ISG announces 2026 ISG Women in Digital Awards winners for Asia Pacific. Leaders with RiskSpan, Spark New Zealand, HCLTech, Wipro, Hamsa AI Labs and Microland Limited named gold winners in six award categories SYDNEY-(BUSINESS WIRE)-Information Services Group (ISG) (Nasdaq: III), a global AI-centered technology research and advisory firm, today announced the winners of the ISG Women in Digital Awards program for Asia Pacific, recognizing women and their achievements in technology roles. ISG announced the winners of the ISG Women in Digital Awards program for Asia Pacific at a live, virtual award ceremony on September 17. Leaders with RiskSpan, Spark New Zealand, HCLTech, Wipro, Hamsa AI Labs and Microland Limited were named gold winners. Share At a live, virtual award ceremony the evening of September 17, leaders with RiskSpan, Spark New Zealand, HCLTech, Wipro, Hamsa AI Labs and Microland Limited were honored as gold winners in six categories. Silver and bronze winners were also recognized, along with the down-selected finalists, known as luminaries, for each category. "Congratulations to the impressive and accomplished Asia Pacific winners of our ISG Women in Digital Awards," said Kimberly Tobias, partner, ISG, and program leader of ISG Women in Digital. "We are delighted to celebrate their successes and their impact on technology, business and the next generation of women leaders." An independent panel of judges, comprised of Sandie Breese, director, Provider Services, Asia Pacific, ISG; Karen Holland, board director and advisor; Angela Jones, general manager, Technology, Strategy and Governance, Australian Retirement Trust, and Vinika Yadav, global HR operations head, Hitachi Rail, evaluated the nominations and selected the following winners: * Rising Star: for demonstrating exceptional and continuous growth, with increasing levels of leadership, responsibility and sphere of impact. Bronze Winner: Maithili Misal, associate architect, ITC Infotech India Silver Winner: Swathi Subhash, manager, regional bid management, MENA, KaarTech Gold Winner: Deepthi Sudharsan, AI engineer, RiskSpan * Women's Advocate: for playing an active role guiding women to succeed in the digital world. Bronze Winner: Sisi Wan, senior director, analytics, APAC, TP Silver Winner: Jayapriya Jagannathan, NFT COE lead, Cognizant Technology Solutions Gold Winner: Heather Langton, chief people officer, Spark New Zealand * Digital Innovator: for making a significant impact on an organization, business or client through creative use of digital solutions. Bronze Winner: Sarah Noelle Jacob Rebueno, chief of staff, APAC - Malaysia & Thailand, TP Silver Winner: Mary Martin Melcy Kruz, industry principal, HCLTech Gold Winner: Shyamala Chandrasekar, chief product officer, Autonomous Banking, HCLTech * Rock Star Leader: for leading a major transformation with significant business impact and demonstrating exceptional leadership skills. Bronze Winner: Brooke Newman, executive general manager, Procurement, Partnering & Real Estate, Suncorp Silver Winner: Padmashree Shagrithaya, executive vice president & MD - Insights & Data Global Business Line, Capgemini Gold Winner: Sandhya Arun, chief technology officer, Wipro * AI Champion: for driving the strategic use of AI as a catalyst to dramatically transform how a company or organization works, how a product or service performs, or how people live or work. Bronze Winner: Mani Prasanna Tallapragada, senior director, DXC Technology Silver Winner: Anuradha Balasubramaniam, senior vice president and head, Agentic Operations, Genpact Gold Winner: Aarti Kapur, co-founder and managing partner, Hamsa AI Labs Meenu Bagla, chief marketing officer, Microland Limited, was chosen by the judges as the Digital Titan of the Year for Asia Pacific from among all regional nominees, recognizing her as the most outstanding woman in digital for 2026. The ISG Women in Digital Awards program, launched in the Americas in 2022, was expanded in 2023 to the Europe, Middle East and Africa (EMEA) and Asia Pacific regions, including India. In 2026, the global program had more than 700 finalists, who are listed in the online ISG Women in Digital eBook. Winners for the Americas were announced in a live, virtual, regional awards ceremony on September 10. Winners for EMEA will be announced on September 24. The ISG Women in Digital Awards are part of the ISG Women in Digital program, established in 2018 to provide a platform to exchange practical advice and innovative ideas on advocacy and advancement in the workplace. The community hosts a LinkedIn page, a LinkedIn Live video series and regular events for ISG employees and the greater IT and business services industry. ISG (Nasdaq: III) is a global AI-centered technology research and advisory firm. A trusted partner to more than 900 clients, including 75 of the world's top 100 enterprises, ISG is a long-time leader in technology and business services that is now at the forefront of leveraging AI to help organizations achieve operational excellence and faster growth. The firm, founded in 2006, is known for its proprietary market data and research, in-depth knowledge and governance of provider ecosystems, and the expertise of its 1,500 professionals worldwide working together to help clients maximize the value of their technology investments. Contacts. Erik Arvidson, Matter Communications for ISG +1 978 518 4542 [email protected] More News From Information Services Group, Inc. STAMFORD, Conn.