Introduction
This newsletter has come full circle, and we are happy to roll out the twelfth and last edition of the newsletter for FY2023 this month. Going forward, we will bring new and exciting content in this newsletter on a bi-monthly basis. Please let us know if you would like us to cover any specific trending topics in the industry.
This month’s newsletter discusses environment, social and governance (ESG) from a financial services (FS) sector perspective highlighting the key challenges in collecting and maintaining ESG data and how an ESG data platform can be an enabler to tackle those challenges. The newsletter also talks about ESG data architecture, ESG KPI library, business intelligence and data governance and concludes by showcasing illustrative analytics use cases which can help firms in driving profitability, boosting investor confidence, and reducing credit, ESG and reputational risk across the value chain using ESG data.
Climate reporting has been a part of business disclosures in India since 2009 when the Ministry of Corporate Affairs (MCA) issued the Corporate Social Responsibility Voluntary Guidelines 2009 followed by multiple iterations and guidelines from different government entities. While ESG disclosures and practices primarily gained traction due to regulatory risk, in recent years, there has been an additional focus on ESG practices and disclosures due to the increased push from customers, investors and shareholders.
The newsletter also contains news on partnerships and alliances between industry stalwarts and new-age companies, changes in government schemes, and adoption of cutting-edge technologies by companies to promote customer satisfaction.
Happy reading!
Trending topic of the month: ESG data platform
Introduction
ESG has been a buzzword for many years and has become an important aspect of business due to government regulations and customer sentiments. Additionally, there is mounting pressure from investors to manage emerging sustainability risks and opportunities, across value chains, to measure, monitor and disclose ESG performance transparently.
In the FS sector ESG is of prime importance due to the following reasons:
- identifying and controlling financed emissions due to investments and lending activities.
- supporting businesses in building sustainable products and services across supply chains like green bonds, e-KYC, digital sourcing, etc.
- providing cheaper funds for complying with ESG goals and standards.
- acknowledging the push from customers, investors and shareholders for climate disclosures.
- adhering to regulations set up by regulatory bodies.
Key challenges
Below are some of the challenges which the FS sector faces regarding ESG data:
- performance tracking of ESG parameters (upstream and downstream activities).
- lacking central ESG policies and decision-making.
- reporting accurate data and complying with government regulations.
- siloed data with no central repository for storing ESG data in a standardised format.
- lacking KPI coverage and proxy logics/frameworks specific to FS sector.
- cybersecurity-related risks and data governance/data ownership.
ESG data platform
Identifying and mitigating climate change risk is complex and it is difficult to measure its impact across different regions and value chains. Currently, ESG reporting and analysis is done in an ad-hoc manner with data sourced from multiple sources and collected in silos which requires manual intervention and often leads to inconsistencies in collecting and analysing the data. Even though current IT system and MIS teams can manage ESG data, organisations should think about the long-term benefits and find efficient methods to store and analyse ESG data to avoid spaghetti architecture. Based on the current state of the IT system, an organisation can use the following alternatives:
- if the existing IT system is a legacy system then the organisation should explore a new ESG data platform, and.
- if the existing IT system is robust and scalable then the organisation can integrate ESG data into an existing data warehouse/lake.
Given the complexities in calculating KPIs across the value chain and defining the proxies in case of missing data points there is an urgent need to have an ESG platform which could help organisations in streamlining ESG strategy, implementation and reporting.
ESG data platform architecture
ESG data journey starts with identifying internal and external data sources along with defining the data acquisition pipeline. Internal data like digital transactions, digital onboarding, loan portfolio, HR and corporate governance can come from a mix of existing data warehouse and manual files, and can be acquired using extract, transform, load (ETL) or file transfer. External data from the government, and third-party ESG data providers can be fetched primarily using application programming interface (API).
1. ESG data journey
One of the ways to streamline ESG data is by developing an ESG data mart. Data management firms should create an ESG data mart with FS-specific data models that has an exhaustive KPI dictionary covering different areas and use cases. However, a key challenge for developing such a mart would be to derive proxy logics in cases where accurate data is not available, e.g. calculating emissions due to lending activities or distribution of goods and services. With ESG data mart, organisations will be able to increase the efficiency of ever-evolving data and provide deeper insights for decision-making.
2. ESG data framework for FS clients
Environment KPI
Products and services
(% digital transactions, exposure to sustainable sectors, % customers sourced digitally)
Energy management
(Total electricity consumption, total Scope 1 emissions, projects to reduce GHG emissions)
Water management
(Total volume of water consumed, total water saved, Total water discharged/treated)
Waste management
(Total waste generated/recovered/disposed, waste management practices, E-waste recycled)
CSR/sustainable sourcing
(Trees planted, trees preserved, %vendors assessed for environmental impact)
Social KPI
Employee health and well-being
(Employee work-life balance, employee health initiatives, workspace hygiene)
Diversity and inclusion
(Gender diversity departments, region.)
