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How Indian BFSI Firms are Thriving through Data-Driven Strategies

December 13, 2023

BFSI firms in India are innovatively leveraging data-driven strategies to thrive and flourish in recent times. Online banking has already generated customer expectations regarding cutting-edge services irrespective of location and time. Open banking and embedded finance have also raised the bar further, enabling customers to get credits through non-bank enterprises. Open banking is also enabling third-party access through APIs to financial information. With the increase in advanced banking operations, customers are steadily expecting their institutions to anticipate their needs better. At the same time, another indicator for BFSI firms about using data analytics in BFSI is to enable better customer experiences for future growth. A Salesforce report in 2019 covered 8,000 business customers and buyers globally and reported how 84% of customers feel that customer experiences are as crucial as the services and products offered by any financial institution. Data shared across multiple touch points and channels have thus opened up several new opportunities for BFSI players throughout the Indian finance sector to flourish amidst a competitive landscape. How Data-Driven Strategies are Helping BFSI Firms Flourish Data analytics in BFSI and other data-driven strategies are enabling BFSI firms in India to thrive and grow in the present scenario. Here are some pointers worth noting in this regard. It is a fast-changing world that necessitates the usage of data-driven strategies across the board for BFSI firms. The digital banking platform segment is already expected to grow by a whopping 11.2% (CAGR or compounded annual growth rate) from 2021 to the year 2026. Bots are leveraging data to provide better customer service across touchpoints without requiring branch visits or conversations with agents. They can service customer requests easily while handling other activities seamlessly. Conversational AI platforms are also using NLP that is integrated with IVR systems. These systems can take calls by answering repetitive questions and prevent any customer panic. Customers are assisted in swiftly resolving queries while calls that are complex are transferred to agents. Banks are offering branch-like services with data-driven strategies, building customer profiles/personas, predicting behaviour, and recommending ideal financial services and products. Fraud detection and security models are trained on continual incoming data, helping BFSI firms know more about normalised activity levels, transaction anomalies, deviations, and more. Another method is behavior profiling which studies customer data and accounts to build profiles and understand where/what kind of transactions have taken place. Prescriptive analytics also helps leverage the data that is gathered by predictive analytics to recommend the measures to be taken once fraud is identified. These are some of the many ways in which data-driven approaches are helping BFSI players thrive in an increasingly competitive Indian finance sector. As they say worldwide, data is the new oil and it will soon be the differentiator and competitive advantage that companies in every sector will want to harness, banking and financial services included. FAQs What key benefits do Indian BFSI firms experience through the adoption of data-driven approaches? Data-driven approaches are helping BFSI firms in India obtain several major benefits including the ability to personalise products/services for customers, identify and eliminate fraud, predict risks and manage them accordingly, and a lot more. In what ways are data-driven strategies enhancing decision-making within the Indian BFSI sector? Data-driven strategies are boosting overall decision-making within the Indian BFSI sector. Banks and financial institutions are leveraging data to make better decisions on granting loans or other products, offering personalised services or solutions to customers, identifying and mitigating risks, and so on.

How Generative AI Can Reignite Customer Relationships for Banks

November 6, 2023

The influence of generative AI in banking has reached profound levels in recent times. The implementation of AI and banking customer experiences today go hand in hand. There is a school of thought that generative AI can reignite and revitalize customer relationships in banking. Early adopters of generative AI will naturally benefit from its productivity boosts and its impact on customer relationships. Accenture has reported how 90% of working hours in the banking sector may be eventually influenced by LLMs or large language models. 54 % of work timings, as per this report, has immense potential for automation via AI in the future. 30% of employee productivity benefits may also be witnessed by the sector by 2028. Generative AI can influence almost all sectors and aspects of the banking industry. Here’s looking at the same in more detail. Advantages of Generative AI in Banking Here is how customer relationships in banking get a boost through AI-powered customer engagement and other benefits of generative AI models. How do Customers Benefit from Generative AI in Banking? Generative AI in banking can completely and positively transform customer relationships in banking along with boosting overall engagement levels considerably. Here are some pointers worth noting in this regard. It is not just about serving customers better. Banks also get several other advantages of using generative AI. They can apply AI and neuroscience-based Gamification to match the cognitive and emotional capabilities of aspirants with job profiles in the company. Using analytics can enable better candidates who are the right fit for banking roles in a more competitive and specialized environment. At the same time, generative AI systems can also go a long way towards enabling superior employee training and retention. They can analyze employee data to predict future attrition rates and recommend steps for better talent retention. With high turnover costs in the banking sector, these insights will be hugely valuable for most entities. Data quality, of course, is a key cornerstone behind the successful implementation of these applications and also the algorithms used by banks. Hence, there is a growing need to invest in the right AI and analytics talent in order to leverage generative AI in banking to the best possible extent. FAQs How can generative AI enhance the personalization of banking services for customers? Generative AI is crucial in enhancing banking service personalisation levels for customers. It helps banks suggest the right products/services to customers based on their preferences and needs. It also helps customers get individualized solutions and assistance from support teams. What role does generative AI play in improving the customer experience in the banking industry? Generative AI plays a major role in enhancing customer experiences in the banking sector. It enables personalized recommendations and advice, along with customized service and support. It helps Chatbots and other tools respond faster to customer inquiries, replicating human conversations and understanding customer intent better. How can banks use generative AI to predict and address customer needs proactively? Banks can leverage generative AI to forecast customer needs better, based on an analysis of their spending trends, transaction history, and preferences. They can address these needs swiftly and at the right time based on these customer insights. What are the potential benefits of leveraging generative AI to reignite customer relationships in the banking sector? There are several potential benefits of leveraging generative AI for enhancing customer relationships in the banking industry. These include improved customer experiences and engagement, quicker resolutions of customer problems, personalized customer solutions and recommendations, and more.

