Because there are several petabytes (one thousand million million (10 15 )) of data coming from disparate sources. Considering the time factor, there has often been the need to summarize these in the blink of an eye. That is a lot to ask for, if you are human.

But what if you are not?

For, if we go by recent trends including Generative AI, whenever and wherever (with due apologies to Shakira for pulling her song out of context) the human brain falters, artificial intelligence ups the stake.AI does job immutably in minutes by “slicing and dicing mammoths amounts of data” and generating a crisper summary than a French toast.

If that gets you thinking, that is quite like DeepSight. You are not wrong. So, here’s why FIs and FinTech’s need a platform like it (DeepSight).

Crisp and Clear are of the essence for Data Management for Financial Services!

Financial Services require information that is concise and transparent. In the fintech and financial services sector, the demand for concise and precise data is even greater. However, it is difficult for humans to extract meaningful data from large amounts of literature without significant investments and additional resources. Automation and AI can effectively handle this task. It is crucial for Financial Markets, Capital Markets, and FinTechs to generate relevant insights quickly and clearly, surpassing the speed of the scientific research community. The stakes are high, involving stakeholders, investors, regulators, and the market itself as a disruptive force. Real-time data, with its differentiating value, can be easily achieved through AI-enabled platforms.

● Nowadays, an enormous amount of data is generated, much of which remains isolated.
● As companies rapidly evolve and mergers and acquisitions take place, the data also undergoes swift changes.
● Furthermore, there are still legacy ecosystems that are fragmented, consisting of multiple workloads/IT systems, isolated databases, and lacking in master data.

However, with the implementation of Magic FinServ’s DeepSight, an exceptionally productive and intelligent rules-based platform, financial services organizations can receive clear, concise, and actionable insights to guide their decision-making.

But before this can happen, they must ensure they have high-quality data. Duplicate, inconsistent, and redundant data serves no purpose in the current context.

Therefore, it is essential to establish the definition and key attributes of good data.

What is good data?

According to decision-makers, good data is any data that is current, complete, and consistent. Good data is also that data that reflects the true picture of how the organization is performing. For financial services and capital markets, good data would mean real-time, and up-to-date data related to the performance of the asset classes that they handle on a day-to-day basis. It would also include data that would help asset managers and FinTech’s stay on course when it comes to adhering to the regulations and compliance measures while protecting the interests of the investor.

Doing something about getting good data

The problem of data management can be well explained by the fact that the data still occurs in silos. While executives want higher-quality data and smarter machine-learning tools to support them with demand planning, modeling, and solution strategies. But there is no getting there without first decluttering their data and breaking down data silos to establish a single source of truth. The first step obviously is to get the data out of the silos and declutter it while establishing a single source of truth, or slice, dice and ingest.

Carrying out slice, dice, and digest!

Slicing, dicing, and ingesting data from a single source of truth involves the process of gathering,arranging, and structuring data from different origins into a central repository. This repository serves as the authoritative and consistent version of the data throughout an organization. This method ensures that all stakeholders can access accurate and reliable information for analysis, reporting, and decision-making.

Fintechs and financial organizations have various critical and specialized data requirements. However, the data originates from multiple sources and exists in different formats. Therefore, it becomes necessary to slice and dice the data for precise reporting, compliance, Know Your Customer (KYC) processes, data onboarding, and trading. In portfolio management and asset monitoring, the speed at which data can be sliced, diced, and ingested is crucial due to strict timelines for regulatory reporting.Failure to adhere to these timelines can result in severe consequences such as the loss of a license.

Data is sliced, diced, and ingested through several methods including data consolidation and integration, data modeling and dimensional analysis, reporting and business intelligence tools, as well as querying and SQL for various activities such as accounts payable (AP), accounting, year-end tasks, KYC, and onboarding.

The Golden Copy: Here’s how DeepSight and Robust Data Management in Financial Services practices gets you there

Here’s a brief on some of the techniques or steps involved in arriving at the single source of truth. Magic FinServ uses a combination of robust data management practices and intelligent platform for generating timely and actionable insights for accounts payable (AP), accounting, year-end activities, Know Your Customer (KYC), and onboarding.

Data Ingestion: Collection of data from different sources, databases, files, emails, attachments, APIs, websites, and other external systems. Data ingestion methods vary according to source – online, sequential, or batch mode to create a centralized location.

Data Integration: Once the data is ingested, it needs to be integrated into a unified format and structure. Data integration involves mapping and transforming the data to ensure consistency and compatibility. This step may include activities such as data cleansing, data normalization, standardization, and resolving any inconsistencies or discrepancies among the data sources.

Master Data Management: Creation of a reliable, sustainable, accurate, and secure data environment that represents a “single version of the truth.” In this step, the data is organized in a logical and meaningful way, making it easier to slice and dice the data for different perspectives and analyses.

Data Storage: The transformed and integrated data is stored in a centralized repository. Data Access and Querying: Once the data is stored in the centralized repository, stakeholders can access and query the data for analysis and reporting purposes. They can use SQL queries, analytical tools, or business intelligence platforms to slice and dice the data based on specific dimensions, filters, or criteria. This allows users to obtain consistent and accurate insights from a single source of truth. Asingle source of truth goes a long way in eliminating data silos, reducing data inconsistencies, and improving decision-making, while promoting data governance, data quality, and collaboration.

Now that we have uncomplicated the slice, dice, and data ingestion with DeepSight, another quick peek into how we have used DeepSight and Rules-based Approach to set matters straight.

