Financial data analytics

Financial data analytics

Analyze your financial data

Itransition provides financial organizations, professionals, and investors with bespoke analytics solutions fully equipped to investigate financial big data assets and turn them into valuable business insights.

Banking data

  • B2B/B2C transactions
  • Mortgage interest rates
  • Cash withdrawals and deposits
  • Customer risk rate

Trading data

  • Stock prices
  • Currency exchange rates
  • Industry benchmarks
  • Market sentiment

Insurance data

  • Claims history
  • Insurance policy data
  • Accident rate
  • Insurance risk score

Accounting data

  • Cash flow statements
  • P&L reports
  • AP and AR ledgers
  • Changes in equity

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Our financial data analytics solutions

Stock market analytics

We create data analytics solutions that combine data mining and machine learning algorithms to keep track of stock price fluctuations, investors' sentiment, and other global market dynamics, enabling you to forecast financial trends, set up efficient trading strategies, and build well-balanced portfolios.
Itransition delivers data analytics platforms designed to map out customer journeys, transactions, and behavior, segment your end-users based on their attributes, and target them with tailored financial services and recommendations, resulting in superior customer acquisition and retention rates.
We provide data analytics tools capable of streamlining KYC processes to ensure safer and compliant customer relationship management, monitoring and predicting market volatility to minimize investment risk, and probing behavioral anomalies to spot financial fraud, cybercrime, and asset misappropriation.

Business performance analytics

Itransition's data analytics systems can track corporate expenses, revenues, and profitability to help you optimize budget planning and accounting while assessing major enterprise and workforce KPIs to facilitate talent management, fine-tune your business processes, and highlight improvement opportunities.

Custom vs platform-based analytics

Depending on your business goals and requirements, Itransition can offer its expertise to either craft a custom data analytics solution from scratch or provide your enterprise with a platform-based tool built on top of Microsoft Power BI, Tableau, or Qlik.

Custom solutions

A custom data analytics system built from the ground up can be the best choice for organizations requiring a tailored set of features, full product ownership, and bespoke security measures.

Platform-based solutions

A platform-based tool is the option we typically recommend implementing if you're searching for a financial data analytics solution with lower upfront costs and faster deployment times.

Custom vs platform-based analytics
  • Embedded ETL engine
  • Native integration with Microsoft products
  • Smooth implementation
  • Multiple data source connectivity
  • Top statistical analysis and forecasting
  • Support from the Tableau community
  • Advanced API command sets
  • In-memory analytics capabilities
  • Automated data integration

Our holistic data analytics expertise

Itransition's developers and consultants will share their in-depth knowledge of fintech and big data to help you design and implement impactful financial data analytics solutions, guiding you all the way from early data assessment to full deployment.

Our holistic data analytics expertise

We evaluate your financial data assets in terms of quality, legal compliance, and availability to make sure they match your requirements. We also identify suitable data sources to integrate them.

We configure ETL pipelines to extract raw data, transform it based on business logic, and load it into the data storage. If needed, we re-engineer and cleanse your datasets for further processing.

We process data with algorithms to spot patterns and correlations, build data models representing such relationships, and use these models to clarify the dynamics underlying financial trends.

We develop analytical solutions powered by data models and equipped with dashboards, charts, and other insightful data visualization features to facilitate data interpretation and storytelling.

We set up API layers to interconnect your data analytics system with market intelligence platforms, financial databases, and other reliable sources, fuelling your solution with an ongoing flow of relevant information.

We can revamp your legacy analytics solution and make it live up to modern standards by redesigning its user interface, implementing new features, or migrating the entire system to a more efficient platform.

A full tech array to drive your data analytics

We can fuel your financial data analytics software with multiple data-related technologies to grasp any meaningful information that may ensure your competitive advantage on the market.

Itransition creates machine learning systems capable of processing your financial data with self-evolving algorithms to understand the logic behind specific market dynamics and aid your decision-making.

Itransition’s data scientists carefully execute each procedure required to extract knowledge from data, including data sources identification, ETL pipelines, data modeling, and engineering.

Our experts leverage statistical and ML algorithms to process historical data, identify recurring patterns, and predict future financial trends to enhance your business forecasting capabilities.

Itransition can provide your organization with a rich selection of big data solutions to efficiently collect, store, and scan data streams for impactful financial insights.

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Ensuring data compliance

In a strictly regulated industry like finance, legal compliance constitutes an essential aspect of software development. Itransition's financial analytics solutions are carefully designed to adhere to all major data management standards and applicable industry legislation.

How we protect your financial data

We empower your financial analytics solution with efficient cybersecurity measures to protect your data assets from breaches, data leaks, and other disruptive events while offering advice on how to adopt data governance best practices.

Identity and access management
  • User activity monitoring
  • Role-based access
  • User account lifecycle automation
Security information and event management
  • Real-time security event analysis
  • Network log aggregation
  • Data storage for forensic analysis
Penetration testing
  • Cyber attack emulation
  • Security control validation
  • System vulnerabilities identification
Secure data governance
  • Data quality notification systems
  • Enterprise data catalogs
  • Data mapping features
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