Biometric Authentication: The Future of Secure Banking Access

October 30, 2023

Biometric authentication has become a key buzzword in recent years, driven by rapid digitization throughout the banking sector and the need to ensure secure access to sensitive data. Traditional authentication methods and other banking access technology usually revolve around PINs and passwords. However, these are increasingly vulnerable to breaches and challenges faced by users in remembering them. Biometrics in banking offers a robust alternative which makes use of behavioural or physical attributes to ensure secure banking access for customers. A Closer Look at Biometric Authentication Biometric authentication deploys technology for identifying an individual based on any part of his/her biology. One of the first examples of biometrics in banking was fingerprints, followed by facial recognition. Both these technologies are widely used in recent times via computers and smartphones alike. Bank call centres have started using voice IDs while Apple Play already offers the pay-by-touch feature with its mobile devices. The iPhone 5S also created a revolution in 2013 when it arrived with a fingerprint reader. There is a massive opportunity ahead for biometrics in banking, especially as a need to ensure secure banking access. Biometric-driven authentication is one of the easiest and most secure options that can be deployed today to ensure widespread customer satisfaction. Biometrics make a strong case for themselves as the future of banking security since they safeguard against the chances of identity theft, takeovers of accounts, and other fraudulent activities. Banks can easily verify returning and new users during the onboarding or log-in procedures. The latter is made simpler and more accurate while costs are significantly reduced by digital onboarding as well. Key Components of Biometric Authentication Biometric authentication usually relies upon the following core aspects: Benefits of Biometric Authentication Biometric authentication can rightfully be called the future of banking security for the following reasons: Does Biometric Authentication have Any Underlying Challenges? Biometric authentication may have a few underlying challenges and hurdles that are worth highlighting. Some of them include the following: Biometric Authentication as the Future of Secure Access Biometric authentication is still poised to become a crucial part of digital transactions and banking operations. Facial recognition, voice recognition, and fingerprint recognition will continue to thrive while biometrics can be integrated further into diverse segments including Government services, healthcare, finance, and more. Several innovations are also underway in this space. To cite an instance, work is ongoing worldwide on advancing behavioural biometrics. This will eventually help identify people based on their interactions with systems or devices. It will ensure an additional layer of security while scaling up convenience levels greatly for customers at the same time. Biometric authentication will ultimately play a vital role in the future of what we know as secure access. Biometrics in banking will become even more mainstream while it will ensure extra security and comfort for both banking entities and customers alike. Yet, solid security measures and tackling privacy issues should be a priority for those implementing these technologies. Based on reports, there were a whopping 400,000 credit card fraud cases alone back in 2020. This tally did not cover identity theft, takeovers of accounts, and varied cybercrimes. Security is thus highly important for everyone, seeing as so many individuals have been victims of such fraud over the last few years. This is where biometric authentication is poised to play a bigger role in the future. FAQs How does biometric authentication make banking access more secure than traditional methods? Biometric authentication makes banking access more secure than conventional methods. This is because it relies on the authentication of unique physical/biological attributes of individuals which are hard to impersonate or replicate. At the same time, there is some behavioural biometrics for an additional layer of security as well. What types of biometric data can banks use for authentication, and how are they collected and stored securely? Banks can use varied biometric data from customers including fingerprints, voice recognition, palm-prints, iris or retina scans, facial recognition, and even behavioral biometrics like typing speed, gait, and keystrokes among others. This data is encrypted and stored securely in banking systems to enable greater safety and convenient access alike. Can biometric authentication be trusted as a reliable method for protecting sensitive financial information? Biometric authentication can be reliable and trusted to safeguard sensitive financial data. There are no risks of pins or codes being hacked, lost, or forgotten. At the same time, it is harder to impersonate individuals’ unique characteristics. Hence, it can be a safer way to protect financial information. What challenges and concerns should banks and customers consider when implementing biometric authentication for banking access? Customers and banks should tackle challenges like privacy concerns and data usage along with secure storage and encryption of data. At the same time, false positives or negatives may be another hurdle along with the time and effort required to implement these technologies as far as banking institutions are concerned.