Magic FinServ AI and rules-based approach for obtaining the single source of truth

Here are a few examples of how we have facilitated data management for financial services and data quality with the slice, dice, and ingest approach. Our proprietary technology platform DeepSight coupled with EDMC partnership has played an important role in each of the engagements underlined below.

Ensuring accurate reporting for regulatory filing: When it comes to regulatory filings, firms invest in an application to manage, interpret, aggregate, and normalize data from disparate sources, and fulfill their regulatory filing obligations. Instead of mapping data manually, creating a Master Data Dictionary using a rule & AI/ML-based Master Data provides accuracy, consistency, and reliability. Similarly, for data validation, a rule-based validation/recon tool for source data ensures consistency and creates a golden copy that can be used across enterprises.

Investment Monitoring Platform Data Onboarding: Existing investment monitoring platform for data onboarding was ensuring trade compliance by simplifying shareholder disclosure, sensitive industries, and position limit monitoring for customer holding, security, portfolio and trade files. The implementation team carried out the initiation, planning, analysis, implementation and testing regulatory filings. In the planning stage, we analyzed the customer’s data like Fund & reporting structure, Holdings, Trading regimes, Asset Types, etc., from a reference data perspective. Post the analysis, reference data is set up and source data are loaded. Thereafter, reference data is set up and source data is loaded once requisite transformations have been done. And now the positions data can be updated real-time with no hassle, and error-free.

Be sure where you stand relative to your data. Write to us for Financial Data Management solutions!

If you are not yet competing on data and analytics, you are losing on multiple fronts. We can ensure that data gets transformed into an asset and provide you with the head start you need. Our expertise encompasses a range of critical areas, including financial data management, data management in financial services, and tailored financial Data Management Solutions.

For more information, write to us at mail@magicfinserv.com.

The post The Art of Slicing, Dicing, and Ingesting – How AI Empowers FIs to achieve data excellence appeared first on Magic FinServ.

Learn the art of carefully stacking up the sandwich, and you can transcend from mediocre to an all-time great sandwich.

Just as with DevOps, which comprises multiple layers of tech stacks that need to be thoughtfully selected to ensure synchronization among the various teams involved in the build, development, design, and deployment phases of the software development lifecycle, it’s essential to remember that a delicious BLT stack relies fundamentally on the quality of its ingredients. By choosing the right components, you can create a truly delightful experience.

Choosing the condiments!

Just as a DevOps practice is about a culture – a culture that fosters responsibility, collaboration, and open communication between development, operations, and other teams involved in the software delivery process, a BLT sandwich too is a part of the American culture and like DevOps there is too no one size fits the rule. People have been experimenting with BLT, but for the ultimate experience, there are only four ingredients you need.   

Building the stack – the bread

First the bread – choose according to your taste and program according to enterprise or process need. Remember just as the bread must be fresh and slightly toasted to hold the condiments – cheese, veggies, eggs and patty.

Similarly, choose a programming language that can meet the requirements of the DevOps tasks and bind the technology stack – existing and new seamlessly. Be liberal with automation, like you had been with butter, because it is pointless to write endless codes that can be automated. Here are some of the programming languages that you can choose from, along with the benefits.

• Python: Readability and ease of use. The advantage of using Python comes from rich libraries, widely used, rich frameworks such Ansible for configuration management and Boto3 for AWS automation that simplify DevOps tasks.
• JavaScript/Node.js: Used primarily in web development. It is one of the most versatile programming languages used for the build automation and creating custom tools.
• Go (Golang): Used for writing microservices, container-based applications, and building CLI tools for DevOps tasks.
• Java: For building enterprise applications. For building robust and scalable DevOps tools or microservices for continuous integration and delivery.

Magic FinServ’s team builds a DevOps for financial services strategy that is in-line with your goals and expansion plans, which could be multi-cloud or hybrid, depending on the organization’s needs.

The Bacon/Patty/Vegan Alternative – Immutable part of BLT

Apart from the bread or bagel, the immutable part of any BLT sandwich is the bacon, meat, or vegan alternative. For you can remove the veggies or change the sauces and the pickle, but the bacon/meat/vegan alternative simply must exist. Else, it is no BLT.

Transform it to DevOps, it is the aspect of containerization that is central or immutable to any DevOps practice. Containerization involves packaging applications and their dependencies together into lightweight, portable containers to provide a consistent and isolated environment, enabling applications to run reliably across different environments, from development to production.

Instead of modifying existing servers, containers are designed to be immutable, so that when things do not go as planned, an updated version spring up. There is no patching or updating here for the servers. For DevOps financial services, Magic FinServ’s highly specialized team designs and maintains highly available & auto-scalable Kubernetes clusters (Azure AKS, Google GKE & AWS EKS) to manage docker containers.

Infrastructure as a code: the Cheese

Just as cheese is essential to a classic BLT sandwich and enhances the flavor profile when the right type is chosen, the selection matters. For instance, cheddar, Swiss, and pepper jack stand as excellent options. When toasted in a pan prior to melting, the experience becomes truly exceptional.

To achieve a more American or classic ambiance, provolone or fontina cheeses become indispensable.

Similarly, Infrastructure as Code (IaaC), a software engineering practice involving the management and provisioning of infrastructure (including servers, networks, and storage) through code, introduces a new dimension to DevOps. The automation of infrastructure provisioning and configuration using tools such as Terraform, AWS CloudFormation, or Ansible plays a pivotal role.

