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Case Study

DKC Lending

How DKC Lending Transformed Private Debt Management with AI-Powered Risk Intelligence

The Client

 DKC Lending is a private and hard money lender helping real estate investors finance opportunities across Florida and select markets nationwide. Combining direct lending capabilities with deep real estate development expertise, DKC provides tailored financing, loan servicing, and strategic guidance across complex real estate transactions. 

 With experience spanning fix-and-flip, new construction, refinancing, rental properties, and other investment strategies, DKC takes a highly personalized approach to lending, evaluating each opportunity around the unique needs of the borrower and project. As the company continues to expand its lending operations and portfolio, DKC is investing in advanced technology and AI to strengthen portfolio intelligence, investor transparency, and data-driven decision-making. 

 

Logo-DKC-horizontal-gold
Business-Execution

Summary

TYPE OF PRODUCT

 Private Lending & Loan Management

BUSINESS VERTICAL

Financial Services, FinTech & Private Lending 

TECH USED

Amazon Bedrock, Amazon SageMaker, Amazon QuickSight, Generative AI & Machine Learning

SERVICE
Full-service Development Team—

Solution Architecture, Delivery Management, AI/Data Engineering, DevOps Engineering, Quality Assurance

DESCRIPTION

RevStar partnered with DKC Lending to introduce AI-powered risk intelligence and reporting capabilities across its loan management platform. The solution combines predictive analytics, Generative AI, real-time dashboards, and automated alerts to help teams identify portfolio risk earlier, streamline investor reporting, and make more informed lending decisions.

RESULTS

Reduced manual reporting time by 80%, deployed 3+ AI models supporting lending and risk intelligence, and established real-time portfolio monitoring and automated investor reporting capabilities. 

[RevStar] did a fantastic job; the formatting and execution are exactly what we needed. We are super impressed with how they’ve streamlined our manual reporting—the results are really, really good.
David Clemens CEO, DKC Lending

The Challenge

As DKC Lending expanded its private lending operations, the volume and complexity of portfolio data created an opportunity to evolve how teams accessed and acted on financial insights. 

Critical portfolio and investor reports required extensive data consolidation, while identifying emerging loan risk often depended on manually reviewing historical performance and servicing activity. At the same time, investors increasingly expected timely, transparent visibility into portfolio performance and risk.

DKC sought to build on its existing data foundation by introducing predictive intelligence, automated reporting, and real-time portfolio visibility that could scale alongside its growing lending operations. 

The Problem

The platform required a scalable way to identify potentially at-risk loans, forecast collections, surface portfolio anomalies, and generate investor-ready reporting without increasing operational overhead. 

The Solution

RevStar partnered with DKC Lending to design and implement an AWS-native AI and analytics framework that integrates predictive intelligence directly into its lending and reporting workflows.

Using Amazon SageMaker, the solution introduced machine learning models for loan risk and portfolio performance analysis. Amazon Bedrock enabled Generative AI capabilities that transform complex portfolio data into clear, professional investor and servicing narratives, while Amazon QuickSight provides embedded dashboards for real-time visibility into performance and risk.

RevStar also implemented automated data pipelines connecting DKC's existing lending data to the new analytics environment, along with AWS Lambda-powered alerts that surface delinquencies, anomalies, and other emerging portfolio risks.

Together, these capabilities created a more intelligent reporting and decision-support layer across DKC's existing loan management platform.

The Team

We have a growing cost-effective hybrid team, with onshore Product Managers and developers from our build center in Colombia. Operating three parallel teams for different products and support.
Two people collaborating at a whiteboard covered with sketches and sticky notes, planning a project layout.

Results

RevStar reduced manual reporting time by 80% and introduced 3+ AI models supporting risk scoring, default prediction, and narrative generation. Real-time dashboards, automated investor summaries, and proactive alerts now provide greater visibility into portfolio performance while establishing a scalable foundation for continued AI innovation. 

Ready for Real Transformation?

Change should feel practical and purposeful, led by people who care deeply about getting it right. Let’s make that change together.

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