Analytics-Driven Personalisation: Redefining the Customer Experience in Banking

October 16, 2023

Analytics-driven personalisation is the biggest recent trend that has completely changed the game in terms of enabling personalised banking along with improved customer experience in banking. Digital transactions, payments, and banking platforms have completely changed the modus operandi as far as both customers and executives are concerned. At the same time, the higher digital engagement and transaction volumes lead to the generation of huge amounts of data on a daily basis. This is in the form of both non-transactional and transactional information. Banks are now finding several merits in tapping and analysing this data to gain invaluable insights for positively transforming customer experiences and processes. Technologies like banking analytics are being used in tandem with machine learning, artificial intelligence, and big data analytics to generate the best possible results for banks in this context. Even McKinsey Global has stated how data-driven entities are 23 times likelier to acquire new customers, while being six times likelier to retain them and 19 times as likely to be profitable due to this aspect. Another key aspect lies in the fact that banking analytics or data analytics in this segment had a value of approximately $4.93 billion in 2021 and is estimated to hit $28.11 billion within 2031 (indicating compounded annual growth rates or CAGR of 19.4%). There are several data or touch points for customers including websites, mobile apps, digital transactions, social media platforms and a lot more. Rich data can be used for redefining customer experiences while also predicting customer engagement and mapping the journey. How Analytics-Driven Personalisation is the Key Factor When it comes to offering personalised banking and redefining customer experiences, big-data analytics is the key element that institutions are looking to leverage in the current scenario. Here are some pointers worth noting in this regard. Several banks and financial institutions have multiple products for customers which cater to varying requirements. Redefining customer experiences thus becomes a major differentiator for these financial institutions in order to enhance customer satisfaction and retention levels alike. Gaining a better understanding of customers and identifying gaps or potential issues will also help improve the overall experience for customers while enabling more personalisation at the same time with full scalability. What are the challenges of data analytics in banking? There are a few challenges of leveraging banking analytics that institutions also need to be aware of. These include: However, analytics-driven personalisation is the biggest trend that will completely reshape customer experiences across banks and financial institutions. Customers now engage across several touchpoints and expect more personalised banking solutions and quick assistance and support for their queries. Hence, institutions will have to rely more on data analysis and insights to make better decisions that lead to improved customer experiences and higher retention. However, maintaining a customer-centric approach is the biggest takeaway that banks should keep at the forefront while scaling up data analytics initiatives simultaneously. FAQs Analytics-driven personalisation greatly enhances the banking experience for any customer. Banks get a full view of the customer profile and specific needs, pain points and requirements. Hence, they can customise their offerings and solutions to meet these needs while solving the pain points and making sure that the customer gets the right solutions at the right time. Both transactional and non-transactional data are used for driving analytics-driven personalisation in banking. This includes data directly gathered from transactions across multiple channels and also other data from surveys, forms, websites, mobile applications, social media platforms and many other sources. There are a few considerations and challenges that banks should keep in mind while implementing personalisation through analytics. Data quality and integrity should be a major focus area, since poor quality may completely jeopardise the whole process. Other considerations include data silos, gathering disparate data across systems, integration and dealing with legacy infrastructure. With more personalised services and engagement, customer experiences naturally improve over time. This leads to higher loyalty and superior engagement since customers get solutions tailored to their needs and their pain points are addressed by banks swiftly due to analytics-driven insights.