In Magic FinServ’s DevOps for Financial Services approach, the Infrastructure as Code concept simplifies and expedites the infrastructure provisioning process. It aids in averting inconsistencies and errors in cloud deployment, ensures policy compliance, enhances developer productivity, and reduces critical dependencies, all at a lower cost.

Monitor and Alert – The Hot Sauce

It is the hot sauce that transforms a BLT sandwich into a gastronomic delight, but one must be careful when it comes to hot sauce. For if the amount of hot sauce is less, the BLT tastes bland, and if it is more, the sandwich becomes too spicy for the tastebuds.    

Monitoring and alerting are the hot sauce of DevOps. These elements offer insights into the health and performance of applications and infrastructure and require prompt attention.

At Magic FinServ, we recognize the significance of addressing vulnerabilities and bugs early on, before they escalate. Monitoring and alerting stand as decisive components of our DevOps financial services package, and we are dedicated to identifying, prioritizing, and isolating application defects while pinpointing their root causes. This practice ensures transparency for the DevOps team concerning issues arising within the process chain. When it comes to monitoring, you have the option to choose between Nagios, Splunk, and DataDog.

The tomato, lettuce and Onion – the CI/CD and the automation aspect

Apart from the tomatoes and lettuce, you can also add onions to the sandwich. While tomatoes add juiciness to the sandwich, adding layers of lettuce keeps the bread from getting soggy. Just like lettuce, CI/CD are a constant in DevOps practice. It is used to automate and improve the process of software delivery, allowing for the rapid and repeated release of new features, enhancements, or bug fixes with minimal manual overhead. For our CI/CD process, we utilize best-in-class tools, including GitLab, Jenkins, Azure, and Kubernetes.

This is how we create our DevOps BLT sandwich, if you would like to have a bite or have a taste of our devops services for financial industry or any other financial technology solutions, write to us mail@magicfinserv.com.

The post Crispy Code, Fresh Lettuce, Tangy Automation: The DevOps BLT Sandwich Delight appeared first on Magic FinServ.

When Mario was first launched in 1983 no one could have guessed that Nintendo’s plumber would end up becoming one of the most famous cartoon characters ever. But he has, and it is not due to his ability to flex his muscles, but his infinite avatars, steady evolutionary graph, and the creative ability of the franchise to be ahead of the times.

As the Super Mario Bros Movie sets new records at the box office – earning a massive $58.23 million in its third weekend of release, a shout out to all Financial Institutions and FinTech’s to ingrain Super Mario’s characteristics and topple the Minions (the disruptions) with smart work, intelligent processes, and a partner like Magic FinServ.

Here is how to be like Mario and out run the Minions.

# 1 Have a trusted and loyal ally

The reason Mario survives all the escapades is because he has allies. Princess Peach, his twin brother, and many others who help him in his multiple adventures.

DeepSight^TM – the trusted ally for fintechs

FinTechs need allies as well. They need an ally that understands their specific needs and provides them with customized solutions. Whether it is the automation of long-winded, repetitive, and mundane tasks or streamlining processes and ensuring STP, or ensuring ROI on the new tool that they have purchased, or simply amplifying the customer experience, DeepSight^TM can do all of that for fintechs. DeepSight^TM AI Optimization framework integrates process workflows and utilizes structured and unstructured data to build tailored solutions that reduce the need for human intervention. This promotes upto 70% efficiency in Front & Middle office platforms & processes. It provides their legacy systems with a new lease of life by integrating with the existing workflows and architectures seamlessly and ensuring accuracy, efficiency, and productivity.      

# 2 Adapting and overcoming obstacles with least possible resources:

The reason the Mario franchise has thrived all these years is simply because they have been extremely agile and adaptable. Mario always gets his girl- Princess Peach. He always manages to rescue her from the Browser making up new tools and overriding the obstacles with a new imaginative approach.  

Magic FinServ’s winning deals: Helping fintechs adapt to changing times and customer preferences  

Financial services have undergone a massive transformation in recent times. The need to provide an enriched customer experience in KYC is greater than before, however considering the flux that markets, fintechs must also measure the ROI when it comes to any new investment. In this catch 22 kind of situation, an AI and ML powered solution that can be planted and baked into existing applications to better it, while reducing the cost of ownership, and eliminating the overhead of paying for recurring subscriptions holds an edge over an off-the-shelf product. That solution is DeepSight^TM  

True digital transformation or modernization comes when organizations and processes are agile and adaptable to changing circumstances, because not everyone can build from scratch. Fortunately, fintechs have the advantage of a partner like Magic FinServ. Magic FinServ’s financial services solutions, like Mario’s trusted power-ups and tools, are built to scale and to be agile as per circumstances. We have a three-fold strategy for creating value, which begins with building a partnership – understanding the challenges, with the focus always on data management and technology, and pursuit of digital transformation.

#3 Evolve continuously and constantly! Only the fittest survive

The secret of the FinTechs success story is their ability embrace any disruption quicker than the rest and ensure faster, smoother, and richer engagement with the customer compared to the monoliths or the banks and legacy FIs.  In 2023, as the businesses (capital and financial markets) demands greater levels of personalization and engagement, Magic FinServ assures that fintechs stay on top of the game, here’s how.       

Magic FinServ: How we help the FinTechs evolve

Like Super Mario, we have several superpowers that can give a boost to the fintech’s evolutionary journey.    

