AI is enabling brighter financial futures for consumers and businesses. From traditional banks to new fintechs, the financial services industry is powering use cases with AI such as preventing payments fraud, automating insurance claims, and accelerating trading strategies.
The latest episode in the I AM AI video series brings these technology stories to life by featuring global financial enterprises and startups transforming banking, insurance and payments.
Automating Insurance Claims and Document Processing
Ping An, China’s largest property and casualty insurer, uses NVIDIA GPU-powered image analysis and AI to rapidly calculate damages caused by vehicle collisions, automate claims handling for simple and clean cases, estimate costs and identify fraudulent claims. This automated experience leads to better customer service, fewer cases of insurance fraud and more efficient delivery of services.
CAPE Analytics, a computer vision startup, is transforming the property insurance industry by analyzing geospatial data to inform more accurate underwriting decisions and mitigate wildfire disasters. The NVIDIA Inception member uses AI to produce detailed data on the vegetation density, roof material and proximity to surrounding structures — more accurately calculating risk and helping homeowners take actions to reduce potential property damage.
Applica, a fintech, deploys progressive AI to streamline text-based workflows that deliver better-than-human performance. Its robotic text automation platform uses NVIDIA GPUs for training machine learning models and inference in production. This eliminates up to 90 percent of manual errors, boosts document turnover rate to less than one second, and reduces physical workforce effort by up to 75 percent.
Banks Adopt AI to Accelerate Model Training and Cut Costs
Bank of Montreal runs complex derivative models to find fair prices for financial contracts used in valuation and risk management. These AI-informed models — trained by Riskfuel, a Toronto-based startup and member of NVIDIA Inception, on 650 million data points and deployed for inference on NVIDIA A100 or T4 Tensor Core GPUs — can drive higher trade flows, generate new risk insights and lead to better product design and selection for Riskfuel’s clients.
Capital One uses Dask and RAPIDS, a suite of GPU-optimized libraries for accelerating data science and analytics pipelines, to achieve 100x improvement in model training times and reduce costs by nearly 98 percent. Its team of data scientists and machine learning engineers use accelerated and distributed data processing for financial and credit analysis.
AI Virtual Assistants Improve the Customer Experience
Square, a global leader in payments, powers its virtual assistant, Square Assistant, using conversational AI to schedule appointments with new and returning customers. These AI models are trained using large hyperparameter jobs running on NVIDIA GPUs in AWS. Once they’re trained and ready for deployment, Square found that inference jobs on large models such as RoBERTa run 10x faster on the AWS GPU service than on CPUs.
Intuit uses conversational AI and intelligent AI assistants to empower financial futures for individuals, self-employed workers and small business owners. The company uses AI technologies, such as knowledge engineering, machine learning and natural language processing and understanding, to provide targeted and personalized assistance with virtual experts, automate financial documents processing, and even forecast cash flow for small businesses.
Funding the Future of Financial Services with AI
NVIDIA’s full-stack accelerated computing platform enables banks, traders, payments providers, insurers and fintechs to deliver enhanced offerings that boost lifetime value for customers and reduce operational costs across their and their customers’ businesses.