Loss Mitigation Under NCUA Examination

Credit union loss mitigation under NCUA examination, highlighting Supervisory Letter 13-02 workout policy, the shift from TDR to ASC 310-20, modification-frequency limits, and 2026 priorities.

TL;DR A credit union’s loss mitigation policy was likely written against a letter that is only half current. NCUA Supervisory Letter 13-02 still governs what examiners expect in a workout policy today. One piece of that same letter, the TDR classification and reporting requirement, has not applied as written since credit unions adopted CECL. This […]

NCUA 2026 Supervisory Priorities: The Delinquency Line

NCUA 2026 supervisory priorities on delinquency, highlighting sufficiency of credit administration, examiner expectations at decade-high delinquency rates, and where prediction fits for credit unions.

TL;DR A credit union does not get to choose whether delinquency becomes an exam topic this year. NCUA already decided that for every federally insured institution, in writing, at the start of the year. Letter 26-CU-01 names the number, states it plainly, and tells examiners where to look. This piece lays out exactly what the […]

Deposit Flight Risk: Seeing It Before the Quarter Closes

Deposit flight risk prediction, highlighting the limits of concentration reports, interagency liquidity expectations, deposit-specific signals, and lead time to act before large depositors move funds.

TL;DR A deposit concentration report tells you what left last quarter. It names the relationships that shrank, the share of total deposits they held, and the dollar amount that walked out the door. None of that helps the quarter you are currently in. A flight risk model is built to answer a different question: which […]

Why “AML Platform” Means Something Different to Every Vendor

AML platform evaluation for banks and credit unions, highlighting the three product categories vendors sell, existing compliance stacks, decommissioning scope, explainability, and deployment speed.

TL;DR Ask three AML vendors what their “platform” covers and you get three different answers. One vendor means a full compliance suite, sanctions screening, transaction monitoring, case management, and SAR filing, all under one roof. Another means a monitoring or risk-scoring engine built to plug into a suite the institution already runs. A third means […]

How AML Fraud Detection Cuts False Positives Without Missing Real Cases

AML fraud detection, highlighting how rule-driven alert backlogs form, the risk of tightening rules, risk-based scoring that cuts false positives, and the evidence examiners still expect.

TL;DR An AML program built on static threshold rules learns to flag a wire over a set dollar amount, a transaction matching one of several typologies, a pattern that fits a published red flag. None of those rules check whether this specific transaction, from this specific customer, with this specific history, looks like anything beyond […]

What Predictive Analytics Software Has to Do Inside a Regulated Institution

Predictive analytics software for regulated institutions, highlighting the four use cases that pay off, explainability for examiners, build, buy, or augment decisions, platform evaluation, and fraud detection proof.

TL;DR Predictive analytics software has one job inside a bank, insurer, or lending institution that it does not have anywhere else. It has to score a borrower, a claim, or a transaction accurately, then show its work to a risk committee, an internal auditor, or an examiner who asks why the model said what it […]

DSO reduction software: the levers that actually move a loan or premium book

DSO reduction software for loan and premium books, highlighting how DSO is measured, why trade AR advice falls short, the levers that move DSO, Regulation F call limits, and tracking DSO by risk segment.

TL;DR A lender searching for DSO reduction software usually lands on advice written for a different business. Early payment discounts, tightened invoice terms, a dunning cadence synced to a billing cycle. None of it transfers to a loan installment or an insurance premium, because none of it was written with a regulated receivable in mind. […]

Best AR Automation Software: A Buyer’s Shortlist

AR automation software shortlisting, highlighting why public rankings don't fit regulated institutions, recommends-versus-executes testing, disqualifying vendor questions, and real automation depth.

TL;DR Search “best AR automation software” and the results rank vendors by feature count, integration logos, and review scores. None of that tells a bank, NBFC, or insurer which of those vendors automates a collections decision end to end and which one only generates a recommendation that still waits on a person to act on […]

Credit and Collections Software: One Function or Two

Credit and collections software, highlighting why institutions run them as separate systems, the cost of disconnected decisions, a shared scoring and data layer, and a self-check for consolidating.

TL;DR Search “credit and collections software” and the results group two different functions under one category label. Credit decisioning approves or declines an application. Collections recovers payment on an account that already went past due. Vendor listings treat them as one shopping category because many buyers evaluate both at once. That grouping does not mean […]

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.