• A data expert partnering with the EDMC   
• A cloud and DevOps expert
• Automation expert on workflows and APIs
• Legacy transformation and rapid digitization experts
• RegTech experts
• DeepSight^TM for making light mundane and repetitive work

We are also expanding our reach to new and unexplored domains such as generative AI and low/no code support and maintenance

We have a center of excellence for each of the avatars that we possess to keep abreast of the times. Our expertise in all the latest practices of Agile and DevOps, AI/ML, and the cloud enables a quicker, smoother transition/ evolution from stage 1 (largely manual and legacy architecture dependent) to a highly automated/advanced stage, and then to a futuristic stage that relies entirely on APIs and extremely intelligent and intuitive platforms.  

# 4 Process Optimization: Leveraging Technology and Quality Data

Just like Mario needs to collect coins and power-ups to progress through the game, fintechs need access to financial services and tools that can help them grow and scale their business.

Magic FinServ’s extended suite of solutions to prime up to every FinTech need

Magic FinServ offers a suite of solutions that can help fintech’s with everything from payment processing to compliance, giving them the resources, they need to succeed.

Advisory Services: Leverages capital markets domain and understanding of business rules to create foundation for game changing digital transformation

Cloud Migration and Management: SaaS enablement of Fintech and custom IT platforms, best practice driven migration to cloud leveraging native properties of Azure, AWS, GCP

Quality Engineering: Magic FinServ performs comprehensive Functional, Performance Load, Security and User Acceptance Testing for our clients. We offer unique frameworks to build automation pipelines using custom solutions as well as industry standard tools like Selenium and Cypress

DevOps and Automation: Leverages Magic’s proprietary automation fabric framework to build frictionless CI/CD and automated testing pipelines, using custom or open-source tools; thus, enhancing time to market

Production Support: Proactive SLA driven support/maintenance of applications, environments, and infrastructure (cloud) to ensure scalability, stability, and availability.

Platform Engineering and Integration: Leverages next gen & cloud native technologies, including Python, Node.js, Angular etc., building on inputs from advisory services to build, implement and modernize fintech platforms. Also, build and manage APIs, custom interfaces, data feeds in an automated manner to achieve seamless integration between OnPrem and Cloud.

AI/ML driven user experience: Leverage Deepsight^TM , a Magic FinServ platform with AI/ML and RPA at its heart, to automate and integrate last mile business processes for improved user experience and enhanced benefits realization

# 5 Customizing response to different environments

Lastly, in each of his journeys, Mario navigates through different worlds and environments, each with their own unique challenges and obstacles, by smartly adapting as per need and using resources that are readily available.  

Magic FinServ: How our rules-based solution is an ideal solution for meeting compliance and regulatory needs for different jurisdiction    

In the fintechs world, there is increasing pressure to confirm rules and regulations. When you are operating in multiple geographies this can be cumbersome, as each region has its own set of rules, timelines, disclosures, etc., related with KYC, shareholding disclosures, ESG disclosures, AML, etc., and violations are severely punished with fines and penalties.  

We address the key requirements according to geographies with an AI and ML powered approach that takes the rules governing that data for the jurisdiction and updates their impact on the value of key information, thereby ensuring that critical information is up to date. Our unique “rule-driven” solution with Data Management, Document Record Management, AI, ML, API Integration, and Reporting and Dashboard are powered to ensure that funds and wealth managers are kept up to date with the latest developments.

 Be like Mario: Embrace disruption without falling apart!   

Just like Mario needs his power-ups and allies to succeed, fintechs need reliable financial services solutions and experienced partners to help them grow and thrive and Magic FinServ is that partner. Magic Finserv’s suite of solutions can provide fintechs with the resources they need to succeed in the competitive world of fintech and give them a winning edge over the competition while navigating the complex financial regulations and compliance requirements.

The post 4 Ways FinTechs can Unleash Super Mario’s Superpowers & Thrive in a World of Minions appeared first on Magic FinServ.

The Kind of Tests Programmers Run during SDLC

The job of programmers or QAs is not easy, they run reams and reams of codes, write codes from scratch, and decipher the gaps/bugs/vulnerabilities with little help apart from the coding libraries and their experienced seniors. As a runup to the SDLC, a programmer or a QA will run tests such as:  

• Integration tests: for finding out whether the components merge in the larger subsystem; interact with other components and whether the data flow is smooth or not, along with testing the interfaces and contracts for compatibility, environment testing, and testing scenarios. 
• Smoke tests: a smoke test checks if the basic functionalities of the software are working properly before proceeding with more comprehensive testing. 
• Release to beta users: gather valuable insights, identify and address issues early, and ensure that the final release meets user expectation  
• Regression testing: The purpose of regression testing is to verify that previously tested and working features of the software continue to function correctly after modifications or enhancements have been made. It helps ensure that changes in one part of the software do not adversely impact other parts.  

Most of the time the tests that are underlined above run in parallel. As there are a million things that programmers or QA teams must address at one and the same time, the chances of queues building up when you are working manually or have not invested in an end-to end automated system, for facilitating testing, are inordinately high. 

Testing queues: An emblematic problem with software testing

Software testing queues present a notable challenge in the realm of testing, causing difficulties for programmers when juggling multiple tasks and determining priorities. They face the dilemma of whether to focus on resolving the existing test issues or addressing the previously identified bug that exposes a vulnerability, all the while contending with overflowing pipelines. Alongside the issue of bloated testing, additional concerns arise from problematic code stemming from legacy systems and a lack of documentation, insufficient resources, and strict deadlines, resulting in unnecessary apprehension. Furthermore, programmers are burdened with handling environmental matters, such as configuring a test environment to resemble the production environment, grappling with intricate and hard-to-isolate bugs, and effectively managing test data. These manual processes consume a significant amount of time. Hence, there arises a necessity for a platform that combines artificial intelligence/machine learning (AI/ML) and robotic process automation (RPA) to expedite the testing process while ensuring efficiency, transparency, and accuracy.

