Management of Artificial Intelligence in Financial Services
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Educational Qualification *
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Contact Number *
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Do you think the following factors are enabling management of artificial intelligence in financial services? If yes, rank the following on a scale of 0 to 10 (0 = least enabling factor, 10 = Most enabling factor) *
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24/7 Availability
Advent of mobile technology
Automation
Better computing power
Capital
Cheaper Storage
Collective Solution for shared Problem
Competitive Advantage
Corporate image
Create value for customers
Customer Retention
Data availability
Digitization
Enhance service quality
Enjoyment with innovation
Faster processor speeds
Financial Inclusion
Fraud Detection and Prevention
Governance
Greater insights into data
Incentives
Innovators and early adopters
Less Human Intervention
Long-term Capability
Lower hardware costs
Maintain Regulatory Compliance
Managerial Support
Monitor back-end processes
More Accuracy
Open source software and libraries
Opportunity for Cost Reduction
Opportunity for profitability
Peers
Perceived Usefulness
Personal innovativeness
Personalised Financial Services
Predictability
Proliferation of open-source software
Real time data
Regulatory Compliance
Robust and rapid processing needs
Save employees’ time
Self-Driving Finance
Serve numerous customers simultaneously
Social Network
technical support
Technological Development and Innovation
Timeliness to access data
Understand Customer Behaviour
Do you find any enabling factor for management of AI in financial services other than mentioned above? If yes, kindly mention them along with their rankings. *
Do you think the following factors are challenging management of artificial intelligence in financial services? If yes, rank the following on a scale of 0 to 10 (0 = least challenging factor, 10 = Most challenging factor). *
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Acquisition cost
Addressing security and privacy issues
Biasness
Breach for Personal Data
Convincing top management to deploy AI
Cost for hiring specialists
Cost for staff training
Customers’ readiness and willingness to be served by machines
Cyber Attacks
Expensive Technology
Fear of failure
Getting the AI system to interpret questions correctly
High cost of investment
High resource cost and low awareness for adopting AI in business processes
Identifying the right AI vendor
Immaturity of industry standards around AI based systems
Inadequate availability of AI expertise, manpower and skilling opportunities
Installation cost
Job Replacement
Lack of Credible and Quality Data
Lack of required skills and knowledge
Lack of enabling data ecosystems
Limitation in Budget Resources
Low intensity of AI research
Maintenance cost
Putting employees outside comfort Zones
Regulatory compliance
Requirement of reengineering of the Processes
Resistance to Change
Rewriting the service operations manuals
Out-dated data sets
Software update cost
Structuring the data according to AI based system
Training of staff
Training the deep learning systems to work efficiently with less data
Unclear internal ownership of emerging Technologies
Unclear privacy, security and ethical regulations
Uncertainty about responsibility
Do you find any challenging factor for management of AI in financial services other than mentioned above? If yes, kindly mention them along with their rankings. *
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