Financial institutions face unprecedented pressure as competition and disruptive technologies reshape how people spend, save, and invest. The competitive landscape is intensifying while sophisticated criminal activities, including fraud and cyberattacks, pose ever-greater challenges. Regulators are enforcing stringent self-analysis, alerting, and reporting requirements. To navigate these challenges, many of the world’s largest banks, credit unions, insurance companies, and mortgage service providers rely on Altair’s data analytics, artificial intelligence (AI), and high-performance computing (HPC) solutions.
Altair® RapidMiner®, Altair’s data analytics and AI platform, is transforming business processes, ensuring compliance, and
enhancing profitability by optimizing reconciliation, streamlining the lending life cycle, electronic trading, credit origination, and more.
For over 30 years, Altair has worked with thousands of financial institutions to automate data pipelines, manage risk, aid the expansion of data science, and comply with an ever-changing regulatory landscape. Our client list includes:
Altair has worked with leading banks and banking providers for more than 30 years. These relationships are rooted in our broad capabilities for financial services analytics, including data management, data transformation, data visualization, reporting, regulation, and fraud and credit risk. Altair understands how critical it is for banks to have the tools needed to provide robust, dependable service and support.
With decades of experience across all insurance sectors, Altair excels in data analytics, the bedrock of insurance. Altair RapidMiner includes data preparation, predictive modeling, and AI capabilities that reduce manual workload and integrate seamlessly into core systems. With support for pricing, fraud detection, decision-making, and customer retention, Altair provides the essentials needed to establish and maintain a competitive edge.
Altair works with 18 of the 20 largest global investment banks. We understand institutions’ need to quickly analyze data and gain the insight needed to make swift decisions. Altair’s range of sophisticated, high-productivity financial services analytics tools combine the best of predictive analytics, machine learning, and AI with efficient data preparation, visualization, and reporting.
Mortgage providers face significant operational demands requiring quick, cost-effective access to data for lending and prepayment risk analysis. Altair’s solutions can acquire financial data directly from the array of systems used in the mortgage business, including Fannie Mae®, Freddie Mac®, Ginnie Mae®, Black Knight®, Sagent®, and more. Altair RapidMiner can handle every phase of the data life cycle, giving decision-makers clear visibility into lending risk and profitability.
Run your SAS language programs without needing to license software from SAS Institute. Mix Python, R, and SQL with the SAS language. Run your SAS language workloads on mainframes, workstations, servers, and cloud platforms and deploy via the cloud, a new on-premises platform, or a hybrid setup.
Implement a semantic, graph-based data fabric that integrates all data sources, both structured and unstructured. Develop enterprise-scale knowledge graphs to eliminate data silos, deliver on-demand insights, and ensure scalability to meet growing data volumes and evolving business needs.
Altair has a decades-long legacy of helping financial organizations automate the transformation of data for reporting, reconciliation, and advanced analytics. Regardless of structure, Altair RapidMiner can automate the extraction, transformation, and delivery of datasets – whether it’s as simple as converting PDF to Excel, preparing data for a dashboard, creating datasets to train machine learning models, staging data for a knowledge graph, or full-on data warehousing.
Altair’s patented decision trees are widely accepted as the best of breed by credit risk and fraud professionals. Across the industry, risk practitioners choose Altair’s decision trees, scorecards, and optimization capabilities for their ease of use, visual appeal, and explainability.
Asset managers with electronic trading operations across many asset classes – equities, fixed income, FX, futures, or commodities – trust Altair® Panopticon™ for real-time visualization of current market activity layered over historic data to find valuable insights, manage risk, and ensure SLAs are met. Altair RapidMiner gives traders, quants, and compliance officers the financial services analytics tools to build and deploy their own real-time monitoring and analysis systems without needing to write code.
Risk assessment is crucial for any enterprise that extends credit to customers. Commonly known as credit scoring, the process helps lenders make confident, informed decisions on whether prospective customers will honor their debt. Credit scoring is typically associated with the banking and financial service sectors, but is required across a wide array of businesses, including telecoms, retail, and insurance. In most cases, credit scoring isn't just a business tool, it's a regulatory necessity. And credit scoring is a vast industry. In the U.S. alone, recent consumer debt valuations hover over $14 trillion.
Altair works with over 4,000 banking, financial services, and insurance (BFSI) companies – including 17 of the world's top 20 investment banks. Altair RapidMiner, our data analytics and AI platform, offers unparalleled breadth and depth across the analytics lifecycle. Whether an organization requires an end-to-end platform or point solutions, Altair RapidMiner empowers customers to give their diverse teams the right tools at the right time. Our Center of Excellence (CoE) methodology provides the tools your team needs to improve their skills quickly, and our unique Altair Units licensing model provides cost-effective options that give organizations a competitive advantage.
At its simplest, a product price is defined as the sum of cost and profit. The primary aim, and biggest challenge, in the insurance sector is accurately estimating product cost. Over the years, insurers have developed a plethora of tools, methodologies, and mathematical models to calculate costs. The big data revolution along with advances in data processing, predictive analytics, and artificial intelligence (AI) has made this effort more achievable.
Credit risk specialist builds robust SAS language-powered analytics framework. Vestigo uses Altair Analytics Workbench to develop and maintain models and programs written in the SAS language. The software's drag-and-drop workflow lets its teams build new models quickly without needing to write any code. When the team needs to update existing client libraries, they can work with clients regardless of what language the client used to build them originally since Analytics Workbench can handle Python, R, and SQL in addition to the SAS language. The Vestigo team can combine modules built in any of the four languages into their updated models.