-( BUSINESS WIRE )-An ISG Provider Lens(R) report finds that Enterprise Service Management increasingly functions as an enterprise execution layer in U.S. organizations... STAMFORD, Conn.-( BUSINESS WIRE )-U.S. public sector organizations continue to modernize mission-critical systems while evaluating new technologies for measurable outcomes, ISG says... STAMFORD, Conn.-( BUSINESS WIRE )-Enterprises are accelerating investment in data management tools and platforms so they can confidently scale AI implementations, ISG says... Information Services Group, Inc. NASDAQ:III Release Summary The 2026 ISG Women in Digital Awards named leaders with RiskSpan, Spark New Zealand, HCLTech, Wipro, Hamsa AI Labs and Microland Limited gold winners. Release Versions

RiskSpan launches Non-QM credit model trained on $87B in loans. Managing Editor Jul 22, 2026 Model separately analyzes bank-statement, DSCR, and full-documentation collateral using data from approximately 226,000 loans RiskSpan has launched a credit-risk model built specifically for non-qualified mortgages, giving investors and issuers a tool that accounts for differences among bank-statement, debt service coverage ratio, and full-documentation loans. Credit Model 7.1 is now generally available through the RiskSpan Platform. When paired with the company's existing Non-QM prepayment model, the new model allows users to conduct credit and prepayment analyses and generate loan-level cash flow projections within a single environment, according to RiskSpan. Morningstar DBRS reported that Non-QM residential mortgage-backed securities issuance reached a record $20.9 billion during the third quarter of 2025, up 97% from $10.6 billion one year earlier, according to figures cited by RiskSpan. Fitch Ratings reported that issuance within its rated Non-QM and non-prime RMBS portfolio increased by more than 800% between 2020 and 2023. KBRA, meanwhile, projects that overall non-agency RMBS issuance - a broader category that includes Non-QM securities - will increase 15% in 2026 to $160 billion. That growth has increased the volume of loan-level data investors and issuers must evaluate when pricing transactions and making allocation decisions. RiskSpan contends that models developed for agency mortgages or older non-agency collateral do not fully capture the borrower behavior found across different Non-QM documentation types. Get the NMP Daily Essential stories, every weekday. Model separates collateral by documentation type. Credit Model 7.1 uses a transition-state framework, with loan-performance transitions estimated independently for bank-statement, DSCR, full-documentation, and other loan categories. That segmentation is intended to capture the differences in borrower behavior and credit performance among products that may all fall under the broader Non-QM label. "Non-QM borrower behavior varies meaningfully by documentation type, and generic credit and prepay frameworks simply don't capture that," said Divas Sanwal, head of modeling at RiskSpan. "Credit Model 7.1 was built from the ground up on Non-QM collateral, segmented by doc type, and validated with published backtesting - giving risk teams, auditors, and counterparties the transparency they need to stand behind the model." The model incorporates 10 loan- and borrower-level variables, including credit scores, mark-to-market loan-to-value ratios, debt-to-income ratios, and loan purpose. It also incorporates three macroeconomic drivers. RiskSpan trained the model on approximately $87 billion in unpaid principal balance across roughly 226,000 Non-QM loans originated or outstanding between January 2018 and August 2025. The distinction among loan types has become more consequential as Non-QM volume increases. NMP previously reported that delinquencies rose across the Non-QM and non-prime RMBS sector, with Fitch identifying deterioration among newer loan vintages. Tape analysis and API access included. The release also includes artificial intelligence-powered tools for processing loan tapes and analyzing collateral. Clients can access model results through an application programming interface and integrate the output into their existing systems. RiskSpan said it plans to add a user-facing backtesting dashboard. Container deployment and additional integrations are also planned for later phases. Credit Model 7.1 is currently available to RiskSpan Platform and Loans Module clients. RiskSpan's model reflects a more granular approach to Non-QM risk: bank-statement, DSCR, full-documentation, and other loans are modeled separately rather than treated as a single collateral category. For mortgage bankers, that distinction could help identify which documentation types are driving expected losses or prepayments within a loan pool, informing aggregation, securitization, and capital allocation decisions. *This article was primarily written by a human author. AI tools were used in a limited capacity for research assistance or light editing. Managing Editor Czarinna Andres leads editorial coverage for NMP, focusing on the trends, policies, and business strategies shaping today's mortgage and housing finance landscape. She brings a background in journalism and media, with experience... Jul 22, 2026