Category: BFSI

INT. Pulse

INT Pulse

Dear Colleague, there you are at your desk, starting the day with a review of your 80/20 list and suddenly –  upcoming meeting alert – or in other words, the sound of your workday dying.  Fret not, because just like you, your boss hates that sound too.  Nope, we didn’t cook this up ourselves – multiple researches stand by what we’re telling you.   Executives spend an average of 25 hours a week in meetings, yet nearly half of those video calls and project updates could disappear without any negative impact, per a survey of over 10,000 desk workers by Future Forum.   Reluctantly going to noncritical meetings wastes about USD100 million a year at big organisations, according to another survey.  The studies found the top reason why business leaders went to unproductive meetings is that they thought it would be a good use of time, but ultimately wasn’t.  They also attend because they’re afraid to miss something important, and to show their own manager they’re working.   Reminds us of that old saying – ‘this meeting could have been an email’.  Just like the one you are reading now.  AI: Why Google Is Taking It Nice And Easy What You Know The once-a-little-known startup, OpenAI, took on Big G head-on in a fight for the spot as AI’s top dog.  Within just 60 days of its release, ChatGPT amassed 100 million+ users worldwide. Also, since it saw daylight, ChatGPT has passed multiple prestigious graduate-level exams in law and business, even going as far as passing the United States Medical Licensing Exam (USMLE).  On the flip side, Google recently released an ad for Bard (it’s own AI tool) that had incorrect information coming directly from the chatbot, resulting in the loss of over USD100 billion in market value for the tech giant. What You Also Know Even with an unspectacular tech stack, ChatGPT’s decision to offer AI to the masses through the web has revolutionised text generation through automation, having big ramifications on sectors like education, employment, and, particularly relevant to Google, the evolution of online searches.  On the other hand, Google has only allowed some groups to test out Bard before its full public release in the near future.  Plus, Blake Lemoine, an ex Googler, stirred up a storm by publishing a document in which he proposed the possibility of the AI being sentient. (ChatGPT had its share of lobotomy as well, BTW) What You Don’t Know ChatGPT might be winning the AI race for now, but soon Sam Altman will probably have to fly to Washington DC and spend afternoons with an 85-year-old farmer-turned-Senator from Idaho, to explain why his great-granddaughter was suspended from private middle school for using something called “the GPT AI.”  Jokes apart, our resident AI/ML lead, Dipak Singh, is doing some transformational work for enterprises with ChatGPT, Analytics and Artificial Intelligence in general. Reach out to Dipak to explore a solution for your organisation BFSI: Apple Is Ummm, A Bank Now? For all practical considerations, yes.  Let us explain. Sometime back, Apple drove an armoured cash van through the American banking industry.  Yeah?  True. While the average bank is paying less than 0.5% on savings accounts, the USD2.6 trillion tech giant announced it would dish out 4.15% (that’s 10X the national average) annual returns to savers. This, when regional American banks are balking in the wake of the Silicon Valley Bank crisis to maintain their deposit bases, and cash-starved fintech startups are gasping for breath.  Is It A Gravity Game Changer? Pretty much. Per Forbes, “as trust in traditional banks falters, the two most iconic names in tech and finance are joining together to create what might become America’s mightiest FinTech.”  Clarification on the other iconic name – since Apple does not have a banking license, it has teamed up with Goldman Sachs Bank, USA.  In pure fintech jargon, Apple is now a neobank like Jupiter and Fi Money – except its ginormous brand strength, with over two billion iPhones globally, is now serving as Goldman’s branch network.  At 4.5%, Where Are The Profits? Apple’s 10X returns savings account is less about profits than it is about bringing more iPhone owners under Apple and Goldman’s financial umbrella.  While two billion people around the world own Apple devices, fewer than 10% are Apple Card users, meaning there is a megatron* market opportunity waiting to be tapped already.  Net earnings from interest margins may not be Goldman’s priority either.   Profits or no profits, the iPhone user is certainly not complaining.  *megatron is a myth, but it sounds so cool, we used it for effect.  Pharma: Unable To Pear The Loss Pharma technology pioneers, here’s a reality check – one that is brought to you, courtesy, insurance companies.  What The Eff? Yes, Pear Therapeutics, creator of 3 FDA-cleared prescription apps to help treat substance use disorder and insomnia, just announced that it is, err, bankrupt, as the tech startup struggled to get insurers to pay for its technology.  Btw, we are talking about America here.  While doctors were willing to prescribe digital therapeutics and patients were willing to use them, “that isn’t enough,” Pear’s CEO Corey McCann wrote in this LinkedIn post.  “Payors have the ability to deny payment for therapies that are clinically necessary, effective, and cost-saving.” What made Pear special? Clinical robustness: Through high quality clinical trials, Pear demonstrated enhanced patient outcomes in substance use disorder and insomnia. Regulatory blessing: One of the earliest to get US-FDA approval, Pear saw 10,000+ prescriptions written for its digital solution. Investor enthusiasm: Pear raised USD300M in equity, USD100M in debt and went public last year with a valuation of USD1B+. Key Takeaway? Per Tushar Sadhu on LinkedIn, “external capital comes with its powers and responsibilities. Unrealistic valuation and pre-mature IPO undid the good work the company had done in product creation.”  Stuff We Are Watching  GoI’s Chatbot Plan: The Government of India is working to create a multilingual ChatGPT-like chatbot helpline that can be used to manage grievances of disgruntled consumers.   USD100,000 Saved by AI: ChatGPT use cases now run into millions, populating every nook and corner of social timelines, but how does

