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Make Your Own AI for Financial Services

AI is Expanding the Opportunities for Financial Services Companies

Executive Summary

The financial services industry is continuously innovating and advancing new technologies in the pursuit of increasing their customer base and finding new opportunities. They are using artificial intelligence (AI) for a number of scenarios that advance their businesses including personalized customer services, risk management, fraud detection and anti-money laundering while adhering to regulatory compliance. This is happening across the board and in all segments of financial services – capital markets, commercial banking, consumer finance and banking, and insurance. Moreover, PWC estimates that the incremental revenue from monetizing data could potentially be as high as US$ 300 billion per year., the open source leader in AI, is empowering leading financial services companies to deliver AI solutions that are changing the industry.

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AI is Expanding the Opportunities for Financial Services Companies

Improve Customer Experiences –

Consumers have come to expect personalized experiences in all facets of life. AI can be used in financial services to segment customers and drive personalized offers that increase conversion and retention in retail banking. Automated agents can help customers answer questions and solve issues on their own without talking to a person, a key to attracting and engaging millennials. Automatically alerting customers to fraudulent activity and taking action can increase customer satisfaction and reduce the likelihood of churn.

Drive Accurate Decisions –

Speed is often discussed as a critical advantage of AI driven automation in areas like equities trading. However, for most financial services companies, the accuracy of decisions can be more important. For example, quickly determining fraudulent transaction on a credit card is important, but inaccuracy in this process can lead to locked or replaced cards for valuable clients, a key customer satisfaction issue resulting in increased churn risk.

Ease Regulatory Compliance –

The rapidly changing regulatory landscape can be very challenging for financial institutions. AI can help companies comply with applicable laws in areas like anti-money laundering, customer data privacy, and asset management. AI systems are superior in many of these areas because they eliminate human error and can detect illegal activity that would be nearly impossible for people to recognize.

Use-cases in Financial Services powered by AI

Why for Financial Services – AI to do AI offers an award-winning automatic machine learning platform in Driverless AI and has been recognized as an industry leader in the Forrester New WaveTM: Automation-Focused Machine Learning Solutions, Q2 2019. H2O, open source, is already being used by hundreds of thousands of data scientists and is deployed at over 18,000 organizations across nearly every industry.

H2O Driverless AI empowers data scientists, data engineers, mathematicians, statisticians and domain scientists to work on projects faster and more efficiently by using automation to accomplish tasks that can take months and can now be reduced to hours or minutes by delivering automatic feature engineering, model validation, model tuning, model selection and deployment, machine learning interpretability, timeseries, NLP, automatic pipeline generation for model scoring and automatic documentation with reason codes, and now bring your own recipes and model operations and administration.

The new innovations and capabilities will enable customers to accelerate their AI transformations in the Financial Services industry

1. Anti-Money Laundering (AML):

AML programs in capital markets and retail banking extensively deploy rules-based Transaction Monitoring Systems, spanning areas like monetary thresholds and money laundering patterns. Bad actors are able to learn these rules over time and change their methods to avoid detection. AIbased behavioral modeling and customer segmentation can be more effective in discovering transaction behaviors and identify behavioral patterns and outliers indicating potential laundering.

2. Credit-risk scoring:

Mortgage or auto loan lenders have relied heavily on past credit history or FICO score for credit scoring. Sophisticated machine learning models can understand the credit-worthiness with additional data. Consumers that were deemed ineligible in the past, can be given credit, expanding the number of credit customers while providing a more precise prediction of risk.

3. Fraud Detection:

Alternative payment modes such as mobile wallets and in-app payments are driving increased payment volumes across both open loop and closed loop payments. The convenience of online payments confers anonymity which increases the risk of fraud at a scale that continues to grow. Fraud detection is now an AI domain, and algorithms spanning classical machine learning to neural networks are being leveraged to fight fraud.

4. Personalized Consumer Experience:

Consumer banking generates petabytes of data every year and consumers want an experience specifically tailored to their needs. Forward looking banks strive to serve their clients when and where they need using AI-powered Chatbots for daily or banking needs. Knowing their customers from a 360-degree perspective allows banks to anticipate what financial products they might need and proactively offer customized products to them.

Customer Case Studies

  • Multinational financial services company
  • Vision Banco, a financial institution

The world-class data science team uses H2O Driverless AI for credit risk scoring, compliance, customer assistance, and market risk analysis in capital markets. Moreover, with a corporate-wide focus on risk mitigation and regulatory compliance, the H2O Driverless AI platform is instrumental with its machine learning interpretability capability

The use-cases Vision Banco cares about spans credit scoring, default prediction, fraud detection, churn prediction and recommendation engines. Having used H2O Driverless AI, they reduced the model process from months to weeks, and additionally, they are able to double the propensity for a customer to consider additional credit offerings.

Win with AI – Get Started Today

AI is critical to success in the financial services industry. Driverless AI enables financial services companies to quickly build personalized banking experiences, fraud and money laundering models, improve employee productivity and more.