Financial inclusion
(Financing to women entrepreneurs, contribution to government schemes, financing to priority sectors)
Community welfare
(Contribution to NGO/social welfare, financial literacy, social awareness drives/events)
Talent retention and training
(Employee retention rate, employee turnover rate, employee skill development)
Governance KPI
Diversity of board of directors
(Number of independent and executive directors, female directors)
Risk governance and management
(Committees for risk monitoring, AML policy framework, periodic review of risk policies)
Business ethics
(breach of code of conduct, bribery and corruption, whistleblower events)
Cybersecurity and data privacy
(Cybersecurity incidents, data loss events, infrastructure and network safety standards)
Customer service and redressal
(% of customer complaints resolved during FY, customer service training, technology initiatives)
The figure gives an overview of identified illustrative KPIs across the three key ESG pillars and multiple ESG parameters. Using ESG KPIs, firms can build business intelligence solutions which can help them to have an overview of the data with YoY trends and help businesses to benchmark themselves with industry leaders, align the solutions with their ESG goals, and standardise and automate ESG compliance reporting. Given below are three sample dashboard formats of business intelligence solutions.
3. Illustrative business intelligence solutions
Business intelligence
CxO dashboard
- One-view of YoY trends of strategic ESG KPI like sustainable lending, digital banking, total energy consumptions and total emissions (Scope1,2,3), etc.
- Performance tracking and aligning with ESG goals.
Benefits: informed business decisions help mitigate ESG risks.
Benchmarking and ESG health check
- Leveraging ESG ratings from external vendors and benchmarking with overall industry and market leader.
- Deep-diving in areas which need improvement to bring it at par with industry average.
Benefits: reduce cost of funds, operational efficiency, new product design.
Compliance reporting
- Standardise and automate ESG disclosures for Business Responsibility and Sustainability Reporting (BRSR).
- ESG KPIs are spread across general disclosures, process disclosures and performance disclosures covering nine guiding principles.
Benefits: compliance and boosting the investor’s trust.
Data governance
While revamping the ESG data journey, there are challenges with data ownership, data quality, and data visibility across systems. With a strong master data management, businesses can develop a discipline to collate, unify and deduplicate the scattered data at a central repository. The right data lineage can help build trust in data by driving discovery, transparency, and traceability of data.
Social parameters of ESG have sensitive KPIs like gender, pay ratio and inclusive working, which requires consent and access management. Data governance can help in facilitating compliance with data protection regulations such as the General Data Protection Regulation (GDPR) and the Personal Data Protection (PDP) bill. With data governance, organisations will be able to control data access by defining role or attribute-based data access matrix and processes with predefined automated workflows. Data governance and security measures will establish governance controls and enforce ethical use of personal data.
The figure gives an overview of identified illustrative KPIs across the three key ESG pillars and multiple ESG parameters. Using ESG KPIs, firms can build business intelligence solutions which can help them to have an overview of the data with YoY trends and help businesses to benchmark themselves with industry leaders, align the solutions with their ESG goals, and standardise and automate ESG compliance reporting. Given below are three sample dashboard formats of business intelligence solutions.
Value creation using ESG data
While reporting as per the government regulations will help in transparency and accountability, FS sector can leverage traditional data like financial inclusion, loan purpose and digital banking, along with ESG data to drive value creation for organisations. The ESG use cases given below can help firms in driving profitability, boosting investor confidence, and reducing credit/ESG/reputational risk across the value chain.
4. Illustrative analytics use cases for value creation
Prospect propensity model
Build product propensity, to identify if the prospect is likely to take ESG products like sustainability linked loans, green bonds, etc., to meet their ESG goals.
Benefits: Proactively understand the customer’s preference, enhanced profits.
Sentiment analysis
Quantifying sentiments of stakeholders (positive/negative) across different channels such as social media, news articles, regulatory notice and whistleblower leaks.
Benefits: Identifying clients who have negative sentiments, reducing reputational and credit risk.
Personal finance advisory model
An asset management company (AMC) can use ML to see patterns in voluminous transactions and holdings of high net worth individuals (HNI) customers across institutions to provide meaningful advisory on ESG themed investment opportunities.
Benefits: Proactively understanding preferred choice of customers.
Credit risk model
Including ESG risk at underwriting stage by calibrating existing credit risk models with sectors/client specific ESG parameters across different products.
Benefits: Mitigate capital risk, price product based on perceived risk.
Portfolio analysis
Deep dive into existing loans portfolio to get insights into financed emissions, ESG trends across different clients/sectors/geographies and ways to mitigate risks.
Benefits: Portfolio diversification, risk mitigation.
Capital allocation model
Enable long-term value creation by optimising existing asset allocation model considering ESG risk and returns across asset classes and sectors.
Benefits: Can be used by banks and AMCs to optimise investment portfolio with right risk rewards and increase profitability.
1. Aditya Birla Capital to sell its insurance broking unit
Aditya Birla Capital’s insurance broking subsidiary – Aditya Birla Insurance Brokers Ltd. – will be sold to Edme Services, a part of Samara Capital Group. Both Aditya Birla Capital and Info Cyber India Pvt. Ltd. will sell their stake for INR 455 crore.
