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Advanced solutions for customer assistance and credit loss mitigation

Vendor

Vendor

McKinsey & Company

Company Website

Company Website

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Product details

The pandemic has affected everyone, including consumers who need credit and the lenders and businesses that provide it. As many consumers face difficulties repaying debts, there will be a sharp increase in those requiring financial help. Lenders must adjust to this new normal, becoming more agile and fully embracing advanced analytics—from assessing and reshaping customer-base segmentation, to changing frontline operations, channels, and debt relief options. Further, generating insights is a major challenge, as financial and operational data are often disconnected, jeopardizing both decision-making and the experimentation process to improve performance. C-Insights is a powerful analytics platform that combines and organizes data, integrating industry-standard key indicators to create a single source of truth and transparency—which makes testing outcomes and identifying problems, and the possible solutions, efficient and effective. C-Insights enables rapid decision making and innovative thinking. It helps leaders quickly implement improvement pilots and deploy advanced analytics models, with training and support from customer assistance and loss mitigation experts who have deep experience working with clients to reduce losses.

What we do

Data access

Improve efficiency, reduce errors, and empower teams with standardized and granular data in the right frequency for their needs.

Analysis and reporting

Make faster and better decisions with a curated reporting suite, resulting in higher recovery rates.

Tests and pilots

Increase the flexibility and ease of testing experiments, while improving their efficiency, accuracy, speed, and through an agile, self-serve system.

Advanced analytics

Support strategy and operations with advanced analytics models that help predict portfolio behavior, leveraging a comprehensive machine learning development and deployment environment and white-label models as a starting point.

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