Personal Finance, Reimagined By AI
As AI technology advances, it's becoming increasingly integrated into personal finance, streamlining processes and enhancing customer experiences
Artificial intelligence (AI) seems like a new-age thing, but the term ‘artificial intelligence’ was first used by John McCarthy, a mathematics professor at Dartmouth College, in 1955. But one has to admit that after November 30, 2022, it has become a household name after ChatGPT brought generative AI to our daily lives.
Imagine teaching a computer to think and act like a human. That's essentially what artificial intelligence is. It's the science of creating intelligent machines that can perform tasks that typically require human intelligence, like understanding language, recognizing patterns, and making decisions.
“When discussing AI, it's crucial to understand its core principles. While AI can automate many tasks, true AI involves more than just following predetermined rules. It requires the ability to learn and adapt based on new information, much like a human,” says Arun Ramamurthy, head, digital Transformation, Andromeda, a loan distributor.
In this story, we look at how AI is slowly but surely becoming an integral part of your personal finance lives.
AI In Banking
According to McKinsey’s 2023 banking report, generative AI could enhance productivity in the banking sector by up to 5 per cent and reduce global expenditures by up to $300 billion. Naturally, when it results in cost savings for the banks, that is passed on to the customer as well. Plus, customers of a bank get benefited in other ways too. Here, let us touch upon customer cyber security, which is a key concern for the banking industry because of the sensitive data it handles.
The financial sector accounts for more than 30 per cent of all cyber-attacks and can be termed as the most targeted sector by cyber hackers. “An early warning system leveraging AI to detect malware, trojans and phishing are actively adopted by the banks,” says Jon O’Donnell, Chief Operating Officer, Acuity Knowledge Partners, a provider of bespoke research, analytics, and technology solutions to the financial services sector.
AI In Insurance
“When it comes to insurance, AI for customer experience definitely is all about simplifying the technicalities of a product to the customer, make the customer more aware during the buying process and provide a seamless experience with the insurer during the policy tenure without having no or minimum dependency on reaching out through multiple channels,” says Krishnan Badrinath, Head Technology - Innovation, Presales and Automation, TATA AIG General Insurance.
If we take the case of car insurance, AI's role in insurance extends to automating claims processing. “For example, AI can now handle the entire process of assessing vehicle damage through smartphone photos, providing quick and accurate assessments without needing human intervention, which significantly speeds up claim settlements,” says Santosh Bhat, Head of Data Science, at PolicyBazaar, an insurance aggregator.
AI has transformed customer service in insurance by integrating advanced chatbots and voice bots. “These tools can handle a large volume of frequently asked questions and routine tasks, allowing human agents to focus on more complex issues, thus streamlining the customer support experience,” says Bhat.
AI In Loans
AI is revolutionising the loan approval process by analysing vast amounts of data to assess a borrower's risk profile more accurately. This enables lenders to make faster and more informed decisions, reducing the time it takes for customers to receive loan approvals.
“We implement AI across all processes, starting from loan offers and approval of that loan and then the process. To provide you with the best loan offers, we combine various data points, including your income and credit score. We also incorporate data from banks, such as their credit scoring models. By analysing this data using our machine learning model, we can generate offers that have a high probability of approval,” says Mukesh Sharma, chief technology officer, Paisabazaar.com, an online marketplace for financial products.
AI In Investments
AI is increasingly being used in trading. AI trading or trading aided by AI is transforming the investment landscape by uncovering hidden insight, whether it is sentiment analysis on social media platforms like twitter or reddit etc. or dynamic portfolio optimization. Not just trading, AI has transformed investments as well.
"Traditionally, stock analysis involved generic recommendations, but modern AI has advanced to evaluate over 1,500 stocks daily. This technology allows for a more nuanced and customised approach to investing, offering insights based on real-time data and trends, rather than relying on broad, one-size-fits-all advice from earlier methods,” says Sarvjeet Singh Virk, Co-founder and MD, Shoonya by Finvasia.
In fact, Share Samadhan, an unclaimed investment recovery advisory, uses AI at each step to smoothen the process of recovery regarding unclaimed assets.
AI In Financial Advice
AI-driven financial advice has shifted the world from the traditional algorithm based systems that have been used for a long time. “Algorithmic financial advice models work on fixed, rule-based processes such as predefined investment strategies or enabled risk profiles but now AI can adapt and personalise. AI systems don't just execute based on preset conditions, but they learn from the vast amounts of real-time data, identify emerging patterns, and adjust recommendations accordingly,” says Abhinav Nayar, Founder and CEO Mool.AI, a company that uses AI to help people make smart financial decisions.
This dynamic approach enables AI to offer more holistic and forward-looking financial guidance customised to individual needs, preferences, and market conditions, AI-driven systems continuously refine their understanding, making them more responsive to shifts in economic trends or personal financial circumstances, which Algorithm based models can’t.
In fact, going ahead we can expect AI to be your financial advisor. Says Rohit Pandharkar, Partner, Technology Consulting, EY India, “Conversational advisory is where you can go and describe your situation and ask for advice. For example, if you have received a bonus during Diwali, you may want to know how to invest it. Such answers are in conversations, either with your relationship advisor at a bank, with your mutual fund agent, your insurance agent or with your financial planner. All this will change through conversational advisory agents.”
So large language models (LLMs), a type of artificial intelligence (AI) that can perform natural language processing (NLP) tasks, have created the concept of conversational advisor in personal finance. As we go ahead we can expect to see more sophisticated versions of such tools.
AI In Customer Service
One of the traditional models for customer service is a call centre where the customers prefer having a conversation with a customer service agent to get the policy service request fulfilled. “We have already enabled the call centre agents with AI powered chatbot that helps the agent to answer the exact query of the customer regarding the policy, product and process for a particular transaction without the agent having to use or browse through multiple documents and increasing customer wait time. The same will definitely be enabled for the customers as well where the customers can chat with the AI BOT and have all the required clarity,” says Badrinath.
Velocity, a cash flow financing platform has launched Vani AI, a solution that uses artificial intelligence to automate customer calls for financial institutions. Trained on specific company data, Vani can have natural conversations with customers.
The AI Dark Spots
It is important to understand that using AI in its day to day operations may sound lucrative, but may not be a simple decision for every financial institution to make. A brokerage Business World spoke to admitted this, “We're still in the development stage for our AI strategy. In fact, it is currently more expensive than manually selecting stocks as the information processing requires very high computing bandwidth.”
“Also, the implementation of AI often requires significant amounts of data, which can be a challenge for many lenders, especially smaller fintech companies,” says Ramamurthy.
AI in personal finance brings significant benefits but also raises ethical concerns such as bias and privacy risk. To address these challenges, responsible AI practices are crucial. This involves ensuring fairness by eliminating biases from algorithms, maintaining transparency in AI decision-making processes, and establishing accountability to hold developers responsible for any harm caused. Protecting privacy is essential to secure sensitive financial data, and human oversight is necessary to retain ultimate control over AI systems, ensuring they are used ethically and effectively.