Meet the QA Companion: Turbocharging the SDLC 

If there is an area where AI is silently revolutionizing, it is the software development lifecycle, encompassing not only coding tasks but also quality assurance (QA). According to a McKinsey study, generative AI can accelerate coding tasks by up to twice the speed, while AI’s role in QA serves as a key differentiator, ensuring quality, transparency, and timeliness.

Magic FinServ’s QA companion, powered by AI, addresses all testing challenges throughout the SDLC. This intelligent solution takes care of tedious, repetitive, and complex testing aspects. With its exceptional intelligence and intuitive nature, it automates tasks, enabling developers to build high-quality software and achieve faster and more reliable release cycles, even when dealing with extensive test suites and challenging tests. Moreover, it provides actionable insights based on its built-in intelligence.

• By efficiently handling humongous amounts of data, surpassing previous capabilities, the QA companion mitigates risks and reduces unnecessary redundancy simultaneously.
• AI-assisted testing eliminates friction between teams.
• The AI-assisted QA Companion takes on most of the demanding tasks, resulting in a highly enriching and empowered developer experience, promoting workplace efficiency.
• Lastly, developers no longer need to rely on more experienced colleagues for assistance, as QA can fulfill their needs by explaining new concepts, synthesizing information, and providing step-by-step guides.

Unique selling points of Magic FinServ’s QA Companion 

The QA companion serves as a reliable aid in navigating the SDLC, offering automation and intelligent code generation that far surpasses human capabilities in terms of time efficiency. Here are some key features that highlight the value of the QA companion for programmers and QA teams:

• Effortlessly track and communicate testing progress in a highly effective manner with the help of the QA companion.
• Seamlessly process data from various file types, including handwritten notes.
• Utilize the in-built test scenario generator to produce intelligent test cases and scenarios, ensuring the pursuit of only necessary test cases and preventing test bloating.
• Download AI-generated test cases and scenarios in any desired file format, customizable to meet user output requirements.
• Generate automated scripts and eliminate the tedium associated with writing code from scratch multiple times.
• Manual scripting becomes unnecessary as the QA companion supports a wide range of scripting languages, such as Python, Java, JavaScript, C++, and more.
• Experience the benefits of a streamlined testing process within agile workflows, integrated with Agile tools like JIRA.
• Leverage the code optimizer’s smart detection technology to identify best practices, code smells, and vulnerabilities.
• Generate high-quality reports, including test plans, test strategies, execution reports, and more.
• Ensure continuous testing throughout your development pipeline, guaranteeing quality at every stage.
• Accelerate time to market by shortening project/product deployment times, gaining a competitive edge in the market.

Now you can bid goodbye to all the juggling between tests as the QA companion not only allows you to carry out tests in parallel tests without getting lost, but it also ensures that you are in control when it comes to timelines and releases. For a more comprehensive discussion on what the QA Companion can do  and its role in Financial Quality Assurance and Quality Assurance in Financial Services, write to us at mail@magicfinserv.com

The post Is your testing getting bloated? It’s time to get acquainted with our QA Companion! appeared first on Magic FinServ.

Barbie, one of the most anticipated movies of the year, is finally here. Running a packed house and setting new records, Greta Gerwig’s Margot Robbie and Ryan Gosling movie has all rethinking the zeitgeist of the time which is certainly neither black nor white – it is pink.  

Once frowned upon, 2023’s summer is splattered with pink; Anne Hathaway, the Princess of Wales, Margot Robbie, and others have worn Barbie’s favorite color on multiple occasions. But the zeitgeist of the Barbie movie is far more serious. It is a creative attempt to dispel many of the prevailing notions about gender stereotypes in a true Greta Gerwig manner. In particular, the kind of stereotyping that implies that blondes are dumb and wearing pink means that you are silly and not smart enough. With Barbiecore signaling an open rebellion against the notion of gender stereotypes, women (including trans women) across the world are embracing their femininity in a manner that would have seemed a bit overwrought in another time or year.

Organizations have 30 years of existence in the Financial Industry and are still subject to stereotypes.

Fintech companies have faced a unique and pervasive form of stereotyping in the business world. Despite the emergence of the first fintech pioneers like PayPal and Bloomberg over 30 years ago, these companies continue to be confined by various misconceptions. Some of the most prevalent stereotypes imposed on fintechs include the following:

• Fintechs are seen as mere disrupters, shaking up traditional financial systems.
• There is a perception that fintech primarily caters to Generation Z and young individuals.
• Fintech companies are often wrongly assumed to be unregulated, operating in a regulatory gray area.
• It is wrongly believed that fintech companies do not adhere to necessary compliance measures.
• Fintech is unfairly perceived as not actively promoting inclusivity in its services.

Spurred by the magic of the Barbie movie, we hope to rub-off many of the fintech stereotypes that exist even today, while pointing out the accessories/assets that fintechs require to nail the #barbiecore trend. 

Dispelling the Stereotypes

Do fintech companies truly live up to their reputation as disrupters?

