Uses of AI in Finance

Artificial Intelligence is taking the financial services industry by storm. Almost every company in the financial technology sector has already started using AI to save time, reduce costs, and add value.

Features

Risk Management

  1. PayPal has been able to boost security by leveraging deep learning technology. PayPal's fraud is relatively low at 0.32% of revenue, a figure far better than the 1.32% average that merchants see.
  2. While a linear model can consume 20-30 variables, deep-learning technology can command thousands of data points.

AI Trading

  1. For years, investment management companies have relied on computers to make trades. Around 9% of all funds, managing $197 billion, rely on large statistical models built by data scientists.
  2. However, these models are often static, require human intervention, and don't perform as well when the market changes. Therefore, funds are increasingly migrating towards true artificial intelligence models that analyze large volumes of data and continue to improve themselves.
  3. In 2000, Goldman Sachs' US cash equities trading desk in its New York headquarters employed 600 traders. Today, it has two equity traders, with machines doing the rest.

Robo-advisory Services

  1. For investors, robo-advice can offer up to 70% in cost savings in certain services.
  2. Some established investment firms are buying existing robo-advisors, such as Invesco's acquisition of Jemstep and Blackrock's purchase of FutureAdvisor. Others are even creating their own robo-advisors, such as FidelityGo and Schwab's Intelligent Advisory.
  3. 77% of wealth management clients trust their financial advisors and 81% indicate that face-to-face interaction is important.

Insurance Underwriting and Claims

  1. A PWC report predicts that AI will have automated a considerable amount of underwriting by 2020, especially in mature markets where data is available.
  2. In a 2013 Oxford study analyzing over 700 professions to determine which were most susceptible to computerization, insurance underwriters were included in the top five most susceptible.
  3. Underwriting may leverage not only machine learning but also wearable technology and deep learning facial analysis technology.

In Q2 '17, global investment in fintech companies hit $8.4 billion across 293 deals

- Pulse of Fintech Q2 2017 (KPMG)

Don't miss this huge opportunity

Benefits of AI in Finance Industry

Benefits of AI in banks and credit unions are widespread, reaching back office operations, compliance, customer experience, product delivery, risk management and marketing to name a few.

Fraud detection

Meeting regulatory requirements

Lowering costs and increasing revenue

Improving the customer experience

Boost customer engagement

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Read our report on AI trends in Banking

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