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Impact of AI/ML on financial institutions: Nageen Kommu, Digitap

Recently, Nageen Kommu, Founder and CEO, Digitap spoke to Dataquest along the lines of the impact of new age technologies on the industry

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Supriya Rai
New Update
Digitap

The financial industry has undergone significant changes in recent years, largely driven by advances in technology, especially Artificial Intelligence (AI) and Machine Learning (ML). AI and ML have transformed the traditional ways of doing business, enabling companies to analyze vast amounts of data with unprecedented speed and accuracy. Financial institutions are increasingly leveraging these technologies to improve efficiency, enhance customer experience, and gain a competitive edge. As a result, financial institutions are better equipped to make data-driven decisions, mitigate risk, and offer personalized products and services to their customers. Recently, Nageen Kommu, Founder and CEO, Digitap spoke to Dataquest along the same lines.

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DQ: How has the advent of AI and ML impacted the financial services industry?

Nageen Kommu: Artificial Intelligence (AI) and Machine Learning (ML) have transformed the financial services industry, bringing unprecedented opportunities and challenges. Financial Institutions (FI) can now offer personalized and efficient services to clients, thanks to AI-powered chatbots that provide 24/7 support, enhancing customer satisfaction and loyalty. AI and ML have also revolutionized risk management, enabling FIs to identify and mitigate risks in real-time, reducing the likelihood of financial losses. 

The adoption has also brought significant challenges, such as increased competition, cybersecurity risks, and the need for upskilling and reskilling of employees. As a CEO, I feel it is essential to invest in AI and ML to remain competitive and provide customers with the best possible services. The opportunities presented by these technologies are too significant to ignore.

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DQ: How can financial institutions balance the benefits of AI and ML with the need to protect customer privacy and security?

Nageen Kommu: Firstly, FIs should prioritize building a robust data governance framework that outlines how data is collected, processed, and protected. This should include strict data access controls, data retention policies, and data sharing agreements.

Secondly, FIs should ensure that their AI and ML algorithms are designed in a way that protects customer privacy and security. This includes building in privacy-preserving techniques, such as differential privacy, and using secure encryption methods to protect sensitive data.

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Thirdly, FIs should be transparent with their customers about how their data is being used, who has access to it, and how it is being protected. This includes providing clear and concise privacy policies, obtaining explicit consent for data use, and providing customers with the ability to control their data.

DQ: Can you provide examples of how AI and ML are currently being used in the financial services industry?

Nageen Kommu: AI and ML are being used extensively in the financial services industry to improve customer experience, reduce costs, and enhance risk management. Here are some examples of their current use:

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Fraud detection: Financial institutions use AI and ML to detect fraudulent transactions and identify potential risks. These technologies can analyze large amounts of data, including customer behavior patterns and transaction histories, to detect unusual activity and prevent fraud.

Personalized customer service: AI and ML are used to provide personalized customer service by analyzing customer data, including transaction history and online behavior. This data is then used to recommend products and services tailored to individual customer needs and preferences.

Risk management: Financial institutions use AI and ML to manage risks more effectively. For example, these technologies can be used to predict credit risk, assess loan applications, and monitor financial markets for potential risks.

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Chatbots and virtual assistants: AI and ML are used to create chatbots and virtual assistants that can provide customer service, answer questions, and assist with transactions. These technologies use natural language processing to understand and respond to customer inquiries.

Overall, AI and ML are revolutionizing the financial services industry by enabling more efficient and personalized services, enhancing risk management, and improving customer experiences

DQ: Are there any potential risks associated with the usage of these technologies in the BFSI Segment ?

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Nageen Kommu: The use of AI and ML technologies in the BFSI segment can bring several potential risks. Firstly, these technologies can be biased and discriminatory, resulting in unfair outcomes for certain groups of customers or incorrect decisions based on inaccurate data. Secondly, the complexity of AI and ML algorithms can make it difficult to understand how they make decisions, leading to mistrust and uncertainty about the fairness of the decisions made. Thirdly, the use of AI and ML can increase cybersecurity risks, leaving financial institutions vulnerable to attacks that may lead to financial losses and reputational damage. Fourthly, compliance with regulatory requirements can be challenging, with non-compliance resulting in legal and financial penalties. Finally, there may be a skills gap within the organization, hindering the effective use of AI and ML.

To mitigate these risks, financial institutions should prioritize the development of robust governance frameworks, conduct regular audits and testing, ensure transparency in algorithmic decision-making, and invest in upskilling and reskilling employees. By doing so, financial institutions can maximize the benefits of AI and ML while minimizing potential risks. It is essential to balance the opportunities presented by AI and ML technologies with the potential risks to ensure that customers' privacy, security, and trust are not compromised.

DQ: How is Digitap enabling organizations in this space?

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Nageen Kommu: Using AI/ML technologies, Digitap is enabling organizations to cater to the customer segment that has been traditionally ignored by banks and larger NBFCs, owing to poor bureau score. We provide data about these customers to help organizations make informed decisions about the creditworthiness of these individuals and therefore, provide credit to them. This enables financial inclusion as well.

DQ: What is the competitive advantage that you have to offer?

Nageen Kommu: Digitap offers a distinctive solution in the form of a scoring model that enables clients to create customized scoring models, benefiting their customer segments. The primary objective of such a model is to help businesses enhance risk management and reduce fraud. The platform provides a range of on boarding options, including KYC solutions, Optical Character Recognition, document validation, and an RBI-compliant video KYC solution.

Currently, the company is focused on catering to individual customers as its primary customer segment. Digitap aims to gather data about these individuals, which can help fintech clients gain a deeper understanding of their customers and make informed decisions about providing credit to them. By leveraging the power of AI and ML, Digitap can analyze vast amounts of data, allowing clients to customize the scoring model as per their specific needs and requirements.

DQ: What more do you plan to do in this space?

Nageen Kommu: We are currently in the process of developing solutions that will help us move beyond the lending technology and credit underwriting use cases. We want to capture the data of the customers to enable cross-sell and up-sell opportunities for our fintech and NBFC clients, and also expand beyond the BFSI space.

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