Financial technology solutions have stepped in to personalize, streamline, and enhance operations, leveraging open banking APIs to ensure accuracy, transparency, and efficiency. With processes speeding up and response times improving, the integration of Deep Intelligence in these applications provides up-to-date information. As a result, the traditional boundaries between disrupters (fintech) and the disrupted (banks and financial services) are gradually fading away.

Currently, there exists a strong collaboration between banks, financial services, and fintech companies, particularly in the back and middle offices, where manual and repetitive tasks were once overwhelming.

Are Fintechs exclusively serving the millennial generation?

In the beginning, fintech companies primarily focused on catering to the tech-savvy millennial generation. However, this is no longer true. The modern fintech industry is now actively targeting a broader customer base, including baby boomers and retirees who constitute 25% of America’s wealthiest population and will remain so until 2030. Fintech is now offering personalized content for portfolio management, timely advice, and up-to-date financial services, as well as fraud prevention, all of which can significantly empower seniors.

Do Fintechs abide by the same regulations as banks and financial institutions?

It’s intriguing to note that fintechs are now among the most heavily regulated businesses, primarily due to their significant investments in cutting-edge technologies such as cloud computing, artificial intelligence, and data analysis. Consequently, when there are changes or updates to regulatory rules or new amendments are introduced, fintech companies seamlessly incorporate these changes into their workflows and backend systems using automated and rules-based approaches, ensuring transparency, accuracy, and timeliness.

Dispelling the Notion that Fintechs neglect Diversity, Equity and Inclusivity

Nothing could be more wrong. Fintechs basic premise is inclusivity. They were the first to come out with an out-of-the-box approach and offer affordable, and customized services and solutions related to finance, mortgage, and loans processing to customers who could not approach the traditional banking and financial institutions.  Today, fintechs have democratized finance and anyone can trade in stocks and decide how to manage their portfolios and make payments from the comforts of their home thanks to fintechs.

Fintechs have also taken the center stage when it comes to complying with ESG and DE&I. They are either showcasing their commitment to DE&I through vision and mission statement or have ensured that reporting pertaining to DE&I such as GRI (Global Reporting Initiative), Bloomberg, Refinitiv, etc., are fee or available at a price. Because either way the investor has the right to know.

While fintechs promote inclusivity in their business practices, their workspaces are one of the most diversified and equitable.    

Reconsidering Compliance measures in the Fintech industry

Earlier, fintechs were not expected to follow the kind of rules and regulations that banks and other financial institutions had to comply with. Fintechs could therefore work out of the box and forge deep ties with the customer using personalized approaches and instill a degree of agility that was not possible earlier. However, there has been a sea change and fintechs today come under the ambit of the same rules and regulations that govern banks and FIs. Also, in the case of many fintech-bank collaborations, it is imperative for fintech to raise the bar and ensure compliance under all circumstances and hence the stereotype that fintech does not follow compliance measures does not apply.  

Nailing the zeitgeist of the times with Magic FinServ

If Barbie uses fashion to defy gender stereotypes, fintechs rely on the cloud, AI-enabled tools and platforms to nail the prevailing zeitgeist of diversity, inclusivity, and acceptance. As an AI company, here’s how Magic FinServ has been changing the narrative around fintechs with tools, platform and resources. 

Faster onboarding, KYC, and due diligence with DeepSight for CX, inclusivity, and regulation compliance

While the fashionistas can easily nail the Barbiecore trend as there is a flood of pink-colored clothing and accessories for both genders, for fintechs embracing the zeitgeist (diversity, inclusivity, and acceptance) would require some sea changes and increased levels of collaboration. For example, for swifter and streamlined onboarding, KYC, and due diligence, just investing in a powerful tool or platform is not enough. For quicker onboarding of customer data, DeepSight, an AI-driven platform ensures faster onboarding of customer data, while also using a rules-based approach that ensures that only relevant data points are extracted, which makes it easier to draw premises and make intelligent decisions quicker than ever before. Quick data onboarding and KYC delights the customer and results in highly engagement and inclusivity.   

Relying heavily on automation for doing the heavy lifting with regards Testing, QA, and DevOps

When the whole world turns “pink” can you afford to be left behind. Whether it is day trading or payments or even loans processing, ease of communication with the customer is vital for creating a truly enriching customer experience.

However, for a truly great application or front-end, or for enabling a lean platform-centric model, there is a lot of heavy lifting that must be done at the backend. A good user-friendly interface is not built by magic. Behind the scenes teams of developers and QA work in tandem to build the product.

When backed by robust DevOps and Quality Assurance automation solutions such as Magic FinServ’s QA Companion, firms can deliver on the promised timelines without sacrificing the quality. Whether it is code commit, or coding bloating, or generating automated scripts so that manual effort is kept at a minimum and QAs have more time and effort in their hands to work on details related to personalization, UI/UX, and enhancing the customer experience.  

Streamlining with Magic FinServ

As fintechs operate across multiple jurisdictions and subject to the same intense regulation as traditional financial institutions, compliance can be a challenge. The challenge is more so for banks that partner with fintech to access innovative technology.  There are risks associated with data privacy and consumer protection, for example the Payment Card Industry Data Security Standard (PCI DSS) and the General Data Protection Regulation (GDPR) that must be addressed. As a fintech provider team up with the experts at Magic FinServ who have years of experience addressing such issues. We provide fintech consulting services that will help ensure transparency, efficiency, and productivity while meeting timelines for monitoring and reporting.

Get smart with our financial technology solutions and get going with barbie. For more write to us at, mail@magicfinserv.com.

The post How Barbie’s Summer of Pink Echoes in Financial Organizations appeared first on Magic FinServ.

