Artificial Intelligence Applications for Financial Services

A quantitative assessment of the market opportunity in finance enterprises for AI software used for sales, marketing, operations, investment, risk, and regulatory compliance. It analyzes 24 use cases driven by five AI technologies across five global regions.

Report Details

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Pages: 49
Tables, Charts,
     & Figures:
25
Publication Date: 3Q 2020
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The intense competition for customers and business—combined with the impact of the COVID-19 pandemic—is helping to accelerate the timing of artificial intelligence (AI)-powered automation projects across customer-facing, backend, and fraud and security processes. Demand for self-service and always available access to new products and existing financial accounts has led to a growing utilization of AI and machine learning (ML) solutions. These solutions allow more robust engagement with customers, more efficient processes and operations, and a more streamlined approach to doing business.

The financial services industry has been an early adopter of analytics and big data for years. Banks, credit unions, investment firms, and fintech companies have been among the leaders in utilizing AI. But mindful of deployment costs, ROI, and regulatory concerns, AI is also being rolled out by enterprise financial services companies. The financial services industry is projected to incorporate AI technology over a number of use cases that are focused on process optimization, predictive analytics, customer interactions, anomaly detection, and customer experience. Omdia forecasts that AI software revenue for financial services use cases will grow from $2.0bn in 2020 to $9.1bn in 2025.

This Omdia Focus Report looks at the following market issues surrounding AI applications within the financial services industry: drivers, barriers, revenue forecasts, key players, and use cases. Omdia identifies 24 use cases that will affect the industry between 2020 and 2025 and provides in-depth analysis of each use case, covering the applications, technologies, and metrics for success. The report and forecast also address the impact of the COVID-19 pandemic, which has spurred more demand for AI and automation, on the financial services market.

Key Questions Addressed:

  • How will data privacy and security issues affect the way AI technology will be deployed within financial services companies?
  • How are vendors responding in terms of how they market, sell, and deliver AI solutions?
  • What KPIs or other metrics are being used to define success with AI in financial services companies?
  • Which financial services use cases will generate the most software revenue throughout the forecast period, and how will this mix vary among world regions?
  • Which AI use cases will be deployed within the finance, insurance, and investment subindustries?
  • How are financial services regulations, privacy concerns, and data security issues affecting the way AI solutions are delivered and utilized?

Who Needs This Report?

  • AI technology companies
  • Financial services companies
  • Banks, credit unions, brokerage firms, institutional investors, and hedge funds
  • Software companies
  • Service providers and systems integrators
  • Industry organizations
  • AI and financial services consultants
  • Investor community

Table of Contents

Executive summary
Overview
Market drivers
Market barriers
Omdia view
Market forecast highlights

Market issues
Market drivers
– Reduced costs and improved scalability and efficiency
– Increased demand for optimization and automation
– Plethora of data available
– Strong demand for more data-driven decision-making and predictions
– Increasing desire for providing more personalization
– Desire for increased security and privacy
Market barriers
– Unrealistic expectations surrounding AI
– Lack of experienced talent
– Algorithmic fairness questions
– Change management issues
Use cases
– Finance use cases
– Customer service & marketing VDAs
– Risk assessment and compliance
– Fraud detection and mitigation
– Video surveillance
– Automated report generation
– Personal financial advisor
– Credit scoring and loan analysis
– Tax filing and processing
– Biometric identification
– Employee expense management
– Voice/speech recognition
– Face recognition
– Machine/vehicular object detection/identification/ avoidance
– Human emotion analysis
Insurance use cases
– Patient data processing
– Claims processing
– E-commerce & sales VDAs
– Insurance underwriting & risk assessment
– Converting paperwork into digital data
– Image analysis for damage assessment
Investment use cases
– Algorithmic trading strategy performance improvement
– Financial search engine
– Market intelligence and data analytics for investment
– Satellite imagery for geo-analytics

Market ecosystem
Market recommendations
– General AI development platforms
– Predictive analytics/operations
– Investment/asset management specialists
– Regulatory/compliance tech providers
– Credit scoring/risk assessment providers
– VDA providers
– Investment companies
– Financial services companies/banks/consumer-facing companies
– Insurance companies

Key industry players
AlphaSense
Artificial Solutions
Behavioral Signals
Boosted.ai
Clinc
DataRobot
Interactions
Kavout
LenddoEFL
Personetics
Symphony Ayasdi
Underwrite.ai
Zest AI

Market forecasts
Forecast methodology
Total AI software revenue for financial services use cases
– Finance AI use cases
– Investment AI use cases
– Insurance AI use cases
Financial services AI software revenue by use case
Financial services AI software revenue by region
Financial services AI software revenue by horizontal
Recommendations

 

List of Charts, Figures, and Tables

Figures
  • Total financial services AI software revenue by region, world markets: 2020–25
  • Representative AI financial services ecosystem
  • Total financial services AI software revenue by use case, world markets: 2020–25
  • Total financial services AI software revenue by subindustry, world markets: 2020–25
  • Finance AI software revenue by use case, world markets: 2020–25
  • Investment AI software revenue by use case, world markets: 2020–25
  • Insurance AI software revenue by use case, world markets: 2020–25
  • Top eight financial services AI software use cases by revenue, world markets: 2020–25
  • Total financial services AI software revenue by region, world markets: 2020–25
  • Top four financial services AI software use cases by revenue, North America: 2020–25
  • Top four financial services AI software use cases by revenue, Europe: 2020–25
  • Top four financial services AI software use cases by revenue, Asia Pacific: 2020–25
  • Cumulative financial services AI software revenue by horizontal, world markets: 2020–25
Tables
  • Financial services AI use cases, listed by revenue
  • Finance use cases, listed by revenue
  • Insurance use cases, listed by revenue
  • Investment use cases, listed by revenue
  • Total financial services AI software revenue by region, world markets: 2020–25
  • Total financial services AI software revenue by use case, world markets: 2020–25
  • Financial services AI software revenue by use case, North America: 2020–25
  • Financial services AI software revenue by use case, Europe: 2020–25
  • Financial services AI software revenue by use case, Asia Pacific: 2020–25
  • Financial services AI software revenue by use case, Latin America: 2020–25
  • Financial services AI software revenue by use case, Middle East & Africa: 2020–25
  • Financial services AI software revenue by horizontal, world markets: 2020–25