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The emergence of decentralised finance (DeFi) and the potential impact on traditional banking and financial services

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

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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How the Large Language Models like GPT are revolutionising the AI space in all domains (BFSI, Pharma, and HealthCare)

How the Large Language Models like GPT are revolutionising the AI space in all domains (BFSI, Pharma, and HealthCare)

Large language models or LLMs are ushering in a widespread AI revolution throughout multiple business and industry domains. DALL-E-2 set the cat amongst the pigeons in the AI segment in July 2022, developed by OpenAI, before ChatGPT came into the picture. This has put the spotlight firmly on the invaluable role increasingly played by LLMs (large language models) across diverse sectors. Here’s examining the phenomenon in greater detail.  LLMs make a sizeable impact worldwide With natural language processing, machine learning, deep learning, and predictive analytics among other advanced tools, LLM neural networks are steadily widening the scope of impact of AI across the BFSI (banking, financial services, and insurance), pharma, healthcare, robotics, and gaming sectors among others.  Large language models are learning-based algorithms which can identify, summarise, predict, translate, and generate languages with the help of massive text-based datasets with negligible supervision and training. They are also taking care of varied tasks including answering queries, identifying and generating images, sounds, and text with accuracy, and also taking care of things like text-to-text, text-to-video, text-to-3D, and digital biology. LLMs are highly flexible while being able to successfully provide deep domain queries along with translating languages, understanding and summarising documents, writing text, and also computing various programs as per experts.  ChatGPT heralded a major shift in LLM usage since it works as a foundation of transformer neural networks and generative AI. It is now disrupting several enterprise applications simultaneously. These models are now combining scalable and easy architectures with AI hardware, customisable systems, frameworks, and automation with AI-based specialised infrastructure, making it possible to deploy and scale up the usage of LLMs throughout several mainstream enterprise and commercial applications via private and public clouds, and also through APIs.  How LLMs are disrupting sectors like healthcare, pharma, BFSI, and more Large language models are increasingly being hailed as massive disruptors throughout multiple sectors. Here are some aspects worth noting in this regard:  Pharma and Life Sciences:  Healthcare:  The impact of ChatGPT and other tools in healthcare becomes even more important when you consider how close to 1/3rd of adults in the U.S. alone, looking for medical advice online for self-diagnosis, with just 50% of them subsequently taking advice from physicians.  BFS:  Insurance:  The future should witness higher LLM adoption throughout varied business sectors. AI will be a never-ending blank canvas on which businesses will function more efficiently and smartly towards future growth and customer satisfaction alike. The practical value and potential of LLMs go far beyond image and text generation. They can be major new-gen disruptors in almost every space.  FAQs What are large language models? Large language models or LLMs are specialised language frameworks that have neural networks with multiple parameters that are trained on vast amounts of unlabelled text with the usage of self-supervised learning.  How are they limited and what are the challenges they encounter? LLMs have to be contextual and relevant to various industries, which necessitates better training. Personal data security risks, inconsistencies in accuracy, limited levels of controllability, and lack of proper training data are limitations and challenges that need to be overcome.  How cost-effective are the Large Language Models? While building an LLM does require sizeable costs, the end-savings for the organisation are considerable, right from saving costs on human resources and functions to automating diverse tasks.  What are some potential ethical concerns surrounding the use of large language models in various industries? Some concerns include data privacy, security, consent management, and so on. At the same time, there are concerns regarding these models replicating several stereotypes and biases since they are trained using vast datasets. This may lead to discriminatory or inaccurate results at times in their language. 

