Business News | Gen AI Can Significantly Reduce Cost of Auto Finance Industry: McKinsey Report

Get latest articles and stories on Business at LatestLY. Generative Artificial Intelligence (Gen AI) can significantly transform the auto finance and leasing industry by cutting operating costs and improving efficiency, highlighted a report by McKinsey & Company.

A Maruti Suzuki showroom (Photo/ANI)

New Delhi [India], November 24 (ANI): Generative Artificial Intelligence (Gen AI) can significantly transform the auto finance and leasing industry by cutting operating costs and improving efficiency, highlighted a report by McKinsey & Company.

According to the report, Gen AI can extend support beyond customer interactions to internal decision-making, generate insights, and optimise processes at scale. If leveraged effectively, AI has the potential to address long-standing inefficiencies and reshape the industry's economics.

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It stated "Gen AI could reduce cost-to-income ratios by lowering operating costs (which typically represent about 60 per cent of income) by five to eight percentage points".

To get the most out of new AI technologies, leasing players can deploy agentic systems, that is, autonomous systems that leverage AI and machine learning (ML) to perform specific tasks. These systems go beyond traditional automation by enabling dynamic, context-aware decision making and execution.

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The report highlighted that auto finance companies can integrate four AI agent groups into their operations to revolutionise their business models.

The first is the Remarketing agent, which includes a remarketing analyst assisted by gen AI on channel and price for vehicle returns, dynamic forecasting of vehicle returns and allocation across channels, and a gen AI agent analysing market movement and commentary.

The second group is the Service and operations agent, where an AI-enabled customer service agent manages document workflows and coordinates repair bookings. AI and humans can jointly analyse dealer performance, garage diligence, and insurance claims, along with AI-enabled report generation that previously required significant manual analysis (for example, garage spend variability and dealer performance).

The third group is the Procurement agent, which supports end-to-end cost scanning and vehicle lifetime value assessment. Under this model, abnormal costs can be automatically flagged for review with recommended corrections, and reconciliation reports can be automatically generated and reviewed jointly by humans and AI agents.

The fourth group is the Sales and pricing agent, where AI agents estimate technical pricing (ie, residual values), drive insight generation, and work side by side with business teams as value managers. A dynamic algorithm suggests new monthly prices based on webscraping, and agents can proactively reach out to customers with commercial offers.

Additionally, this agent group can generate comprehensive reports to maintain transparency and to control costs for maintenance, repairs, and insurance. These agents have the ability to flag abnormal claims in insurance, identify unusual dealer spending on maintenance and repairs, and detect irregular tire usage by customers, ensuring cost efficiency and operational integrity.

The report stated that to unlock early impact, organisations can begin by integrating AI into remarketing efforts, because optimising pricing across sales channels is both high impact and relatively easy to implement.

By integrating AI agent groups into the auto financing journey, companies can improve efficiency and reduce operating costs while empowering human agents to act more quickly on improved opportunities. (ANI)

(The above story is verified and authored by ANI staff, ANI is South Asia's leading multimedia news agency with over 100 bureaus in India, South Asia and across the globe. ANI brings the latest news on Politics and Current Affairs in India & around the World, Sports, Health, Fitness, Entertainment, & News. The views appearing in the above post do not reflect the opinions of LatestLY)

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