How did David emerge victorious in the battle with Goliath? With a slingshot. From the five stones he had picked up for the battle, David just needed one stone to defeat the giant (Book of Samuel, Old Testament). While much has been written about his intelligence and valor, his aim streamlined and precise was just as important in ensuring Goliath’s defeat. From a purely technical standpoint, since we are in the technology and data business, had David been late by a split second, or had his aim not been streamlined or precise, the story of David and Goliath would have had a different ending.

Similarly, in financial and capital markets, there is a lot that can be achieved (or lost) when processes are not streamlined, particularly in critical areas like invoice processing. Just as David’s perfectly timed and streamlined shot delivered maximum impact, a streamlined invoice processing mechanism shields organizations from irritants such as delays, errors, and penalties, and future proofs them from disruptions and missed opportunities.

Understanding the Essence of Invoice Processing

In simplest terms, invoice processing is defined as the series of steps that takes place right from the time when the supplier invoice is received to the time when it is paid and recorded in the general ledger. The invoice can be received via mail, or as a PDF attached to an email, or as an e-invoice. Whatever the format, the invoice must be manually/automatically scanned into the accounting system, digitized, ETL performed, data validated, and later inserted in the workflow approval and payment system.

Why Manual Invoice Processing is No Longer Viable

While earlier, invoice processing was largely dependent on human effort, most organizations are now moving to some forms of invoice automation solutions. This shift is primarily driven by the complexities of global financial and capital markets, which involve multiple asset classes. Manually processing invoices is impractical due to the higher likelihood of errors introduced by humans and the significant amount of time it takes, such as a lengthy 19-day process. Consequently, implementing automated workflows with Straight-Through Processing (STP) becomes a strategic investment that empowers firms to improve their spending practices and enhance efficiency.

Getting there: Why Rules-Based AI/ML Engine Critical for End-to-End Automation

While hedge funds and asset managers invest in intelligent platforms like Coupa and SAP Concur, they are still unable to accrue the true benefits. Many still rely on manual labor at some stages of invoice processing. For example, while an automated platform makes the processes of extraction of relevant information easy from the plethora of document types, there are other more complicated information that must be extracted for non-PO invoices, such as allocation and tax withholding, which require a more advanced invoice processing solution than just plain data extraction or OCR. It requires the application of pertinent business rules for ensuring that invoices are processed correctly and do not result in compliance or regulatory failures. While a centralized invoice receipt, digitized information (including data from emails, faxes, and email attachments) and optimized processes – internal sources and outsourced integrations) are prerequisite for ensuring productivity and efficiency, but for true transformation, additional value with quality and compliance, absolute traceability, and control end-to- end is also necessary. And hence the need for a platform like Magic DeepSight^TM for both structured and unstructured invoices.

Magic DeepSight^TM : When your need is for a Streamlined and Advanced Solution

Since we are talking about the David and Goliath, all it takes to sort out the invoice processing problems is well-sorted, streamlined solution like DeepSight^TM, that can be easily integrated with existing invoice processing platforms and organization-wide workflows, organizations can counter traditional invoice processing woes related to lack of efficiency, high costs, no real-time financial visibility, non-compliance, penalties, reputation damage, business disruptions, and revenue leakage with ease.

DeepSight^TM brings together the best-of-breed technologies such as AI, Robotic Process Automation (RPA), machine learning, a rules-based engine, and analytics, to integrate seamlessly in existing systems and transform how your businesses handle invoice data. Highly advanced, DeepSight^TM builds up the right momentum for modern enterprises (enriches data quality with a rules-based, deep learning/self-learning approach), and facilitates institutions to make well-informed decisions. Its user-friendly interface is a significant value-add as it helps finance teams be aligned and on the same page.

What makes DeepSight an Exceptional Tool for Automated Invoice Processing

1. Complete End-to-End Solution
   DeepSight is the ideal solution if you seek an end-to-end approach. It ensures a smooth and efficient invoice processing experience, whether you’re dealing with PO or non-PO invoices, requiring minimal human intervention. While conventional automated Invoice Processing platforms, even the most intelligent ones, focus on data classification, extraction, and cleansing, they fail to utilize business rules for determining the appropriate invoice allocation for non-PO invoices, necessitating manual work. However, DeepSight stands apart with its intelligent data technology. Its AI/ML engine not only extracts data but also offers significant value by performing critical analytical functions. This capability proves invaluable for Hedge Funds, Investment Managers, and Brokerages handling a vast number of non-PO invoices alongside their PO invoices.
   DeepSight utilizes a pre-built, highly intelligent, advanced, and comprehensive rule-based AI/ML engine to effortlessly determine allocations and tax withholding. This process effectively meets essential compliance and stakeholder requirements while preventing revenue losses. The enhanced invoice information, also referred to as the golden data, is securely stored in the internal accounting system through Magic FinServ’s API for accurate record keeping. By offering a single window or centralized single source of truth, it promotes transparency and traceability.
   DeepSight’s continuous upgrades and updates enable it to adapt to new information using its pre- trained AI/ML and rule-based data extraction capabilities. This results in an end-to-end automated solution that learns with minimal supervision, making it an exemplary version of such a comprehensive solution.
2. Rules-Based Data Extraction through Pre-Trained AI/ML Models
   DeepSight’s intelligent document content recognition performs accurate identification, classification and segregation of documents. Critical data elements from documents are recognized and extracted by pre- trained ML/AI models through a rules-based engine. Incorrect, Out-of-date, Redundant, Incomplete, Incorrectly Formatted extracted data is cleansed utilizing DeepSight’s reverse lookup algorithm and pre- trained models. So, more insights and less effort.
3. Straight Through Processing (STP)
   One of the key requisites for future-proofing any process is STP. Data from invoice documents is extracted, cleansed, transformed and invoices are created in Coupa without requiring any manual intervention or active monitoring is required.
4. Streamlined Exception Management
   The system will be implemented with an exhaustive exception workflow to alert users for any manual input (if required). Real-time exceptions resolution mechanism available in the system (Review UI) aims to reduce redundant effort of filling same information every time with onset of new legal entities/funds/deals Our rule-based user interface ensures clean and consistent data, reducing errors, and streamlining the process for Coupa customers.
5. Enabling Traceability with Regimented and Well-defined Processes
   One of the major requirements when it comes to invoice processing is traceability. DeepSight system provides audits in exception handling, error handling, and changes in rules. These are performed in a well-defined and regimented manner. All activities are documented as version changes or user actions as appropriate and can be accessed via the audit table or in the form of reports for further audit.
6. Create Standardized Nomenclature
   All of the business rules/key parameters will be picked from a Single Golden Copy (maintained in DeepSight). This nullifies the chances of inadvertent human errors that can result in data integrity issues.
   By embracing streamlined and automated invoice processing, it is possible for organizations to unlock multiple benefits. They can eliminate bottlenecks, improve accuracy, enhance visibility into financial operations, and achieve greater control over their accounts payable function. They are also in a better position to direct their time, effort and resources for more strategic and value-added tasks.

