AI has played an active role in the financial services industry over the past few years.
According to Deloitte, AI is opening the door to new opportunities and innovation in the financial services industry and its organizations. But what opportunities will financial organizations get from implementing AI? What risks will they face? What benefits does the financial industry gain by using AI on a day-to-day basis?
Developing Financial Products and Building Personalized Offerings
Ilya Smirnov
Open Banking is expanding its financial services offerings, enriching and sharing customer data, while Beyond Banking promotes services that go beyond traditional banking and the sharing of customer data.
When developing personalized offers, it’s especially important to model them based on social status analysis, consumption history, feedback analysis, customer preferences, etc. This is like analyzing the target audience in marketing, but this step is important in all areas related to working with society. Further work includes segmenting customers based on social status and preferences and analyzing customer data in real-time.
Development of Digital Environment and Remote Banking
This application area uses chatbots and virtual assistants, including for:
- Out-of-bank support services; remote banking, which is popular because of the time saved on traveling
- Advice on smart investing and saving in the form of tips in a blog from a financial institution
- Biometric transactions to ensure the safety and efficiency of various operations
- OCR technologies for document recognition and analyzing customers’ facial expressions while processing banking products
Remote banking also incorporates the use of personalized push notifications and app interface development based on customer preferences.
Financial Industry 4.0
As much as society may be frightened by the accelerated digitalization and automation of most processes, it’s worth acknowledging that these technologies have long been firmly embedded in our lives. There is no denying that innovative technologies help scale business processes and increase productivity and competitiveness.
What else makes Financial Industry 4.0 different?
- Embedding banking products in non-banking channels: Creating an ecosystem, increasing accessibility of banking services through widespread adoption
- Total digitalization: Digital mobility, cashless payments, digital registration, biometrics
- Adaptability, flexibility, and scalability: Realize microservice architecture with targeted deployment in cloud infrastructure
- Information security: Cybersecurity, data protection, regulatory compliance, fraud detection
- Big data: Data analysis and modeling, data management patterns, processes, and strategies
- AI and machine learning: RPA, fraud prevention, and predictive analytics
- Hyper-personalization: Adapting to customer behavior, personalized financial services and data-driven product recommendations
- Open Banking API: Data exchange between trusted and verified third parties
But as McKinsey points out, Industry 4.0 is not just about advanced technologies and their widespread adoption and use. It’s necessary for employees to continuously upgrade their skills and develop the missing skills to work with these technologies.
Risk Analysis and Modeling
Unfortunately, no system is 100% safe from cybercrime and fraudulent attacks. Every day we face information leaks, data falsification, and fake news. But using AI in the financial industry can help prevent some of these risks.
AI can: analyze transactions and monitor anomalies in real time; scan the face for transactions; and collect biometrics (voice, eye photos, and DNA for authentication and authorization). Machine learning is needed to detect fraud schemes.
Challenges, Barriers and Risks of AI Implementation
- Anonymization of customer data
- AI project development and operational costs
- Data quality and quantity
- Mismatch of current IT infrastructure with the demands of AI development and implementation
- Implementation of large language models (LLM) in banking
Benefits of AI Implementation
- Synergetic effect from innovation implementation (three-fold return on investment)
- Increase in new customer acquisition rates (15% on average)
- Increase in cross-selling through personalized recommendations (up to 50% on average)
- Reallocation of personnel to more important tasks (up to 30% on average)
- Improved user experience
Ilya Smirnov is head of AI/ML at Usetech. Ilya has a Ph.D. in physics and mathematics and is the author of more than 50 scientific articles in applicable analysis and MDPI-level journals. He is also a visiting professor at the Massachusetts Institute of Technology.
