Artificial Intelligence in BFSI Market Recent Study Including Key Players, Applications by 2027

The global Artificial Intelligence in BFSI market size is expected to reach USD 68.23 Billion at a steady CAGR of 36.5% in 2028, according to latest analysis by Emergen Research. Artificial Intelligence (AI) helps in predicting future trends based on analysis of past behavior of customers, and also helps banks to detect patterns in laundering, identify fraud, and make customer recommendations. These advantages are resulting in increasing deployment of AI in banking operations, which is driving revenue growth of the global Artificial Intelligence in BFSI market.

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Competitive Outlook:

The latest research report offers key insights into the strengths and weaknesses of the prominent players using SWOT and Porter’s Five Forces analyses. Market segmentation based on product type, application spectrum, and key regions has been included in the report. The investigative study accurately estimates the market size, market share, and revenue generation over the projected timeframe.

Key players in the market include Amazon Web Services (AWS), Inc., Google LLC, CognitiveScale, Inc., Descartes Labs, Inc., Avaamo, Inc., Intel Corporation, Baidu, Inc., SAP SE, Microsoft Corporation, and Oracle Corporation.

Some Key Highlights in the Report

· In February 2021, FinMkt, which is a loan origination and point of sale financing SaaS provider, announced its partnership with Persistent, which is a global solutions company that delivers enterprise modernization, next-generation product engineering, and digital business acceleration. The partnership will allow small and mid-sized financial institutions to accelerate the digital lending strategies. FinMkt will ramp up its Artificial Intelligence and machine learning capabilities to provide financial institutions with significant insights to shape their credit policies.

· Fraud detection & prevention units in BFSI companies are using Artificial Intelligence to eliminate such activities. Big data is characterized by volume & value and by capturing and processing this in real-time, and Natural Language Processing (NLP) algorithms can detect inconsistencies and discrepancies and ensure fraud prevention.

· Machine learning provides banking companies the opportunity to enhance their business by improving performance and efficiency of BFSI activities. Machine learning attempts to study, identify and classify patterns and make decisions from data collected over time. Machine learning can be used to produce accurate and rapid results, which will drive demand among BFSIs.

Emergen Research has segmented the global Artificial Intelligence in BFSI market on the basis of offering, solution, technology, application, and region:

· Offering Component Outlook (Revenue, USD Million; 2018–2028)

o Software

o Services

o Hardware

· Solution Outlook (Revenue, USD Million; 2018–2028)

o Fraud Detection & Prevention

o Customer Relationship Management

o Chabot

o Anti-money Laundering

o Data Analytics & Prediction

o Others

· Technology Outlook (Revenue, USD Million; 2018–2028)

o Machine Learning

o Context Aware Processing

o Natural Language Processing (NLP)

o Deep Learning

o Others

· Application Outlook (Revenue, USD Million; 2018–2028)

o Risk Management

o Financial Advisory

o Compliance & Security

o Back Office / Operation Customer Service

Regional Landscape:

The report offers a comprehensive analysis of the current growth opportunities for various regions of the Artificial Intelligence in BFSI market, calculating their revenue share over the forecast timeline. Furthermore, the report analyzes the year-on-year growth rate of these regions over the forecast duration. The leading geographic regions encompassed in the report include:

· North America

· Europe

· Asia Pacific

· Latin America

· Middle East & Africa

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Key Questions Addressed:

1. What is the estimated value of the global Artificial Intelligence in BFSI market by the end of the forecast period?

2. What are the fundamental factors propelling the growth of the global Artificial Intelligence in BFSI market?

3. Which are the leading regions in the Artificial Intelligence in BFSI market with the highest market shares?

4. Which regional segment is likely to record the highest CAGR during the forecast duration?

5. What are their strengths and weaknesses of the leading companies in this market?

Table of Content:

Chapter 1. Methodology & Sources 1.1. Market Definition 1.2. Research Scope 1.3. Methodology 1.4. Research Sources 1.4.1. Primary 1.4.2. Secondary 1.4.3. Paid Sources 1.5. Market Estimation Technique Chapter 2. Executive Summary 2.1. Summary Snapshot, 2020-2028 Chapter 3. Key Insights Chapter 4. Artificial Intelligence in BFSI Market Segmentation & Impact Analysis 4.1. Artificial Intelligence in BFSI Market Material Segmentation Analysis 4.2. Industrial Outlook 4.2.1. Market indicators analysis 4.2.2. Market drivers analysis 4.2.2.1. Increasing preferences for personalized financial services 4.2.2.2. Advancement in technology 4.2.3. Market restraints analysis 4.2.3.1. Increase in concern for security. 4.3. Technological Insights 4.4. Regulatory Framework 4.5. Porter’s Five Forces Analysis 4.6. Competitive Metric Space Analysis 4.7. Price trend Analysis 4.8. Covid-19 Impact Analysis

CONTINUED…!

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