Financial institutions grapple with complex decisions everyday, struggling to turn data across various systems into actionable intelligence.
Eliminate the data overwhelm with financial data analytics that brings structure to scattered information. Identify the forces influencing performance, operations, and compliance to support sharper forecasting and proactive business responses.
Whether you’re dealing with large datasets from multiple sources, need help organizing it for clearer analysis, or want to turn raw numbers into easy-to-understand visuals, Roxiler Systems works alongside you at every stage of your data analytics journey. From data integration and transformation to insight generation and visualization, we help teams make sense of their data, faster.
Key Features:
Errors, duplicates, and inconsistencies eliminated from financial, customer, and transaction records through data cleansing.
Accelerated ETL workflows with data preprocessing pipelines for real-time analytics and compliance reporting.
AI-Powered Data Quality Monitoring for fast data discovery, lineage tracking, and audit-compliant, decision-grade datasets.
Benefit:
Data Engineering helps financial institutions harness clean, consistent, and analytics-ready data, minimizing risk and enabling smarter decisions in lending, credit scoring, and compliance.
Key Features:
Centralized data storage that consolidates customer, transaction, compliance, and operational data.
Scalable data lakes and warehouses that support growing volumes of unstructured and structured financial data.
Seamless integration with CRMs, ERPs, and core platforms simplifying GLBA, FCRA, (GDPR for EU), CTF and AML compliance.
Benefit:
Strengthened financial services with centralized data access for faster reporting, improved risk management, compliance adherence and data-driven decision-making.
Key Features:
Predictive Analytics to forecast loan defaults, credit risk, churn, and fraud using historical data.
Hyper-targeted lending and personalized financial services using ML-powered segmentation.
AI-Driven Risk Scoring & Anomaly Detection to assess borrower behavior and flag suspicious transactions, with AI Copilots and NLP- driven querying.
Benefit:
Smart visualization helps financial institutions go beyond dashboards, leveraging AI for predictive, real-time insights that enhance decision-making, reduce risk, and personalize customer interactions.
Fragmented customer data across legacy systems blocks a true Customer 360 view, limiting financial analytics performance and personalization.
Without automated data pipelines, financial reporting remains slow and error-prone, impacting compliance, analytics accuracy, and timely decisions.
Financial Institutions still use descriptive rather than predictive analytics, unable to forecast defaults, churn, or fraud in real time.
Real-time fraud detection with AI enables faster anomaly spotting and risk scoring - far more effective than legacy monitoring across scattered systems.
Without structured financial analytics, institutions struggle to meet audit timelines and compliance regulations due to inconsistent data handling and lack of traceability.
Financial institutions need dynamic, AI-powered dashboards to visualize portfolios and customer journeys in real-time to spot anomalies that matter.
Bridge critical data gaps in Finance with centralized analytics, real-Time monitoring, and predictive insights for smarter compliance and risk management
When you’re stuck deep inside data mineshafts everyday handling immediate concerns, it’s easy to miss diamonds in the rough staring right at you. We’ve helped organizations uncover and capitalize on opportunities by delivering powerful insights, right when needed. We can give you that edge too.
Roxiler Systems transformed FRR Forex’s remittance operations with a unified CRM—boosting compliance, lead conversions, and efficiency through automation, real-time insights, and seamless FxPlus integration.
Do you still have any questions, let us know. We would be happy to assist.
Customer 360 Analytics in finance refers to a unified view of customer data from all touchpoints transactions, support, KYC, and behavior to enable personalized services and targeted campaigns.
Tools include machine learning models, time-series forecasting, and AI-based data mining platforms like Apache Spark, Snowflake, and TensorFlow.
Data Analytics tools detect fraud by analyzing real-time transactions, user behavior, and historical fraud patterns to flag anomalies instantly.
Financial Data Analytics transforms raw data from various systems into real-time, actionable insights – helping institutions identify trends, assess risks, and make faster, data-driven decisions.
Analytics tools detect fraud by analyzing real-time transactions, user behavior, and historical fraud patterns to flag anomalies instantly.
A centralized warehouse unifies customer and transaction data – boosting reporting speed, compliance, and advanced analytics capabilities.
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