Navigating the Future of BFSI: Insights from Vymo on Market Positioning, AI Impact, Gamification, and Talent Retention

October 12, 2023

The future of the banking and financial services (BFSI) industry hinges on various factors that leverage advanced technology towards enabling higher progress. Here are some insights from the Managing Director-Asia Pacific at Vymo, Rajesh Sabhlok. Vymo is one of the quickest-growing SaaS entities in the market at present with a novel positioning based on its focus on the financial industry. This narrowed-down emphasis on the ideal client profile has enabled a deeper understanding of the challenges faced by the sector and sales teams, while ensuring that core solutions cover their requirements and spur higher adoption of users. Let us now look at some valuable insights that deserve closer attention. Key Insights for the BFSI Industry Here are a few pointers worth highlighting in this space: Let us now take a closer look at some other valuable insights that should matter to BFSI companies. Additional BFSI Trends Worth Noting Here are a few more trends and insights from Vymo that should merit closer attention from banking and financial services institutions. Here are some more emerging trends as per Vymo’s forecasts. Emerging BFSI Trends According to Vymo Here are a few more emerging trends that are crucial for the banking and financial services (BFSI) sector. Vymo feels that it has created a unique ecosystem with its digital sales engagement and enablement solutions for sales teams, along with higher user adoption through strategic approaches. It has created a customer-focused post-sales target operating model which has a novel tool kit that ensures better engagement and user adoption levels. The entity is also investing in ML and AI models to enable better user experiences and skill development simultaneously. Customers now have increasing access to reviews, price comparisons, product comparisons, and other information online. Their buying behaviour will naturally be influenced by all these factors. Hence, sales teams and agents should rapidly transform their processes while being digitally enabled to meet the customer shift. Hyper-personalized solutions for customers are the need of the hour throughout multiple touch points. There is a higher demand for more agile approaches that are tailored to individual requirements along with digital-first interactions through portals and apps. Customers now want digital onboarding journeys and automated onboarding procedures. Sales professionals are increasingly looking for more support from AI-based tools to streamline and quicken procedures while lowering their overall workloads. Flexible and usage-based insurance will also be necessary for customers along with pay-as-you-go systems. Insurance companies will also have to increasingly sync their operations with ethical and sustainable practices to connect better with their customers and their specific requirements. These are the core trends that the BFSI industry should witness over the coming decade.

RBI plans to introduce wholesale CBDC in the call money market soon

September 19, 2023

India is already synonymous with futuristic technological advancements and innovations that extend to every industry. Finance is no exception to shifting global undercurrents and the Reserve Bank of India (RBI) has been at the forefront of several future-first transitions in recent years. One such move has been the RBI’s move pertaining to the extension of the wholesale CBDC (central bank digital currency) as tokens for the purpose of interbank borrowing or the call money market. The apex bank of the country is reportedly planning this new feature rollout for the RBI digital currency in the near future as per various reports. Here’s what we know so far. RBI’s big wholesale CBDC initiative Here are some insights as to the RBI’s plans to boost money market efficiency: PTP will take visitors through the entire framework, beginning from onboarding to the dairy and KCC loan sanction and disbursement processes within a few minutes. It may completely transform rural credit sectors in the future while being used for distributing loans of smaller ticket sizes in the future too (personal loans and MSME loans). The RBI has also worked to showcase its digital rupee and its evolution along with conducting live transactions with the same at the summit. UPI One World will help visitors complete onboarding without possessing an Indian bank account. RuPay On-The-Go will enable contactless payments through accessories used or worn regularly. BBPS will facilitate cross-border bill payments, complete with easier fintech integration and support for regular financial entities to execute domestic and cross-border transactions alike. RBI’s Innovation Pavilion at the G20 Summit venue saw the announcement being made on the starting of the wholesale CBDC pilot for interbank borrowing either this month or early next month. The RBI is betting big on this project, with an aim towards touching 1 million transactions each day by end-2023 as compared to 20-25,000 for July. On the other hand, Punjab National Bank (PNB) has also announced its CBDC (central bank digital currency) launch with UPI (unified payments interface) interoperability being a key feature for the digital rupee-based mobile application. As can be seen, there are exciting developments afoot in the Indian banking and financial services industry. The Reserve Bank of India is focusing on technology-backed innovation, an approach that will only enhance operational efficiencies and ecosystem-wide transparency in the near future. FAQs The call money market (CMM) is the platform for short-term loans that are sometimes one-day loans, traded by financial institutions like banks. Lenders and borrowers in this market are majorly these banks or entities. CMM may be accessed by banks for meeting any reserve needs or for covering any sudden cash shortfalls on any specific date. Wholesale CBDC will have a positive impact on the call money market. It will transform the interbank market by improving overall efficiency. The usage of central bank money for settlements will lower the costs of transactions greatly. This will be possible by pre-empting the requirement for any infrastructure for settlement guarantees or other collateral for the mitigation of settlement risks. The RBI is already using e?-R as its retail version pilot for the CBDC while Digital Rupee – Wholesale (e?-W) has also been introduced. The former is similar to a digital token that is representative of legal tender. There are several blockchain technology components that are being used for these initiatives. The RBI is expected to take several measures towards ensuring greater security for wholesale CBDC transactions. It has already proposed two CBDC structures, namely account and token-based. It has already aligned itself towards the latter for retail while the wholesale sector may get the former. Usage will be secured through tokenization at the retail level, ensuring security against fraudulent payments, duplicate payments, and other issues. There could be dedicated security protocols implemented by the RBI for these initiatives.

