Analytics in Financial Services

Enable seamless banking experience with data management, regulatory compliance and cloud transformation. Improve banking experience

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Enhance customer experience and operational efficiency with data and AI

A robust data fabric can help financial institutions with real-time, accurate, and actionable insights to offer personalization, be compliant to regulations as well as grow their business and create a smarter organization. Sigmoid helps global banks and financial services companies unlock new opportunities at every stage of the customer lifecycle and explore avenues for data monetization. Our end-to-end, data engineering and advanced analytics and solutions help in improving processes, manage risk, prevent fraud, and ensure regulatory compliance. Our BFSI data experts can help build robust data foundations and predictive ML models to increase your profitability.

3 days to 1 hour

improvement in risk assessment time for F100 investment bank

60%

improvement in dashboard performance for a leading Fintech company

65%

reduction in false alerts for a top tier investment bank

Deploy financial analytics capabilities and enable a data-driven organization

  • Centralized data repository from siloed sources
  • Data transformation and harmonization
  • Data governance and cataloging
  • Highly available and fault tolerant architecture
Blog

Check out our blog on real-time data warehousing with Apache Spark and Delta Lake for financial institutions.

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Banking & Financial Analytics Services
  • Marketing attribution and campaign optimization
  • Real-time decisions on lead buying and servicing
  • 1:1 personalized email marketing
  • CLTV optimization
Case Study

Explore how our ML solution for lead buying delivered an 80% precision improvement for a life insurance brokerage firm.

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ML-based approach to lead buying
  • Faster and secure data processing pipelines
  • Manage and analyze compliance data
  • Real-time monitoring and anomaly detection
  • Optimize costs and reduce time to compliance
Case Study

Find out how we automated risk scoring to reduce risk assessment time from 3 days to 1 hour, improving financial crimes compliance.

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Analyze compliance data
  • Data and analytics roadmap on the cloud
  • Migration from on-premise and legacy systems
  • Seamless hybrid and multi-cloud adoption
  • Optimize existing cloud performance and costs
Case Study

Explore how Sigmoid’s data migration best practices for Snowflake delivered 10x faster insights for leading Fintech company.

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Multi-cloud adoption & migration

Data Management

  • Centralized data repository from siloed sources
  • Data transformation and harmonization
  • Data governance and cataloging
  • Highly available and fault tolerant architecture
Case Study

See how we automated daily data ingestion from 100+ vendors to drive real-time analytics and BI reporting.

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Customer Experiences

  • Marketing attribution and campaign optimization
  • Real-time decisions on lead buying and servicing
  • 1:1 personalized email marketing
  • CLTV optimization
Case Study

Explore how we delivered a 7% sales lift through personalized messaging for the 12 MN+ customer base of a leading enterprise.

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Regulatory Compliance

  • Faster and secure data processing pipelines
  • Manage and analyze compliance data
  • Real-time monitoring and anomaly detection
  • Optimize costs and reduce time to compliance
Case Study

Find out how we automated risk scoring to reduce risk assessment time from 3 days to 1 hour, improving financial crimes compliance.

Read case study

Cloud Transformation

  • Data and analytics roadmap on the cloud
  • Migration from on-premise and legacy systems
  • Seamless hybrid and multi-cloud adoption
  • Optimize existing cloud performance and costs
Case Study

Know how we helped a client save $2.5 MN annually by migrating on - prem systems with 150 Mn+ rows of data to a cloud platform.

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Mitigate risks and ensure regulatory compliance with our data and analytics services designed specifically for BFSI.
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Financial Analytics Services

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Data Collection and Analysis

Gathering and analyzing pertinent financial data, including market prices, interest rates, economic indicators, and historical asset performance. This data forms the foundation for comprehensive financial analysis.

Data Modernization icon

Financial Risk Modeling

Choosing appropriate mathematical models (e.g., VaR, stress testing, Monte Carlo simulations) to represent different types of financial risks, and calibrating these models using historical data to accurately capture the underlying dynamics.

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Fraud Detection

Utilizing comprehensive data mining, anomaly detection algorithms and advanced ML models for behavioral analysis, identity verification, and transaction monitoring to mitigate associated risks and effectively safeguard financial institutions.

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Trade Surveillance

Monitoring market transactions and trading activities to ensure regulatory compliance by leveraging real-time data analysis, pattern recognition, and surveillance tools to detect market abuses and identify potential trading irregularities.

Customer success stories

Insights and perspectives

Blog Cloud data security

How to enhance cloud data security for financial institutions

Pov Financial Crime Detection and Prevention

Sigmoid’s POV on financial crimes - detection and prevention

Guidebook Data management with DataOps

Modernizing enterprise data management with DataOps

Want to be customer-centric, compliant, and yet competitive?

Find out how F500 banks and financial institutions engage with Sigmoid to deliver the perfect banking experience!

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FAQs

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Financial analytics is critical to modern risk management strategies employed by banks and financial services, enabling them to comprehensively assess and mitigate potential financial risks. The use of data and advanced analytical techniques deliver valuable insights to facilitate risk identification, measurement, and mitigation. It aids in the detection of fraudulent activities and ensures compliance with regulatory requirements. Through stress testing and scenario analysis, organizations can evaluate their resilience under adverse conditions and create investment portfolios that balance risk and return.

Yes, organizations can utilize financial analytics to develop personalized financial products by analyzing vast amounts of financial data and gaining insights into customer behavior, preferences, and risk profiles.

A data-driven approach allows for the customization of financial products to meet individual needs, such as tailored investment portfolios, personalized insurance coverage, or customized loan offerings. Financial analytics empowers organizations to offer more targeted and relevant solutions, enhancing customer satisfaction and driving better financial outcomes.

Financial analytics streamlines account planning and revenue potential by enabling businesses to make data-driven decisions. Through comprehensive analysis of financial data, businesses can identify profitable customer segments, optimize pricing strategies, and forecast revenue projections accurately. Financial analytics also helps in monitoring key performance indicators (KPIs) such as customer acquisition costs, lifetime value, and churn rates, allowing businesses to proactively address issues and improve revenue streams. By leveraging these insights, businesses can develop targeted account plans, allocate resources effectively, and maximize revenue potential.

Increase productivity by over 30% with DataOps!

Enjoy a smoother transition to the cloud and enable better digital transformation strategies with our proven DataOps services.

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