2. An Indian FinTech company is using artificial intelligence (AI) bots as collection agents
Though the use of AI while onboarding new customers, risk modelling and back-end loan processing is a norm in the FS sector, Rezo AI – an Indian FinTech company – has launched a product for nonbanking financial companies NBFCs) which uses AI chatbots for collections.
3. Life Insurance Corporation of India (LIC), General Insurance Corporation of India (GIC), and New India Assurance continue to remain Domestic Systemically Important Insurers (D-SIIs)
The Insurance Regulatory and Development Authority of India (IRDAI) has declared that LIC, GIC and New India Assurance will continue to remain D-SIIs. These organisations have been declared as D-SIIs based on their size, market value, and domestic and global interconnections.
4. IDFC First Bank and Crunchfish launch an innovative offline payment solution
IDFC First Bank has partnered with Crunchfish, a Swedish fintech firm that specialises in offline payments, to present a payment system for offline retail transactions. Customers can use the payment system to make purchases without an internet connection by using Bluetooth and soundwave technologies. The system integrates a variety of payment platforms and uses two factor authentication to guarantee increased security. The partnership’s ultimate objective is to help businesses lower the cost of accepting card payments while providing an alternative payment option for customers places with little or no internet access.
5. Unity Small Finance Bank (Unity SFB) replaces its core banking system (CBS) with M2P’s Turing
In order to update its CBS, Unity SFB has joined forces and replaced its CBS with M2P’s CBS tool Turing. The collaboration aims to enable the bank to launch cuttingedge digital services, enhance customer service, boost organisational effectiveness and deliver a seamless customer experience.
6. Morgan Stanley’s wealth management adopts to GPT-4 to assist financial advisers
Morgan Stanley’s wealth management division has used GPT-4, a cutting-edge natural language processing tool, to organise its vast intellectual capital. GPT-4 will let financial advisors access and organise the bank’s mass of data, facilitating more informed and precise decisionan making. After being tested with 300 advisors the artificial intelligence application will be widely used in the coming months.
1. Reserve Bank of India (RBI) to enhance computing infrastructure to keep up with the FinTech industry
Shaktikanta Das, Governor of the RBI, has urged for the expansion of the central bank’s computing infrastructure to handle the growing workload and to facilitate the adoption of new technology. that the Governor believes this expansion of computing infrastructure might increase the RBI’s efficiency in regulatory operations and enable the organisation to keep up with the rapid evolution in the FinTech sector.
2. Farmers received INR 514 as claims for every INR 100 paid as premium under
the Pradhan Mantri Fasal Bima Yojna (PMFBY)
Under the flagship PMFBY, around 38 crore farmers have been enrolled and over 12.37 crore have received claims provisionally since 2016.
3. IRDAI grants licences to two newcompanies to commence Life Insurance Business in India
IRDAI has recently granted registrations to two new insurance companies – Acko Life Insurance Ltd. and Credit Access Life Insurance Ltd. – to commence life insurance business, taking the count of life insurance companies in India up to 25. Additionally, IRDAI has 20 new applications pending for approval in the pipeline for life insurance business registrations.
4. India’s e-RUPI struggles for adoption as central banks gain traction
Despite support from the government and major banks, India’s e-RUPI – a digital prepaid voucher-based payment system introduced in August 2021 – is only being moderately adopted. The primary reasons for its low adoption are privacy concerns, less transparency, and low market penetration due to which only a few citizens are adopting the payments system.
5. Cap on commission payments replaced with an overall cap on EoM
Effective 1 April 2023, the IRDAI has stated that the decisions related to commission payments must be taken by the board of insurers and should be within the expenses of management (EoM) limit. The previous cap on commission payments has now been replaced by an overall cap on EoM. This move will have a positive impact on the insurance business as it will provide more flexibility to insurers in managing their expenses which is expected to enhance insurance penetration and ease of doing business.
6. Increasing acceptance of co-lending between NBFC-banks and NBFC-NBFC
Industry leaders are in favour of co-lending models between two NBFCs or between banks and NBFCs, and believe it will be used at a much wider scale in the upcoming future. Co-lending models entails a win-win situation for both the
parties (originator and primary funder). Originators or smaller NBFCs can operate with the funding light model as the major portion of the funds are contributed by the primary funder or larger NBFC, at the same time primary funders are benefited because of the reduced operating expenses and greater
geographical reach.
7. Health payments card launched by National Payments Corporation of India (NPCI)
NPCI has launched a RuPay-powered card for healthcare payments for employed Indians in collaboration with two FinTech companies (Qubehealth and Falcon). This card is expected to ease the expenses reimbursement process for employees from their employers and provide cashback and discount offers towards medical expenses.
Acknowledgements: This newsletter has been researched and authored by Arpita Shrivastava, Aniket Borse, Dhananjay GoeI, Harshit Singh, Krunal Sampat, Shyam Mishra, Raghav Sharma and Riddhi Ruparelia.
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