Banking & Finance News Wrap | Weekly Snippets September | Indus Net Technologies (INT.)

September 8, 2023

✔️https://newspatrolling.com/research-ranking-launches-indias-ai-driven-financial-mentors-vasu-and-vidya/ Introducing Vasu and Vidya, the new AI-driven financial mentors from the house of Research & Ranking that will transform how individuals perceive and understand various finance-related topics. ✔️https://www.financialexpress.com/business/digital-transformation-bybit-creates-an-ai-powered-tradegpt-3233264/ TradeGPT is here to transform the trading game with its cutting-edge AI insights and predictive power, courtesy goes to TradeGPT’ – Your Ultimate AI-Powered Trading Companion. This will generate trading insights and answer technical questions from its market data ✔️https://www.consultancy-me.com/news/6682/emirates-nbd-looks-to-leverage-the-power-of-generative-ai Emirates NBD is harnessing the incredible power of generative AI to shape the banking of tomorrow. This will include leveraging Github Copilot X, and will also have exclusive access to Microsoft 365 Copilot. ✔️https://campaignbriefasia.com/2023/08/31/digibank-indonesia-redefines-smart-banking-with-innovative-ai-powered-campaign-from-nada/ DigiBank Indonesia is rewriting the future of smart banking with a groundbreaking AI-powered campaign, courtesy of NADA.

Close shave – Thank your asteroids.

