Synechron, Inc. has announced the launch of its AI Data Science Accelerators for Financial Services, Banking and Insurance (BFSI) firms. These four new solution accelerators help financial services and insurance firms solve complex business challenges by discovering meaningful relationships between events that impact one another (correlation) and cause a future event to happen (causation).
Following the success of Synechron’s AI Automation Program – Neo, Synechron’s AI Data Science experts have developed a powerful set of accelerators that allow financial firms to address business challenges related to investment research generation, predicting the next best action to take with a wealth management client, high-priority customer complaints, and better predicting credit risk related to mortgage lending. The Accelerators combine Natural Language Processing (NLP), Deep Learning algorithms and Data Science to solve the complex business challenges and rely on a powerful Spark and Hadoop platform to ingest and run correlations across massive amounts of data to test hypotheses and predict future outcomes.
The Data Science Accelerators are the fifth Accelerator program Synechron has launched in the last two years through its Financial Innovation Labs (FinLabs), which are operating in 11 key global financial markets across North America, Europe, Middle East and APAC; including: New York, Charlotte, Fort Lauderdale, London, Paris, Amsterdam, Serbia, Dubai, Pune, Bangalore and Hyderabad. With this, Synechron’s Global Accelerator programs now includes over 50 Accelerators for: Blockchain, AI Automation, InsurTech, RegTech, and AI Data Science and a dedicated team of over 300 employees globally. They also demonstrate Synechron’s commitment to research & development, innovation, and upskilling employees.
“Digital Transformation is reshaping the financial services and insurance industries. Synechron is helping our clients to develop strategies to guide their businesses through this change. Our Data Science Accelerators provide a powerful causation platform and business-driven use cases for four very complex financial services challenges. Given the overwhelmingly positive feedback we received for our AI Automation program (Neo), I am confident that the industry is hungry for applied AI solutions and will benefit tremendously from this program,” said Faisal Husain, Co-founder and CEO of Synechron. “Going forward, we will continue to use our FinLabs and unique ‘Power of 3’ approach which combines business knowledge, digital expertise, and technology delivery to develop transformative solutions for the world’s largest banks and insurance companies. This will help them to gain a competitive edge and to accelerate their Digital initiatives.”
The AI Data Science Accelerators include:
- Syn-AI and Causality – is a powerful Data Science platform that ingests large volumes of structured and unstructured data and powers the business case Accelerators. It uses the latest advancements in parallel computing and delivers a scalable platform for rapidly-analyzing massive data collections and identifying meaningful Granger Causal relationships.
- Visual Research – automatically generates personalized buy- and sell-side research reports with automated data collection, synthesis, and analysis, lowering costs while enabling systematic research not possible with manual processes.
- Informed Investing – allows wealth managers to receive alerts for critical events related to the assets they manage such as geopolitical and sector events that impact security prices and buy/sell recommendations.
- Customer Complaints Management – identifies the factors driving customer complaints and prioritizes each claim by the likelihood of being disputed or esclated to enable banks to more quickly and proactively resolve the most critical complaints.
- Credit Risk – empowers banks to manage their credit portfolios proactively, enabling users to drill down into the factors driving likely credit events and to proactively manage individual risks ranked by probability of incurring a specific credit event.