KPMG helped a U.S. payments network combine big data, artificial intelligence and statistical modeling to advance its capability to detect fraudulent transactions.
In the algorithmically-driven world of transaction security, this payments network knows precision is everything: Incorrectly blocked purchases mean lost sales and diminished customer loyalty. The company asked KPMG to help it develop an AI-driven fraud analysis engine as a value-added service for the network partners and card issuers who rely on them for fraud prevention support.
KPMG combined advanced machine learning algorithms and pattern recognition modeling to extract previously uncovered insights from our client’s transaction data. The company has gained the ability to offer more precise “second opinions” about suspect transactions, in real time. Working with KPMG, they’ve strengthened their competitive position as a trusted technology partner in a changing payments landscape.
Working with KPMG, our client has combined big data, AI, and statistical modeling to add a ready-to-deploy transaction fraud detection capability. Specific benefits include:
KPMG worked with our client to develop a fraud transaction proof of concept, along with an implementation roadmap. KPMG:
As AI succeeds in widening the competitive divide between leaders and laggards in all industries, clients appreciate KPMG’s ability to help them integrate the right combination of technology, organizational capital, and data strategy to advance their own AI agendas.
As part of our ongoing commitment to designing and building practical solutions, we structured an innovative co-development relationship model that leveraged the AI modeling capabilities of KPMG with massive pools of proprietary data from our client.
KPMG actively distills the AI experience and insight gained in data analytics engagements around the world into ready-to-deploy tools, technologies, and accelerators so clients can take advantage of our capabilities and move quickly to their objectives on day one.
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