Zapata Computing and KPMG UK collaborate to create risk and operational modeling

 
Industrial generative AI company Zapata Computing Holdings Inc. and audit, tax, and advisory firm KPMG UK have successfully completed a client project to streamline the compliance models of an international insurance firm.
Using Zapata’s advanced analytics, optimization, and generative AI capabilities, the project aims to revolutionize the client’s risk, operations, and compliance modeling processes.
KPMG’s actuaries, in collaboration with Zapata’s data engineers, have transformed one of the client’s compliance models, which comprises tens of millions of inputs, into an optimized solution using innovative algorithms. This new approach drastically reduces computing time by over a thousandfold while maintaining accuracy, allowing the client to meet compliance requirements efficiently. Clients will now receive advanced approximations rather than actual finished calculations.
Christopher Savoie, Chief Executive Officer and Co-founder of Zapata AI, remarked, “KPMG UK is renowned for assisting clients in managing risks, complying with regulations, and enhancing overall business performance. The transformative results we’ve achieved for this insurance client are applicable to any company struggling with high-complexity, high-resource computational models on legacy systems. Given the current scarcity of compute and data science resources, Zapata’s ability to quickly deliver value is especially meaningful. We are proud to partner with KPMG UK to combine our technical and domain expertise to deliver significant client value.”
Feargal De Burca, Partner at KPMG UK, added, “The Zapata AI team has demonstrated remarkable results in streamlining large, complex model workflows for our insurance client. Zapata’s expertise and technological solutions have the potential to transform the operations of financial services and insurance companies by delivering efficiencies and spearheading innovative digital transformation programs.”
Source: reinsurancene.ws
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