Financials

Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry?

As a Pre-Sales Lead specializing in Gen AI & Cloud, I bring extensive experience in leveraging cutting-edge technologies for business solutions. At Tredence Inc., I've been actively involved in designing and delivering impactful partner strategic cloud solutions, focusing on AI and GenAI applications for BFSI.

My role involves ideating, designing, and launching new products and accelerators built on platforms like Snowflake and Databricks, which often incorporate AI and GenAI capabilities. I lead solution design for AI-driven projects and empower teams through knowledge sharing in these areas. My experience at PwC and NTT Data also involved integrating AI solutions into cloud and IT architectures for various sectors, including BFSI and government.

Q2. Are there recent or planned investments in gen AI technology to improve the operational efficiency of the BFSI?

As per Mckinsey's report of 2023- Recent investments in generative AI aim to enhance operational efficiency in the BFSI sector. Generative AI could add $2.6 trillion to $4.4 trillion annually, with 75% of the value coming from customer operations, marketing, sales, software engineering, and R&D.

Banking could see an additional $200 billion to $340 billion in value annually. Generative AI automates lower-value tasks, enhances knowledge worker productivity, and drives workforce transformation. While specific investment figures aren't mentioned, the significant potential value indicates a likely increase in investment in this technology to improve operational efficiency and customer interactions in the BFSI sector.

Q3. What is the current demand/volume in the gen AI technology market? How are key players adapting?

Current demand/volume specifics answered in the previous question, regarding adapting: Banks and Insurance companies are Investing heavily in research and development to improve the capabilities of generative AI technology.

Some general use cases:

• Expanding product offering

• Focus on customer experience- Investing in AI-powered chatbots to improve customer service and experience- personalized services and enhanced engagement.

• Enhancing risk management capabilities using generative AI-powered predictive analytics

• Automating back-office processes such as data entry, compliance, and reporting

• Improving customer insights using generative AI-powered data analytics.

• Claims processing and adjudication, Underwriting, Policy administration and management

Examples

JPMorgan Chase: Investing in AI-powered chatbots and predictive analytics

Bank of America: Enhancing customer experience through AI-powered virtual assistants

Citigroup: Investing in AI-powered risk management and compliance solutions

Lemonade: Using generative AI for claims processing and underwriting

Q4. Who are the main players in the gen AI, and what market share or position does each represent?

The generative AI market is led by key players offering a range of solutions and services. Some of the main players and their focus areas:

OpenAI: Known for its GPT series, OpenAI is a leader in natural language processing and generative AI.

Microsoft: Offers a range of generative AI solutions, including text and image generation, through its Azure platform.

AWS: Provides generative AI services, such as text and image generation, through its cloud platform.

Google: Through its Google AI and DeepMind subsidiaries, Google develops generative AI solutions, including text and image generation.

Adobe: Offers generative AI-powered creative tools, such as Adobe Fresco and Adobe Photoshop.

Other notable players in the generative AI market include:

Anthropic: Focuses on developing safe and steerable AI models.

Midjourney: Offers a generative AI platform for image and video creation.

Insilico Medicine: Develops generative AI solutions for drug discovery and development.

Lumen5: Provides a generative AI platform for video creation and content generation.

AI21 Labs:  Develops generative AI solutions for natural language processing and content generation.

Q5. What are the best growth opportunities in the market, and why? 

The generative AI market presents significant growth opportunities in the Banking, Financial Services, and Insurance (BFSI) sector. AI-powered customer service, risk management, and compliance are key areas of focus.

Generative AI can enhance customer experience through personalized financial advice and portfolio management. It can also improve risk assessment and fraud detection, reducing losses and improving overall risk management.

Additionally, generative AI can automate compliance reporting and monitoring, reducing the administrative burden on BFSI institutions. In insurance, generative AI can streamline claims processing and underwriting, improving efficiency and reducing costs.

Overall, generative AI has the potential to transform the BFSI sector, enabling institutions to improve customer satisfaction, reduce costs, and drive revenue growth. As the technology continues to evolve, BFSI institutions that adopt generative AI solutions will be well-positioned to stay competitive and capitalize on new opportunities. By embracing generative AI, BFSI institutions can unlock new levels of innovation, efficiency, and growth.

Q6. Are there any mergers and acquisitions/consolidations that are expected in the gen AI industry?

Recent Acquisitions

There have been recent acquisitions in the generative AI industry, such as MosaicML being acquired by Databricks for $1.3 billion and Casetext being acquired by Thomson Reuters for $650 million.

Predictions for Future Acquisitions

Big tech companies like Google and Meta are likely to make major generative AI acquisitions, while companies like Apple and Amazon may not enter the generative AI M&A race.

Q7. If you were an investor looking at companies within the space, what critical question would you pose to their senior management?

As an investor, I would ask the following critical questions to senior management:

Competitive Advantage

How does your generative AI technology differentiate from others in the market?

Scalability

What is your strategy for scaling your generative AI solutions to meet growing customer demand?

Data Quality and Availability

How do you ensure access to high-quality, relevant data to train and fine-tune your generative AI models?

Business Model and Revenue Streams

What is your business model for generating revenue from generative AI solutions?

Long-term Vision

What is your long-term vision for the company's role in the generative AI market, and how do you plan to maintain leadership and innovation?

This article was contributed by our expert Sparsh Arora