AI in Banking and how banks are best positioned to reap the maximum benefit
AI and automation technologies are transforming almost every sector. A recent analysis by PWC predicts that AI could contribute a whopping $15.7 trillion to the global economy by 2030. Of this, $6.6 trillion will likely come from increased productivity; $9.1 trillion, from consumption side effects. As the survey pointed out, a large chunk of AI impact would be driven by consumption side effect which is quite evident in the fintech space where both the number of users and the volume of transactions are growing consistently.
Top three AI use cases in fintech space are fraud detection, risk (credit) analysis, and CRM. AI models are deployed to gauge risk and fraud in billion of transactions taking place globally. Pirimid Fintech has developed proprietary models which collects transaction data and map user behaviour and other patterns to flag a transaction as potential fraud. With the application of machine learning, the model can learn to include and remove various data points to refine the fraud detection process.
Secondly, AI is transforming lending from lenders dominated market to borrowers dominated market. With real-time credit profiling using extensive data sets, lenders can capture borrowers who had been left out in the traditional approach. AI based profiling is seamless, faster, and more efficient, which has become a must for all the lenders to adapt to compete with new-age competitors. Use cases are not just limited to lending; it has also been extensively used by businesses to approve a vendor and ascertaining payment terms for customers. When it comes to credit profiling, we at Pirimid believes in an approach which is exhaustive enough to touch all possible data points.
Multiple data points for credit profiling
Source: Secondary sources, expert interviews, BCG
Customer relationship management is another area being transformed by AI. As per a Gartner report, by 2020 consumers will manage 85 percent of their relationships with the enterprise without interacting with a human. Fintech firms are using customer-facing systems such as chatbots or voice systems that are capable of providing human-like interaction with consumers to effectively resolve issues at a fraction of the cost, no matter the time of day.
So what does the future hold for AI?
As mentioned before, AI is already being used by financial institutions and fintech start-ups globally to reduce the risk of fraud and personalizing the customer interaction process through chatbots. But we believe this is just the beginning and the true potential of AI is yet to be seen. AI has already started replacing human investment managers by turning the entire investment process in auto-pilot by Robo-Advisory. Pirimid has helped clients in launching Robo-Advisory platforms which are fully automated right from customer onboarding to developing and operating investment portfolios. In a few years down the line, we believe AI-based smart advisors will assist customers in
- Tracking utility expense pattern and recommend changing plans or changing the providers itself
- Know when they should change credit card providers to save interest cost and meet usage goal
- Add more layers to security by blockchain distributed ledgers and biometric identity tools including facial recognition
- Receive recommendation on the best time to buy a product considering your financial health and product outlook
- Know when it is the right time to take fresh debt or settle the existing one
Banks are in the best position to reap the complete benefit of AI
AI is promising, but it cannot run without data. The success of an AI model depends significantly on the quality and volume of data. The better the data quality, the better the machine learning models would be able to achieve accuracy. This makes a strong case why banks have an enormous advantage for now; they have a bulk of consumer data sitting in transaction history and account records. According to recent research by IDC, the banking industry is expected to spend $79.2 billion on AI-enabled solutions in 2022, with a CAGR of 38% over 2018-2022. Most of the investment will go on fraud detection and risk management, credit risk assessment, AI chatbots, and customer engagement.
Top AI Use Case in fintech based on 2019 market share
Automated customer service agents, sales process recommendation and automation, and automated threat intelligence and prevention systems will get the
Various research has indicated that AI is going to be a powerful tool, both strategically and financially. There are enormous benefits for banks considering high-quality data they have on their millions of customers. Most banks consider technology a crucial aspect as 32% of them are already using AI technologies. Solutions such as credit profiling model, early warning system and smart data lake, which offers high quality and richness of data through multiple sources are among the most AI based implementations in 2019.
One of the challenge most of the global banks facing are to acquire and retain AI talent. Large tech firms like Amazon and Google are not only best in alluring best talents, but they also have higher profit-per employee ratio, which allows them to offer high salaries and excellent perks. Even behemoths like Bank of America and JPMorgan Chase are unable to compete against the tech giants in AI talent war. Hence, AI solution providers are the best alternative for banks to consider for their next AI implementation. We at Pirimid Fintech has the best class technology experts with deep expertise in AI and ML to deliver even the most complex aspects of banking solutions.
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