Meet Security & Compliance Standards
Transform Your Financial Operations with Ksolves Big Data Solutions
Financial institutions generate massive volumes of data, but much of it remains underutilized. Ksolves delivers Big Data analytics in finance by building secure, scalable data platforms for banks, fintechs, insurers, and capital markets. With 12+ years of data engineering expertise, we help modernize data infrastructure, enable real-time analytics, strengthen risk management, and simplify regulatory compliance.
Our Big Data Service for the Finance Industry
Ksolves delivers end-to-end Big Data analytics for financial services, from strategy and lakehouse engineering to real-time analytics and managed support.
Big Data Strategy & Architecture
Build a scalable Big Data foundation with Ksolves. Our architects assess your banking, payments, trading, and risk systems to design secure, cloud-ready architectures that support modernization, regulatory compliance, and future growth.
Financial Data Lakehouse Engineering
Unify fragmented financial data with a modern lakehouse. We implement Delta Lake, Apache Iceberg, and Apache Hudi to consolidate transaction records, customer data, and compliance datasets into a governed platform for Big Data in the finance industry.
Real-Time Streaming Analytics
Our engineers build high-performance Apache Kafka and Apache Flink pipelines for continuous data processing. Process payment events, trading feeds, and customer transactions with low latency. Enable real-time fraud detection, operational monitoring, and faster business decisions.
Fraud Detection & AML Analytics
Detect fraud before it impacts your business. We build AI-powered analytics solutions that identify suspicious transactions, AML risks, and abnormal customer behavior in real time while reducing false positives.
Credit & Risk Analytics
We develop scalable pipelines for continuous credit scoring and portfolio risk analysis. Replace overnight batch jobs with real-time risk insights. Our solutions support BCBS 239, Basel III, and enterprise risk management initiatives.
Market Risk Analytics
Gain real-time visibility into market exposure. We build distributed analytics platforms that process trading data, market feeds, and portfolio positions to support P&L attribution, XVA calculations, and faster risk reporting.
Customer Analytics & Personalization
Unify transactional, digital, and open banking data into comprehensive customer profiles. Power churn prediction, product recommendations, and next-best-action strategies with big data analytics in finance. Deliver personalized financial experiences at scale.
Regulatory Reporting Automation
Simplify complex regulatory reporting. Ksolves automates data validation, lineage, and reporting workflows for Basel III, IFRS 9, BCBS 239, MiFID II, and GDPR, reducing manual effort and improving audit readiness.
Core Systems Integration & Migration
Connect modern Big Data platforms with legacy core banking systems, payment gateways, trading platforms, CRM solutions, and third-party data providers. We use CDC, ETL, and API-based integration to ensure reliable, low-latency data movement. Migrate with minimal disruption to business operations.
Build a scalable Big Data foundation with Ksolves. Our architects assess your banking, payments, trading, and risk systems to design secure, cloud-ready architectures that support modernization, regulatory compliance, and future growth.
Unify fragmented financial data with a modern lakehouse. We implement Delta Lake, Apache Iceberg, and Apache Hudi to consolidate transaction records, customer data, and compliance datasets into a governed platform for Big Data in the finance industry.
Our engineers build high-performance Apache Kafka and Apache Flink pipelines for continuous data processing. Process payment events, trading feeds, and customer transactions with low latency. Enable real-time fraud detection, operational monitoring, and faster business decisions.
Detect fraud before it impacts your business. We build AI-powered analytics solutions that identify suspicious transactions, AML risks, and abnormal customer behavior in real time while reducing false positives.
We develop scalable pipelines for continuous credit scoring and portfolio risk analysis. Replace overnight batch jobs with real-time risk insights. Our solutions support BCBS 239, Basel III, and enterprise risk management initiatives.
Gain real-time visibility into market exposure. We build distributed analytics platforms that process trading data, market feeds, and portfolio positions to support P&L attribution, XVA calculations, and faster risk reporting.
Unify transactional, digital, and open banking data into comprehensive customer profiles. Power churn prediction, product recommendations, and next-best-action strategies with big data analytics in finance. Deliver personalized financial experiences at scale.
Simplify complex regulatory reporting. Ksolves automates data validation, lineage, and reporting workflows for Basel III, IFRS 9, BCBS 239, MiFID II, and GDPR, reducing manual effort and improving audit readiness.
Connect modern Big Data platforms with legacy core banking systems, payment gateways, trading platforms, CRM solutions, and third-party data providers. We use CDC, ETL, and API-based integration to ensure reliable, low-latency data movement. Migrate with minimal disruption to business operations.
Big Data Challenges in Finance Solved by Ksolves
Despite large data assets and significant technology investment, most financial institutions still struggle to produce timely, trustworthy, and actionable intelligence. These are the root causes Ksolves is built to address.
Siloed Financial Data
Disconnected banking, trading, and risk systems limit visibility and delay insights.
Legacy Batch Processing
Batch jobs cannot support real-time fraud detection, risk monitoring, or instant payments.
