Wolters Kluwer Financial & Corporate Compliance announced a strategic partnership with FairPlay AI, a leader in algorithmic fairness and model optimization technology. The collaboration brings together Wolters Kluwer’s trusted Fair Lending Wiz analytics platform with FairPlay’s innovative suite of solutions to provide lenders with a unified approach to identifying, remediating, and documenting disparities.
“We are committed to helping financial institutions navigate an increasingly complex regulatory environment with confidence,” said Atul Dubey, EVP & General Manager, Compliance Solutions, Wolters Kluwer. “Delivering FairPlay’s capabilities along with our trusted Fair Lending Wiz platform provides lenders with the tools they need to deliver fair, transparent, and inclusive financial services. This partnership marks our ongoing expansion across the lending workflow and asset classes leveraging our deep expertise and AI-driven solutions.”
Wolters Kluwer will resell FairPlay’s Fairness Optimization, Second Look, Model Validation, and Proxy Detection solutions. Lending institutions will benefit from a single, connected pathway to detect disparities, search for and document Less Discriminatory Alternatives (LDAs), re-underwrite declined applicants, and generate examiner-ready governance evidence.
“Wolters Kluwer’s Fair Lending Wiz platform is trusted by lenders and regulators across the industry, and we are honored to partner with them,” said Kareem Saleh, Founder and CEO of FairPlay AI. “Our combined technologies give lenders the tools to not only measure fairness, but to act on it, ensuring institutions can meet regulatory expectations while expanding access to credit in a responsible, data-driven way.”
Wolters Kluwer Compliance Solutions is a global provider of expert regulatory content, technology, and services that help financial institutions manage risk and meet their obligations with confidence.
FairPlay AI is a pioneering provider of algorithmic fairness technology that helps lenders make fairer, more inclusive decisions without increasing risk.
