Quantitative Research Platform for Financial Services

“We’ve been able to standardize the data, the know-how, and the ways of collaborating amongst ourselves and with our customers so that they can see the work we’re doing, as we do it. Domino accelerates our speed to delivery, providing a much faster and better return on our modeling investment.”

— Jacob Grotta, Managing Director of Risk and Finance Analytics at Moody’s Analytics

Challenges

Strict Regulations
Regulations

Financial services companies analyze sensitive PII and manage money from the public, thus they face strict regulatory requirements and need to have full visibility into all project contexts and be able to reproduce past experiments for auditing.

Collaboration
Collaboration

With 24-hour global capital markets and distributed teams, collaboration with colleagues from different teams and regions on both investment ideas and models can be difficult, undermining the benefits of collective wisdom.

Legacy Systems
Legacy Systems

With the competition for talent from fintech and the broader tech industry, financial institutions need to give quantitative researchers and investment professionals access to the latest tools for contributing to alpha and the bottom line.

Benefits for Financial Services Companies

Underwriting and Credit Scoring
Underwriting

Capabilities of machine learning algorithms fit nicely with underwriting needs. Quantitative risk analysts can train models to help underwriters work faster and more accurately.

Personalized Services
Personalization

With the help of machine learning, financial institutions can provide personalized products, services, and recommendations without adhoc manual analyses.

Fraud Detection
Fraud Detection

Machine learning can identify anomalies such as unusual patterns in trading data, and alert risk managers to investiage or trigger automatic remediation.

Trusted throughout the finance industry.

Domino lets data science and quantitative research teams perform ad hoc experimentation and analysis, schedule runs to collect, aggregate, and cleanse data, develop financial models, deploy and maintain lineage of credit ratings, detect fraud, meet auditing requirements, and more.

BNP Paribas Cardif
Lloyds Banking Group
Coatue
DBRS
LendingHome
Moody's Analytics
S&P Capital IQ
Snap Finance

BNP Paribas Cardif uses the Domino platform to develop and manage its artificial intelligence algorithms in a unique environment accessible in its 35 countries. (French) →

Coatue increased productivity and achieved significant operational savings →

Snap Finance uses API Endpoints to publish and operationalize R models as web services →

How Moody’s Analytics uses Domino to drive customer value and efficiency →

DBRS delivers faster research outcomes with Domino →

How S&P Global trained its workforce to be data-driven. →

Promoting data science literacy at S&P Global →


Make your business model-driven.

Have a question? Feel free to contact us.