Predicting financial growth with statistical modeling started with Bachelier’s ‘The Theory of Speculation’. The primitive form of AI and its application started way back in 1900. Gradually it was taken over by Bayesian statistics followed by parallel strategic computing systems, Expert Systems to interactive & responsible modern AI systems.
Tech integration is not new to finance, but AI had a slightly different start. It was presumed that an automation system is only can bridge mundane limitations, making way for chat-bots as support functions, a 24*7 answering machine, responding to endless client queries at a time. It worked like a wizard to baffle the existing redundancies in the financial system. An intelligent document scanning system reduced the back-office load and gradually moved forward to streamline and optimize the processes.
The progression for even better projections was certainly not expected from AI. With further sophistication of machine learning models, AI was entrusted to male credit decisions, participate in stock bidding, and quantitative trading like critical decision-making processes. A recent report states that 10 years down the line AI will predict the stock market with 100 percent accuracy and an even longer time scale.
Now, AI in BFSI is not limited to supporting technology to bridge human limitations. Now, it’s scoring high credibility to drive the top line of growth and extend the profit margin with a competitive edge.
Profit Earning Applications
When the businesses were struggling to meet the financial targets, AI emerged as a boon to waiver the loss. The process took a sharp turn to what we call intelligent plans with assured Turn Around Time(TAT) for all financial services. Plus, AI interfaces are more robust, invariant to human biases with Natural Language processing that made it much easier to strike a human-like conversation with the visiting customers at online counters.
Hence be it for streamlining customer data to the optimization of the back office process AI attributes are formidable all sects of finance operations. Today we have designed bots used for self-help asset management or valuable insights from a data-pile or detection of anti-money laundering patterns. Here are the few AI transformations that the present finance sector is opting for.
B2B enterprises are struggling to hit their financial targets, but leading companies are turning to AI-based sales intelligence tools as the bridge between the limitations of human organization and outstanding sales results, between drowning in data and competitive advantage, and between winning and losing
Interactive Humanoid Bots: If considered globally, humanoid chatbots were first introduced in the year 2015, by Ally Banks in the US. Tracing the trend HDFC bank attracted the limelight towards them by launching ‘Eva’ as the first humanoid, AI-powered chatbot with Natural Language Processing (NLP) abilities. The success of Eva in striking a human-like conversation won the heart of many, solved 5 million+ queries with an 85 percent accuracy rate across the globe. Queries are met in milli-seconds followed by quick recommendations with non-stop 24*7 engagement. Once it was mentioned that a bank saves 4 minutes of the consultant’s time due to queries made by chatbots and they can focus on critical processes efficiently.
AI-directed Risk-Management- AI-derived insights are a new way to make informed decisions – it has been a much easier task to waiver the market risks at bay with a promise of effective investment outcome. The ability of AI for faster data screening enables it to skirt through multiple data sets from both formal to informal platforms. Banks today are fostering tailored software for Constant Vulnerability Testing to eliminate data breaches, support resilience with cloud technology, mobile user support, and others. Today banks are heavily investing in AI and expecting more cognitive technologies for better prediction and performance.
Analytics with AI-vantage- It has been predicted that 32 % of the operative heads in the financial sector use AI for predictive analysis in making informed decisions and recommends AI-powered search engines and voice recognition features. On a real note, AI-Analytics provide wealth benefits for the finance service, by exacting the root cause, preventing revenue drops, and detecting the fine-variance in the data stream. It’s a much faster and convenient way to map the consequences beforehand and make calculated predictions. Further sophistication of machine learning algos will make it easier to manage, structure, and analyze data to save both time and money for financial corporations.
Anti-money laundering- Secured banking is a reach-out for all finance customers and organizations are quite tight when it comes to assuring safe transactions in money matters.
Here AI is a perfect fit for securing banking systems money laundering and detecting fraud and busting cybersecurity threats. From malicious behavior, reviewing computer-generated log-system to spurious emails, AI software is taught to provide scam solutions with details like when, where, and how the fraud was committed. Further, it can also integrate various multi-factor authentication systems, identity recognition, face recognition at ATMs, biometric footprints, and more.
AI-surfaced Back-office- Smart data capture tools like Optical Character Recognition or OCR are also a part of AI automation. The technology helps to convert the documents into searchable data. It has decreased the error in maintaining consistency in record keeping of billing information, cheque deposits, banking statements from the customers, and others. Aligning with the shift towards digitization, AI took over the task to gain valuable insights from the captured information. Stepping towards automation has greatly improved the TAT and enabled the bank to keep track of the processing time.
Self-Help Wealth-Advisory– Blending the Gen-Z needs, banks and financial institutions have put on a savvy suite and appointing digital touch-points in managing personal portfolios. Integrating automation has resulted in shaping wealth management and helped to fetch insights from multiple platforms even from social networking sites. Other than only relying on bank statements, savings charts, and assets information from informal sections will help to come up with unbiased advice managing wealth. Plus it promises to eliminate mundane errors and false alarms and even has structures independent bots to look over the personal asset with accurate predictions.
Gain upon AI Integration
AI will save more than 1 trillion USD for the banking industry as per current estimates. On the other hand, financial institutions are expecting a cost drop of 22 percent in funding the operations, mostly front office with AI integrations by 2030. The distribution of savings from AI will be by; reduction in the retail branches, security, teller, and cashier scale in front office operations, applying AI in KYC/AML and underwriting the collection system.
The above stats clearly approves that AI is the most promising application for finance institutions. Yet the finance industry needs to gain customer trust in implementing AI operations which leads to improving the machine learning algorithm to capture accuracy and better human-like interactions. This way we can gain a broader application window to use AI to be incorporated in social media, free text fields, and even machine vision into the development of lending, investment, and insurance products.
How to Get Trained in AI for BFSI?
If you agree that AI has the capacity to solve most of the banking sector for banking then you should consider upskilling. With AI institutions a financer can opt for a futuristic job like- Fintech headhunter/liaison, Self-driving finance engineer, Sustainable wealth manager, Crypto Forecaster, Trust officer, Cross-company cybersecurity liaison, and others.
To ‘win the war of skills’ Indian Institute of Technology-Roorkee in collaboration with WileyNXT will be launching Artificial Intelligence in Banking program. India’s first-of-its-kind online program is made for technology and finance professionals. Miles Education is the branding partner for the course. For more insights keep an eye on the Miles Education website for more updates!