Ritesh Srivastava, BharatPe on top AI trends for fintech industry to watch in 2023, CIO News, ET CIO
By-Ritesh Srivastava,
Over the past few years, the global fintech industry has been greatly impacted by the rise of artificial intelligence (AI) and machine learning (ML).
As industries become increasingly automated and digitally transformed, AI and ML technologies are being used to build various financial services, including secure digital transactions and personalized financial advice. According to industry data, the global AI in fintech market size is expected to reach USD 26.67 billion by 2026, with a CAGR of 23.17% from 2021 to 2026.
Here are some of the top AI trends in the fintech industry to watch for in 2023:
The machines will take over humans (literally) – The rise of multilingual chatbots.
In the coming months, we will see chatbots use machine learning and AI to handle common questions from customers in their local languages and dialects, which call centers often spend significant time and resources answering.
By analyzing big data, fintech companies can identify specific customer questions and interaction patterns and use this information to train their chatbots. In addition to answering pre-programmed questions, sentiment analysis allows chatbots to understand customers’ relationship with financial services, leading to improved customer satisfaction and process automation.
AI will take center stage in the decision-making process
Credit decision making is often one of the first areas to adopt AI. According to McKinsey, AI works with structured and unstructured data to make more precise credit decisions and positively impacts the credit approval process, including processing time and percentage of applications approved.
There are three main ways that AI-driven credit decision-making will be adopted in 2023:
- Credit Eligibility: AI will analyze many consumers and accurately determine whether a particular client is eligible for a loan
- Limit assessment: AI algorithms will automate the determination of the maximum loan limit based on various factors
- Pricing: AI-powered fintech can offer competitive pricing and adjust prices based on changes in the market
Conventional credit risk analysis often uses complex statistical models that assume formal relationships between functions in the form of mathematical equations. In contrast, artificial intelligence (AI) uses machine learning (ML) methods that can learn from data without requiring rule-based programming. AI uses several types of classical ML algorithms and deep learning techniques, including the Random forest method, Support vector machine (SVM), K-nearest neighbors (KNN) and Neural networks (NNs)The role of CDO/CDS will become more prominent
As fintech companies seek to make data a more central part of their business, the role of Chief Data Officer (CDO) or Chef Data Scientist (CDS) is becoming increasingly strategic. The CDO/CDS is responsible for providing insights that enable data-driven decision making and to help assess the impact of data on the overall functioning of the organization. Currently, a framework for this assessment has not yet been established, but the CDO/CDS is well positioned to take on this role.
Deploying data at scale and improving technical maturity can have several implications. The CDO/CDS will play a critical role in adapting these efforts to the evolving regulatory landscape and helping to establish an open and transparent data culture that transcends organizational and functional silos.
Defi and blockchain are coming back with a bang
Decentralized finance (DeFi) is an emerging financial technology that is based on secure distributed ledgers, similar to those used by cryptocurrencies.
Decentralized finance (DeFi), which aims to make peer-to-peer transactions instant and free, and addresses the current challenges of costly, slow international payments, is expected to be back in vogue.
DeFi’s truest potential to serve users lies in its ability to serve applications as well as ecosystems. In addition, the versatility of DeFi blockchains makes them the perfect infrastructural tools to power Web 3.0 ecosystems that need trustless on-chain financial services and deep liquidity.
Conclusion
It may seem like AI is a future technology, but it has been around for over 50 years. The first artificial intelligence was introduced in 1956, and now is the time for companies to fully understand its potential and use it globally. AI can make Fintech businesses more successful, and companies that don’t adopt it may struggle to keep up with the competition. Getting on board with AI now will give them a competitive edge and allow them to get a head start in the race. With AI, companies will also be able to build best-in-class fintech products that are new, safe and secure.
The author is Chief Data Scientist at BharatPe.
Disclaimer: The views expressed are solely those of the author and ETCIO.com does not necessarily subscribe to it. ETCIO.com shall not be liable for damages caused by any person/organization directly or indirectly.
