Today’s banking and financial institutions face a dynamically changing environment, in which regulatory constraints, consumer de-leveraging, and evolving channel dynamics present significant obstacles to profitability. FinLab provides end-to-end analytics support for clients through custom solutions primarily in the areas of revenue acceleration, smart operations, fraud identification, and customer experience. Our team is geographically diverse, with experts in Atlanta, Boston, London, New York, and Silicon Valley.
We work with our clients to build custom solutions that combine deep industry expertise, quantitative analytics, and research, while helping them build capabilities needed for long-term success.
What we do
Data and analytics
Our data scientists take a data-driven approach to best understand client needs and create innovative approaches to solve their most complex challenges. We evaluate large quantities of data, carry out complex analyses, build statistical and machine-learning models, and develop actionable recommendations for a wide range of banking and financial institutions.
Software development
We bring the best of user experience and design to our integrated solutions by creating custom software and visualization tools for financial-services companies. We cover customer acquisition and retention, pricing, fraud detection, customer service, and more.
System design
Our systems architects help financial services companies assess their current end-to-end architecture and design, and build their next generation. We work with C-level business and technology executives to develop a keen understanding of their core business challenges; propose future-proofed, end-to-end technologies that satisfy functional requirements; and help the organization grow and scale.
Featured capabilities
Corporate Credit Assessment
Monitor risks and early warning indicators for a client’s portfolio with a unified view across market, industry, news, financial, and payment data, designed for credit analysts and managers.
Retention Navigator
Determine clients at high risk of churn and identify the best treatment options using a segmentation engine.
Geo Core
Evaluate localized real estate stress by asset class, using proprietary epidemiologic models, local economic data, and county-level real estate mix.
ExtractionLab and Financial Forecasting
Create automated workflows to extract financial tables from PDFs and generate standardized financial statements using state-of-the-art optical character recognition (OCR) and natural language processing (NLP) technologies.
Examples of our work
1M+ IoT data points processed daily
A North American real estate investor and developer wanted to reimagine the tenant experience across its residential, commercial, and mixed-use properties. FinLab partnered with them to build and scale innovative digital solutions, powered by a robust data and analytics infrastructure. We built an application that enabled residential tenants to coordinate their move-ins, submit rent payments, manage maintenance requests, and order services such as housekeeping and grocery delivery. Also, at the company’s commercial properties, we developed and launched a comprehensive data-backed program that helped evaluate building wellness based on air quality, density metrics, and thermal imaging, informed by real-time data streams from IoT devices.
$30M savings identified
A US lawn-services company sought to improve its long-term strategic growth and near-term profit by reducing the value at risk from high rates of customer churn. FinLab worked with the company to build an innovative analytics-powered save desk application, which supported the call center and regional branch managers in proactively identifying customers likely to cancel services and offering personalized treatments based on those customers’ churn triggers. The application also allows for continual measurement and improvement of retention efforts, and helps identify 65 percent of at-risk customers, with a potential savings of around $30 million in the near term.
8–12 percent loss reduction
A US financial-services firm sought to digitize and standardize its corporate credit-monitoring processes and improve its underwriting efficiency and quality. FinLab worked with the organization to develop a single integrated workflow platform, powered by historical assessment data and advanced analytics. The platform evaluates credit analysts’ cases, automating high-confidence assessments and supporting underwriting reviews by providing relevant data and easy-to-use digital worksheets. The new platform also enables the firm to mitigate operational risks through process consistency across teams and improve its compliance controls through a complete and transparent chain of custody and enhanced tracking and monitoring.
Featured experts
Matt Fitzpatrick
Senior PartnerNew York
Leads the firm’s work in digital and technology solutions for our Financial Services Practice and is a coleader of QuantumBlack, AI by McKinsey
Gabriel Morgan Asaftei
PartnerNew York
Develops applications powered by artificial intelligence and machine learning for real estate, retail, and financial services companies