Predicted dealer default in the immediate next month
– Achieved 95% predictive accuracy
– Enabled monthly portfolio-level risk management
Dealers were segmented into 9 risk groups based on:
– Probability of default
– Value at risk
By focusing collection efforts on the top 30% most-likely defaulters, the models successfully captured 98% of actual defaulters, significantly improving collection efficiency.
IMPACT
WHY ITURING.AI
The platform enables collections teams to:
FAQs
The business experienced delayed dealer payments, with over 20% of dealers defaulting and some delays exceeding 365 days, impacting cash flow and increasing risk.
iTuring built machine learning models that predicted dealer defaults month over month using historical data across products, regions, and customer segments.
The predictive models achieved 95% accuracy in identifying dealers likely to default in the following month.
Dealers were segmented into 9 risk categories based on probability of default and value at risk, allowing teams to focus on the most critical cases.
By targeting the top 30% most-likely defaulters, the company captured 98% of defaults and improved collections by 332% without increasing collection effort.
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.
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.
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.
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.
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 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.
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.
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.