July 27, 2023

Dear Colleague, we woke up today with a bit of a ‘dinosaur feeling’. 🦖 How Come? The Jurassic emotion was a direct result of finding out that a house-sized asteroid is making a very close pass of our planet today. Fyi, when faced with the wrath of such a rogue rock, the dinosaurs were not so lucky, and that’s evident because these days you are filling up their remains in your car’s fuel tank. 🦖 + ☄️ = ⛽ What’s On The Rocks? As you read this, Asteroid 2018 BG5, a space rock from the Apollo group of near-Earth asteroids, will fly by earth (July 27,2023) at a speed of 30,094 kays an hour, per NASA’s Center for Near-Earth Object Studies (CNEOS). The asteroid will come as close as 4.1 million kilometers to us – a distance which may seem large, but it is relatively small in astronomical terms, considering the vastness of space and the size of the asteroid. Should You Withdraw All Your Savings? No. No. NASA’s best have assured that there is no risk of impact with Earth today or in the foreseeable future. ⚠️ However, even a small asteroid can cause significant damage if it enters the Earth’s atmosphere, as shown by the Chelyabinsk meteor event in 2013, when a 59 feet asteroid exploded over Russia, injuring over 1000 people and damaging nearly 8000 buildings. STATS: Sorry, The Doctor Isn’t Available Life sciences leaders, heads up. Are your sales reps getting the cold shoulder/elbow nudge from doctors more often these days? Turns out, they are not trying to hoodwink your system while catching up on Oppenheimer during office hours. Yeah? How Is That? A new CMI Media Group survey of physicians across countries is providing fresh evidence that face to face meetings with doctors is becoming a rare commodity since COVID-19. When asked, 25% of the doctors reported reducing face-to-face interactions. With another 10% of doctors permanently closing their doors for reps, the survey suggests pharmaceutical companies will find it increasingly tough to put their drugs in front of ~35% of physicians via the traditional in-person route. Aha. What Could Work Then? To start, how doctors utilise their time roughly maps onto the value they place on each touchpoint. Print and online journals are on top, with 79% finding them very or extremely useful. Pharma reps on the other hand, are pretty much down on the attention radar. Only 33% doctors find reps very or extremely useful, placing them below resources like medical websites and unbranded disease education from biopharma. Bonus Data Points 🍎 99% doctors engage with print/online journals or medical websites at least once a month. 🍎 75% also engage with search engines and email, online drug references, direct mailers, medical apps, professional online communities, brand emails, medical videos on YouTube, and medical podcasts. The doctors’ world is clearly leaning towards an omnichannel approach. If you need to explore such a strategy, chat up with Anindya, our resident Life Sciences man. Psst, he curates the most amazing conversations over ☕️. Ai & ANALYTICS: The Chatbot Will See You Now Unlike physicians who are reducing their face time with med reps, did you know chatbots have no pressing personal issues (yet) and are doing mankind some sterling service? I Do This blurb refers to securing consent from humans for stuff like clinical trials and other life sciences related studies, where, hold our battery pack, chatbots are doing very well. Seriously? Yo! Results from a study of the use of a chatbot in the consent process show that it encourages inclusivity, and leads to faster completion of the process with high levels of understanding. On the flip side, the traditional method of securing consent lacks a mechanism to verify understanding objectively, just like all the web forms we give consent to without understanding zilch of the fine print. Comparatively, the chat-based method can test comprehension, disqualifying users who do not show understanding to give consent; rather, it puts them in touch with a genetic counsellor to figure out why knowledge transmission did not occur. Pretty dang smart for a piece of software, talking of which, we have a whole bunch of AI-powered chat bots held in a big steel vault behind Dipak’s office desk. Get in touch with him to deploy one for your business. BFSI: A Single Source of Truth We’ve been swamped with news, stories, videos, and you-name-it, all revolving around artificial intelligence, once prompting OpenAI’s CEO to say, people are ‘begging to be disappointed’ about GPT4, meaning let’s water down the hype, please. But amid all the speculation and noise, what are the most achievable, real world uses of AI? The BFSI Space Is A Great Start, We Say The BFSI sector is flourishing with AI tech integrating with many functions, from the digital KYC verification process to evaluating credit scores. However, to quench the thirst of the customer base accustomed to the convenience of digital tools, the industry needs to deploy more AI tech, the first among them could be; Customised Experience: Because of the very nature of the trade, BFSI players have always had a finger on consumer pulse. Time to take that to the er, bank. Their spending patterns and investment portfolios can assist BFSI businesses to build relevant, personalised messages, enabling them to better present their products and services across various platforms, improving acquisition and loyalty. This is where AI and data analytics shine, delivering value by creating a single source of truth from an ocean of data from within and outside the business. Fraud Detection: While the original BFSI fraud detection model is focused on detecting fraudulent transactions – an area where generative AI has added a powerful weapon to the fraud detection arms depot – a gap remains. You guessed right, detecting fraudulent human behaviour. Fraud does not happen in vacuum or underwater. People commit fraud. AI can also be deployed to comb through the field of behavioural indicators. It’s time to task AI with sifting through the subtleties of human communications — written