Fraud Detection Gaps
Rule-based systems miss evolving fraud patterns and generate high false-positive rates.
Regulatory Complexity
Fragmented data and manual reporting increase compliance risks and audit effort.
Poor Data Quality
Inconsistent data reduces the accuracy of analytics, reporting, and risk models.
Limited Customer Insights
Disconnected data restricts personalization, churn prediction, and cross-sell opportunities.
Dealing with fragmented risk data, slow fraud
detection, or regulatory reporting gaps?
Why Choose Ksolves?
Ksolves is a trusted service partner for Big Data in the finance industry, delivering certified expertise, proven integrations, and enterprise-grade security across every engagement.
12+
Years of Industry
Expertise
180+
Salesforce Projects
Implemented
30+
Countries Served
100%
Global Salesforce Support
350+
Certifications
200+
Happy Clients
99%
On-Time Project
Delivery
Big Data Technologies Built for Financial-Grade workloads
We work exclusively with production-proven open-source and cloud-native technologies, selected for the throughput, reliability, and auditability requirements of Big Data analytics financial services institutions at enterprise scale.
Apache Kafka
Apache Flink
Apache NiFi
Amazon Kinesis
Azure Event
HubsGoogle Pub/SubDebezium
CDCKafka Streams
Delta Lake
Apache Iceberg
Apache Hudi
AWS S3
Azure Data Lake Storage
Google Cloud Storage
Apache HBase
Apache Cassandra
Apache Spark
Databricks
Presto / Trino
ClickHouse
Apache Druid
dbt
Apache Hive
PySpark MLlib
TensorFlow
XGBoost
scikit-learn
MLflow
Flink ML
Apache Atlas
OpenLineage
Great Expectations
dbt tests
Other Industries We Cater To
We implement Big Data solutions to align processes, data pipelines, and analytics for scalable growth across industries.
Manufacturing
Build predictive maintenance, real-time quality control, and OEE optimization platforms by unifying production, supply chain, and equipment sensor data.
Retail and E-Commerce
Deliver real-time customer analytics, demand forecasting, and inventory intelligence that personalize experiences and reduce operational costs at scale.
Healthcare
Consolidate EHR, clinical, and billing data into HIPAA-compliant platforms that power predictive patient care, population health analytics, and compliance reporting.
Nonprofit
Unify donor, program, and impact data into governed analytics platforms that drive data-driven fundraising, grant reporting, and measurable mission outcomes.
BFSI
Power real-time fraud detection, credit risk analytics, regulatory reporting, and personalized customer intelligence across banking, financial services, and insurance.
Logistics
Consolidate fleet, warehouse, and supply chain data to optimize route planning, reduce delivery costs, and improve end-to-end operational visibility in real time.
Education
Unify student performance, engagement, and institutional data to support early intervention, personalized learning pathways, and smarter administrative decisions.
Telecom
Process CDRs, network events, and subscriber signals at petabyte scale to enable churn prediction, fraud detection, and real-time network performance intelligence.
Hospitality
Unify guest behavior, booking, and operational data to personalize guest experiences, optimize pricing strategies, and improve revenue per available room.
Media and Entertainment
Deliver real-time content analytics, audience segmentation, and recommendation engines that maximize engagement, reduce churn, and monetize content effectively.
Ready to Activate Your Financial Data as a
Strategic Asset?
Speak with a Ksolves Big Data architect about your risk, fraud, compliance,
or customer intelligence requirements.
Frequently Asked Questions
It refers to using scalable data engineering platforms to process the high volume, velocity, and variety of financial data. Ksolves applies this through real-time streaming pipelines, governed lakehouses, ML-powered fraud detection, credit risk scoring, and automated regulatory reporting across banks, insurers, fintechs, and capital markets firms.
Transaction records, trade and order book data, credit bureau feeds, loan origination data, customer behavioural signals, market data (equities, FX, rates), actuarial data, regulatory datasets, and third-party alternative data. In our Big Data in the finance industry services, we handle your platform for real-time streams and historical batch workloads at a petabyte scale.
Basel III (CET1, RWA, LCR, NSFR), IFRS 9 ECL modelling and staging, MiFID II transaction reporting, BCBS 239 risk data aggregation, CCAR stress testing (US institutions above $100B), and GDPR data subject request processing.
Kafka and Flink-based pipelines typically achieve milliseconds to low single seconds from event ingestion to alert generation. This is sufficient to intercept payment fraud before settlement. Sub-millisecond latency for FPGA-based high-frequency trading is outside the scope of Big Data streaming platforms.
We build Kafka-based event streaming platforms, real-time AML monitoring, usage-based billing pipelines, and customer analytics engines tailored for fintech transaction volumes, PSD2, and Open Banking frameworks, for both early-stage fintechs and established players handling millions of transactions daily.
Typically 8 to 24 weeks, depending on scope and integration depth. We use an agile model, releasing working pipelines early so stakeholders see measurable value before full platform deployment.