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How A Loan Origination System Can Help Streamline Your Lending Process

How A Loan Origination System Can Help Streamline Your Lending Process

Why are loan origination systems gaining ground globally? Many lenders and financial institutions are of the opinion that loan origination system software tools backed by automation and other technologies are the best ways to enhance and streamline the overall lending process.  With a rapid leap towards digitization, conventional banking systems are finding it tougher to consolidate and grow their market presence.   With more consumers adopting fintech and other digital platforms for loans and other transactions, financial institutions are finding it favourable to invest in loan origination systems for future progress.  Digital open source loan origination systems can take care of the whole process of lending, right from the initial process of origination to the final disbursement. Institutions can tap such systems for enabling smoother onboarding of customers upon receiving their loan requests.  This system will take care of several aspects of the whole lifecycle, including application, credit checks, pricing of loans, digital KYC systems, and the final disbursal.  How A Loan Origination System Can Help  The basic loan origination system workflow helps immensely with regard to ensuring agile and smoother loan processes, while covering various kinds of loans, including retail, SBA, SME, commercial, and other types.  With the origination process well established, some of the biggest advantages include lower turnaround times for processing, greater data accuracy, real-time generation of reports, higher satisfaction of customers, greater monitoring and tracking mechanisms, and improved compliance and quality alongside.  Key Aspects Of Loan Origination  An online loan origination system will take several aspects into account, including the following:  Loan applications– This includes getting applicant details while helping people with their application formalities.  Processing– This covers the verification and collection of the information or details of applicants.  Underwriting procedure– This is a procedure which helps lenders work out if the loan applicant is a high or low risk customer and whether the loan request should be approved or not.  Disbursal– This is the last step where the formalities are taken care of and other details are scrutinized, while the loan amount is eventually disbursed.  Customer servicing– This covers all servicing-related steps, including dispatching reminders and also ensuring timely loan repayment.  What A Loan Origination System Should Possess There are several loan origination system requirements that should be kept in mind. These include the following:  Automated Lending Procedures  The origination system can help in automating end-to-end processes of lending, while centrally organizing workflows that cover everything from managing leads to the final disbursal and customer servicing.  A Unified And Single Customer Interface  The system should fuse various functions which are a part of the loan process under a single platform. This will lower manual and operational issues, while ensuring that customers get a more standardized and high-quality experience at the same time.  Digitized And Easier Loan Process The system should garner all necessary details digitally, while helping with easier archiving, tracking, retrieval, control, and traceability. The origination system will also lower manual errors and overall cycle timelines. Integration With Core Banking Mechanisms  The origination system should easily integrate with the legacy and core banking systems of financial institutions, while automating various aspects including validating credit scores, managing leads, and checking blacklists.  Configuring And Automating Credit Policies Deviation and credit policies usually begin with specific guidelines and are standardized through similar scenarios occurring repeatedly, which leads to higher wastage of time for workers in various sectors. The right automation system can take care of business cases which are repetitive and also enable empowerment of personnel to emphasize more on transactions with higher values.  Better Compliance Tracking And Management The loan origination system should enable a financial institution to manage compliance better, while arranging procedures seamlessly for easier traceability and visibility.  Better Deployment Systems The loan origination system should be flexible enough for ensuring that tailored solutions work in contextual scenarios, instead of being imposed and standardized solutions. This will lower the time of implementation while enabling swifter time-to-market for institutions as well.  A good loan origination system can enable quicker loan processing and better customer experiences in sync with digitization of the entire banking and financial services sector. This is why loan origination systems are becoming the preferred mechanism for several financial institutions. 

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