The Power of Data: How Analytics is Revolutionising Debt Collection in BFS

May 10, 2023

Data, as always, is proving to be the real game-changer for BFS (banking and financial sector) companies. Analytics is driving higher efficiencies and benefits for BFS players, including debt collection. What is the role of analytics in BFSI debt collection? Here’s finding out. With regard to better engagement with consumers for debt collection, BFS players have always depended on conventional models including phone calls and emails/letters. The aim here is application in bulk, which has often led to several experiences that are not as pleasant for both parties (borrowers and lenders). Customers now expect increasing personalisation with diverse requirements and preferences. By tapping machine learning, AI, and predictive analytics, companies are now acting on data-based insights while resolving several problems across sectors, including debt collections. It has led to simpler, faster, and easier systems and procedures for consumers and banks alike, with advanced data science abilities providing teams cutting-edge tools that they require for higher transparency and standardising operational processes. How is data analytics transforming debt collections for BFS entities? Here are some of the ways in which analytics is gradually revolutionising debt collections for banks and financial service providers. A. Building custom outreach strategies- Debt collection is not only about physically reaching out to borrowers. The blueprint has to be wider today, in sync with fast-changing banking ecosystems. Personalising the outreach to borrowers across types and personas, with stage-based plans across channels (deriving from anticipated consumer responses at each stage) is highly necessary for BFS entities today. Data and analytics is now spurring decision-making throughout the entire value chain of collections, along with saving time, energy, and costs for companies simultaneously. B. Debt resolution strategies- Analytics has enabled better debt resolution blueprints on the basis of insights. These include the following aspects: Risk Classification of Borrowers- ML-based algorithms can accurately forecast the chances of delinquency of borrowers, deploying innumerable parameters as inputs. Due to resource limitations, calling every defaulter is next to impossible, not to mention the need to engage debtors, to avoid future non-payment risks and delinquencies. Hence, analytics is what enables hyper-personalisation in this case, enabling agents to communicate the right message in specific scenarios to particular groups of customers. Channel Forecasts- On the basis of insights on earlier communication and behaviour of customers, BFS companies can predict the suitable template, channel, frequency, language, and time to contact borrowers. Several borrowers also prefer digital communication and their preferences may be better identified by algorithms. Optimising Blueprints- Tracking real-time borrower behaviour throughout multiple channels enables the creation of a personalised blueprint and mechanism for debt collection. Predicting Intent-to-Pay– It encompasses forecasting the willingness of borrowers to repay the money, based on outreach measures and historical measures for working out the priorities for the coming day in terms of tele-calling or other outreach initiatives. Internal transaction information, when fused with other factors and behavioural triggers can predict delinquencies, while enabling BFS companies to accurately build pro-active strategies for customer outreach. For instance, lenders may swiftly gain a perspective of customers’ aggrieved/negative reactions or reducing account balance and their inter-relationships. Better Borrower Understanding- Using analytics for debt collections will enable an examination of transactional, demographic, and behavioural information. This will help BFS players gain a better understanding of consumers, while identifying specific patterns and getting insights that help them develop strategic blueprints for collections. Monitoring borrower responses to several types of messages is also helpful in determining ideal frequencies for interaction and suitable timelines. Risk-driven segmentation may also be useful for better targeting. Insight-Driven Debt Collection Decisions- Debt collection decisions can be taken in a better way, driven by analytics-based insights. Segmentation, predictive systems, deep behavioural analysis, and other blueprints are all possible for BFS companies. Insights are helpful for warning banking entities early regarding delinquencies and defaults in the future. It will help banks work out when people are likely to default and come up with custom strategies for mitigating these situations. These insights also help build suitable responses for interactions with borrowers. Issues with continual follow-up communication will be resolved with data-based intelligence. Banking entities will have suitable knowledge for catering to customers with suitable details at the right times. Building Personalised Relationships- Customer relationships and experiences are crucial aspects for all BFS entities. Data-driven insights and analytics may help greatly in both these departments. Lenders can have language/region-based responses for customers. As can be seen, data analytics can completely transform debt collections for banks and financial services players. Data errors, incorrect entry, issues with detecting frauds have been identified and resolved with smart and new-age AI-based tools. At the same time, debt collection can be enhanced greatly through better insights and real-time visibility into the process. From reaching out to customers at the right time and with personalised offerings, to improving engagement and scaling up predictive/forecasting abilities, it enables BFS players to resolve long-standing problems and convert debt collection into a seamless and standardised process. FAQs 1. What is debt collection in BFS? Debt collection refers to the mechanism for collecting and recovering unpaid/due debt from borrowers. 2. What kind of data is collected and analysed for debt collection? The types of data collected and analysed for debt collection include historical customer data on engagement and interactions, behavioural data, preferences, demographic data, socio-economic and macro-economic data, past financial transaction history of customers, and more. 3. What are the benefits of using data analytics in debt collection? There are several benefits of using data analytics for debt collection, including customising communication and outreach with borrowers, predicting/forecasting future chances of defaults and non-payment, working out better debt collection strategies, and standardising the process. 4. Can data analytics help in predicting future defaulters? Data analytics can be immensely helpful in the prediction of future customer defaults, through generating insights on past purchasing behaviour, financial history, transaction history, and many other parameters. This helps banking and financial services companies forecast the likelihood of defaults and take pro-active steps accordingly.

The Emergence Of Decentralised Finance (DeFi) And The Potential Impact On Traditional Banking And Financial Services

