/ October 3, 2019
Technology is the word synonymous with banking processes now. Every process and business vertical in a bank relies on technology for smooth functioning. Robotics and Artificial Intelligence (AI) are the buzz words among the banking technology circles these days. These are proving to be cost and time effective, able to handle large volume of business transactions and hence most appropriate for adopting by banks. Robots can work on repetitive tasks with utmost efficiency, without getting exhausted.
Imagine a simple funds transfer request, which is submitted online through mobile banking channel by a customer. A robot can now read that information, log in to the funds transfer system, record the information, and pass it on to a human for final verification. This has led to significant increase in efficiency.
The adoption of robotics allows flexibility in managing the work load. To support large campaigns, robots can manage a flood of applications for transactions such as opening new accounts or recording new credit card sales. They can also learn how to improve performance and accuracy with little or no human input. In addition, multi-lingual language processing and voice recognition capabilities allow robots to interact and conduct seemingly intelligent conversations with customers.
Leading Indian banks have adopted these new technologies. Here are some examples:
State Bank of India
To fuel its AI mission, this year, SBI launched a national hackathon, “Code For Bank”, for developers, startups and students to come up with innovative ideas and solutions for the banking sector, focusing on technologies such as predictive analytics, fintech/blockchain, digital payments, IoT, AI, machine learning, BOTS and robotic process automation.
SBI is currently using an AI-based solution developed by Chapdex, the winning team from its first hackathon. The solution essentially scans cameras installed in the branch and captures the facial expressions of the customers and immediately reports whether the customer is happy or sad … this is real-time or near real-time feedback!
From a customer chatbot perspective, SBI has launched SIA, an AI-powered chat assistant that addresses customer enquiries instantly and helps them with everyday banking tasks just like a bank representative. Since its launch, the chatbot has responded to millions of queries from thousands of customers. It is believed that SIA is setup to handle nearly 10,000 enquiries per second or 864 million in a day. That is nearly 25% of the queries processed by Google every day.
Deployment of this size is arguably the ﬁrst of its kind in India and even across the world. SBI claims that SIA continuously learns with each interaction and gets better over time (this alone isn’t unique; it’s the premise of more or less any machine learning-based product). Currently, SAI can address enquiries on banking products and services. It is trained with a large set of past customer questions and is said to aptly handle frequently asked questions.
HDFC Bank has developed an AI-based chatbot, “Eva”, built by Bengaluru-based Senseforth AI Research. Since its launch in March this year, Eva (which stands Electronic Virtual Assistant) has addressed over 2.7 million customer queries, interacted with over 530,000 unique users, and held 1.2 million conversations.
Eva can assimilate knowledge from thousands of sources and provide simple answers in less than 0.4 seconds. It is interesting to note that within the first few days of its launch, Eva has answered more than 100,000 queries from thousands of customers from 17 countries across the globe.
With the launch of Eva, the bank’s customers can get information on its products and services instantaneously. It removes the need to search, browse or call. Eva also becomes smarter as it learns through its customer interactions. Going forward, Eva would be able to handle real banking transactions as well, which would enable HDFC Bank to offer the true power of conversational banking to its customers.
HDFC Bank is also experimenting with in-store robotic applications. The Bank’s IRA (stands for “Intelligent Robotic Assistant”) robot appears to be in research and development stage right now, and not in widespread use. We will have to wait and watch for its broad based application in bank processes.
ICICI Bank has deployed software robotics in over 200 business processes across various functions of the company. The Bank seems to be referring to what is often referred to as “robotic software” – a kind of software generally focused on automating office work.
At ICICI Bank, software robots have reduced the response time to customers by up to 60 percent and increased accuracy to 100 percent thereby sharply improving the bank’s productivity and efficiency. It has also enabled the bank’s employees to focus more on value-added and customer-related functions. Software robots now perform more than 1 million banking transactions per working day.
The software robots at ICICI Bank are configured to capture and interpret information from systems, recognize patterns and run business processes across multiple applications to execute activities, including data entry and validation, automated formatting, multi-format message creation, text mining, workflow acceleration, reconciliations and currency exchange rate processing among others.
The bank has created the software robotics platform mostly in-house, leveraging AI features such as facial and voice recognition, natural language processing, machine learning and bots among others.
In February this year, ICICI Bank launched its AI-based chatbot, named "iPal". Since its launch, the chatbot has interacted with 3.1 million customers, answering about 6 million queries, with a 90 percent accuracy rate.
The services offered by iPal are divided into three broad categories, most of which are mapped to the iMobile app.
Category 1: It involves FAQs, which are simple questions that you may want to ask your bank executive for which there are simple, structured answers. You ask the queries and the bot will give you the correct response, and it learns along the way.
Category 2: It involves financial transactions, wherein you can make fund transfers from person-to-person, pay your bills or recharge your mobile phone bills using queries.
Category 3: It involves helping people discover new features. These are simple how-to tasks such as how to reset your ATM pin, which is a bit more evolved and is like interacting with your bank executive.
The bank is currently in the process of integrating iPal with existing voice assistants such as Cortana, Siri and Assistant.
Axis Bank launched an innovation lab called “Thought Factory” last year to accelerate the development of innovative AI technology solutions for the banking sector.
The innovation hub located in Bengaluru, has an in-house innovation team and an accelerator program through which the bank engages with startups in a 3-month program. Shortlisted startups are then put in a structured mentorship program for fine-tuning, validating and scaling their business.
Recently, Axis Bank launched an AI & NLP (Natural Language Processing) enabled app, Conversational Banking, to help consumers with financial and non-financial transactions, answer FAQs and get in touch with the bank for loan other products.
Currently available on Facebook and the Axis Bank website, it will soon be extended to mobile banking channels.
To help reduce the turnaround time (TAT), the bank has implemented AI across 125+ processes and cognitive automation across 90 processes, which needed repetitive manual labor. Currently, robotic process automation (RPA) is complete for most processes, including account maintenance and servicing, loan disbursements, bulk transaction processes and ATM support. What it means is that if previously an employee spent 15 minutes to do data entry and scrutiny while opening a savings account, now it takes two-three minutes (for exception scenarios only) since the bot has been trained to extract, match and validate the data across documents. Not only has TAT and customer experience improved across processes but human prone error and objectivity is significantly eliminated thus improving compliance, too. The other critical area where the bank is using AI is operational risk and AML.
Axis bank is seeing significant improvement in efficiency, time and cost savings. The Bank has a far more robust credit risk model; evident from the fact that 80 percent of the suspicious transactions are from 5 percent customers identified as high risk by the AI-enabled neural network.
With RPA there’s visible reduction in TAT – savings account opening has reduced by 90 percent, on current accounts by 92 percent, and on other processes by 50 percent to 80 percent.
The above is the technology story of just the four major banks of India. The other banking and financial organizations are not remaining untouched by the new technology developments. We simply will have to wait and watch how deeply the AI and Robotics can penetrate the financial world and change the way these organizations would conduct their business.