Can AI in banking and finance lead to economic empowerment?
The reported estimates as per ‘Fintech in India- Powering a digital economy’ global AI spending is expected to reach USD 19.1 billion of which the banking sector will account for 17 percent of share. In India, the financial sector is not untouched with the innovations in artificial intelligence. A study by Forbes has identified following areas as key investments for AI in the banking and financial sector:
- Customer centricity: acquiring and retaining customers providing innovative products and a holistic experience of customers.
- Improvement in operations, cost management and focus on profitability.
- Risk management, surveillance and fraud detection.
- Underwriting and claims management related to the insurance sector.
Similarly, another report by Edgeverve has argued that AI in the rural banking space has an ample potential in the spheres such as building credit history, relationship manager, and lifestyle based banking. In building credit history AI can aid in collecting and studying data like Aadhar linked data, crop turnover, handset details, SMS logos, social network data, GPS data, call logs and contact list identifying the creditworthiness of customers. The system can prove extremely useful in lending small value loans and renew the same as commanded by the AI machine. The technology of AI can pave a way for National regional language processing (NRLP)- AI based robots talking in regional language with the rural customers and establishing a clear communication to understand their needs. The regional language can lessen the gap that exists between urban employees and rural customers facilitating an empathetic relationship between the two. The robots can play a role in explaining to them about banking products, can also discuss with them the solutions for their problems related to debts and loans, and ultimately provide them with mechanisms for saving. The lifestyle based banking refers to the varying nature of lifestyle of every customer and designing incentives accordingly. In this manner, various government schemes like Gram Sadak Yojana, Swaach Bharat Abhigyaan, MNREGA — banks can use feeds of all such incentive payments data from UIDAI database into the AI engine and come up with best possible solutions for the customers. Therefore, the use of AI in the rural banking space can emerge as not only a revolutionary one-stop solution but also aid in keeping rural citizenry economically empowered.
As for banks, AI can hugely impact the business of banks for instance banks can think of newer revenue channels and find ways to encash AI enabled characteristics. Further, the AI programmed robots can enhance the financial engagement by interacting with rural customers, thereby, boosting their economic standing. Banks can also provide guidance on product harvests to the farmers and the same can be then linked to respective customer’s earning capacity which is also linked to other banking related decisions. The AI programmed technology can be helpful in analyzing the effectiveness of government schemes by working in conjunction with the UIDAI database. The latest image analysis technology can examine the effectiveness of Swacch Bharat Abhiyaan and accordingly map its incentive announced by the government through Jan Dhan account. The solution provider dimension of AI can provide a risk assessment, detect fraud, provide better customer services and eventually lessen the disparities between the rural and the urban. The technology solution providers can provide predictions related to agriculture with the help of drones and sensors.
The growing Fintech sector in India has gone hand in hand with the growing digitisation, changing customer behaviour (which looked for more convenience), developing a range of innovative services and products for an evolving economy. As reported in the analysis by Centre for Internet and Society, “the deployment of AI technologies is still nascent in the banking sector, the competitive advantage that the technologies bring has been recognized by banks with some developing ‘innovation centres’ and running hackathons – these initiatives often take the form of partnerships between banks and FinTech companies”.
The emergence of virtual customer interface has resulted in a customer interface for offering an alternative form of customer service assistance, processing queries to answer user questions and connecting users to appropriate services and suggesting relevant information via text and speech. AI algorithms are being utilized for a personalised engagement between firms and their customers establishing a fulfilling relationship between customer’s needs and demands and the solutions provided by a financial institution. Companies like Accenture and Grameen Foundation have built apps that work to gauge insights into the emotional and cognitive states of the clients. The use of AI along with economic empowerment has also led to gender empowerment ostensibly seen in the applications built by companies like Grameen foundation. According to the Grameen Foundation, women are known to be better investors towards nutrition, education, health and save against a rainy day. The organisation is increasingly deploying technology for low income groups and especially women by improving their capacity, access and trust towards financial services.
Government Initiatives for AI and finance – The Way ahead
The AI task force set up by the Ministry of Commerce and Industry includes a report on Fintech as well. The report mainly states that the use of AI in Fintech will help in expanding existing efforts of India stack, an enabler of digital payments and paperless transactions. The taskforce has also argued that in implementing AI in Fintech, there are two challenges — balancing scale and innovation and anticipation of market demand. The other hurdles on the way include data confidentiality and access to financial services. The key enablers for overcoming these roadblocks include availability of data, open application interfaces, decision making and smart analytics. In this matter, the key government stakeholders — ministry of corporate affairs, Reserve Bank of India, and National institute of Financial management are developing mechanisms in understanding innovations in the fintech industry and how the various actors in the financial sectors are using new methods, products and technologies. The report of the Inter-regulatory Working group on Fintech and Digital Banking released in February 2018 has argued that artificial intelligence and robotics in data analytics and risk management will ride on three pillars- BlockChain, Artificial intelligence, and Internet of Things (IoT).
The other governmental initiatives and schemes include the programmes like Digital India, Make in India and Skill India initiatives. India is endeavouring to develop Industry 4.0 aiming to digitise various sectors including banking with the use of IoT, AI and Big Data analytics. Similarly, Niti Aayog- government think tank has chalked out a national policy on artificial intelligence to outline adoption and commercialisation of AI in India. Another digital platform called IndiaStack is a collaboration between technology think tank iSpirt, comprises API based infrastructure that would enable the development of technologies built around eKYC, eSign, DigiLocker, UPI and Aadhaar authentication (CIS: 2018).
Legal considerations and challenges- Towards a Conclusion
In the present context, there is no overarching framework or a paradigm to guide the establishment of AI related structures in India. There are laws that indicate certain aspects of finance of India, however, they remain unrelated with AI. As argued by CIS, there is a lack of policy framework to evaluate the implementation of AI in finance. The challenges in the development and innovation of AI services in the finance sector include absence of standards – there is lack of fixed standard or rule to regulate use of AI in banking sector, education- lack of expertise across educational sector with regards to developing such technology and human capital, adaptability- to adapt AI based approach according to newer changes, and opacity of algorithms.
To conclude, although we have understood how AI in banking and finance can lead to both gender and economic empowerment, however, the execution of such a technology remains a bigger challenge amid lack of political and policy framework. Therefore, governmental efforts are crucial in identifying legal challenges and effectively tackle them in the times to come.
This piece is written by Manisha Chachra.