April 24, 2023

Decentralised finance (DeFi) has made a huge splash worldwide, with its potential for traditional banking disruption. It is a rapidly growing financial technology that uses secured and distributed ledgers, based on blockchain and smart contracts, just like cryptocurrencies. But how is it contributing towards disruption or financial services innovation? In the U.S., for instance, the SEC (Securities and Exchange Commission) and Federal Reserve have clearly outlined the regulations for centralised financial entities such as brokerages and banks that customers depend on accessing financial services and capital directly. DeFi poses a challenge to this centralised financial setup through empowering people with peer-to-peer digital transfers/exchanges. It also contributes towards the elimination of fees charged by financial institutions and banks for the usage of specific services. Those holding their money in secure digital wallets can instantly transfer funds, while anyone with internet can make use of DeFi. What is centralised finance? For understanding decentralised finance, one should first have an idea of what centralised finance is all about. Here are some core points worth noting in this regard: Centralised finance has the money held by the banks and third parties. They are the ones who enable money transfers across multiple parties, each of them charging fees for the usage of services. Networks clear charges and request payments from banks. Every chain entity gets payments for services provided. All transactions are supervised in this system, right from local banking services to applying for loans. How does decentralised finance (DeFi) work? Decentralised finance (DeFi) has huge potential for traditional banking disruption. Here are some points worth noting: This system does away with intermediaries by enabling merchants, individuals, and businesses to take care of financial transactions with new and emerging technologies. DeFi makes use of security protocols, software, connectivity, and hardware advancements via peer-to-peer financial networks. Individuals can easily trade, lend, or borrow funds whenever they get an internet connection, using software for verifying and recording financial transactions throughout financial databases that are distributed. Distributed databases are those which are readily accessible throughout multiple locations, gathering and aggregating data across users and leveraging a consensus-based mechanism for verification. Decentralised finance (DeFi) does away with the need for any centralised financing model, through enabling any individual to make use of financial services almost anywhere, irrespective of their identity or location. DeFi applications enable higher control over funds for users via personal wallets and trading solutions catering to individuals. Decentralised finance does not ensure complete anonymity. Transactions, while not having individual names, can be traced throughout all entities with access, including the law and Governments. DeFi makes use of blockchain technology as used by cryptocurrencies. The blockchain is the secured and distributed ledger/database. Transactions get recorded through blocks and verified by users. Once verifiers agree to transactions, the blocks are closed and then encrypted. Another block is made with data on the earlier block within the same. The blocks are conjoined through data in every proceeding block, which gives it the blockchain moniker. Information in earlier blocks cannot be modified without any effect on the following ones. Hence, there is no way to change a blockchain. How DeFi is being used in the financial sector Decentralised finance (DeFi) is being used widely in the financial sector, with the following being the major take-aways: P2P (peer-to-peer) financial transactions, right from payments through applications and issuing loans. DeFi is enabling direct interest rate negotiation between two parties and lending through its networks, equating to lower fees. Anyone with internet can access DeFi platforms and there are no locational limitations on transactions. Smart contracts on blockchain and records of competed transactions can be easily reviewed and are immutable. Income-generation and capital transfer abilities for investors with high security. Here’s how it is disrupting traditional protocols: DeFi is enabling lending/borrowing at scale between unknown parties and minus intermediaries with automatic setting of interest rates, based on demand and supply. Loans are secured through over-collateralisation, with loan access anywhere and anytime. DeFi is also enabling the de-centralised trading and development of derivatives for various assets like commodities, stocks, and even currencies. Decentralised asset management for cryptocurrency is another growing trend. Decentralised exchange concepts have come up, with cryptocurrency holders no longer needing to leave the arena for token swapping. DEX has several smart contracts with reserves of liquidity, operating as per pre-defined mechanisms of pricing. Decentralised insurance is also available, covering bugs for smart contracts in this entirely new space. This is a major risk area for DeFi users, and is covered by these plans. As can be seen, crypto-based decentralised finance has already reached an advanced stage in terms of its evolution. It is steadily taking care of all the necessary functions of a financial system as a result. DeFi could well be the next big thing in global finance, provided it can navigate security threats successfully. FAQs What is decentralised finance (DeFi) and how does it differ from traditional finance? Decentralised finance is where distributed and secured ledgers are used with blockchain technology like cryptocurrencies. It means peer-to-peer transfers without higher fees for transactions as charged by all the entities in a traditional transaction chain. It can enable anytime and anywhere transactions between unknown parties, with automatic conditions and smart contracts, eliminating intermediaries. How does DeFi work and what are the key components of DeFi platforms? The main components include specific hardware, software, stablecoins, and so on. The infrastructure is continually evolving, and the system works through an independent yet secured and highly traceable network on the blockchain. Transactions are recorded, stored, and are verifiable easily. At the same time, there are no intermediaries and resultant charges. Parties can directly engage in transactions with automatic setting of interest rates or other crucial parameters. What are the potential advantages of DeFi over traditional finance? DeFi is a transparent and open system as compared to the closed and centralised system followed by traditional financial institutions. Transactions are public and may be viewed by any individual. They are readily traceable as well. At

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