DeepSight futureproofs Invoice Processing for a Global Alternative Investment Manager

A global alternative investment manager that was facing problems due to its archaic largely manual- oriented invoice processing, was able to tackle high-level issues related to redundancy, productivity, costs, etc., with DeepSight^TM. The customer’s business across different asset classes such as credit, private equity, and real estate, was difficult to manage due to the extremely high volumes of invoices. Manually mapping the complex business rules related to charges and tax withholdings was not an easy task to accomplish manually. With Magic FinServ’s DeepSight^TM, the client was able to override the obstacles of time, operational costs, and errors while bolstering efficiency and productivity. Provided below is a step-by step guide of how DeepSight was able to meet the client’s objectives.

• Parse through diverse invoice formats whether it is an image, PDF, excel, etc., with ease
• Using DeepSight, the global alternative investment company, was able to extract information smartly and accurately related to different vendor invoices and carrying varied templates.
• One of the biggest advantages of the tool is its ability to self-learn user’s action and feedback, thereby making it easier for the tool to auto populate from new learnings.
• Our advanced and highly comprehensive solution based on AI/ML, fixated issues related to tax withholding and allocation with a rules-based approach.
• For ensuring seamless end-to end processing, data was enriched via RPA and an RPA-enabled workflow was implemented for approvals and authorizations processing.
• Using APIs for seamless integration with the core platform

The use case above exemplifies how DeepSight^TM can be easily integrated with existing workflows or platforms to provide the results that firms had been looking for.

A truly transformative Invoice processing with DeepSight^TM

While productivity and cost savings are the essential pillars of automated invoices, truly transformative invoice processing is one that focuses on increasing stakeholder satisfaction, improving agility and ensuring better management of working capital. For true transformation, additional value with quality and compliance, absolute traceability, and end-to-end control is also necessary. As a new shift is surfacing in the business ecosystem, it is time to redefine invoice processing and shift from the traditional approach to the DeepSight^TM approach powered by AI technologies. With a highly refined and comprehensive solution that self learns with little help and has the gigantic capacity to scale up while ensuring end-to-end automated invoice processing of both PO and non-PO invoices, organizations not only can significantly reduce the percentage of errors and improve efficiency, but more essentially, they get a head start because of the deep insight they have gained thanks analytical capabilities of DeepSight (with rules-based approach) and an end-to-end solutioning of invoicing and prevention of revenue leakage.

For more information on how we can transform and enrich invoice processing with DeepSight^TM, drop us a mail, at mail@magicfinserv.com to know about our invoice automation solutions. Even if you already have invested in an IP platform, you will be surprised to find what you are missing and how we can ensure a true end to end automation, where you will not have to worry about manual work ever again.

The post The Power of Automation: Revolutionizing Invoice Processing in Hedge Funds & Capital Markets appeared first on Magic FinServ.

What seemed like wishful thinking once is now within reach thanks to the Developer Companion, an Artificial Intelligence-enabled platform designed specifically for the harried developers and development teams walking the thin line between contradicting business interests. The Developer Companion can do a lot more than just write a line of code, as you are about to find out very soon. But before that, a sneak peek into the developments that are underway in software programming.

Coding Goes through a Shift in Financial Software Development

The approach to financial software development has been undergoing a massive shift thanks to Artificial Intelligence and Machine Learning. Though Integrated Development Environments (IDEs) have been around for some time now, providing autocomplete features that take away some of the pains of coding, AI has been ushering in a paradigm shift underway in the world of software development. AI- assisted coding is simply the use of artificial intelligence/machine learning models to generate code automatically. AI-assisted code generation marks a new epoch because it relies on prebuilt code modules to build applications without the developers writing much (or any) code themselves. Instead, AI-assisted coding tools generate custom code entirely from scratch based on comprehensive training data and smart algorithms. Or to say, the central premise of these tools is the LLM model, that includes training on massive amounts of data existing source code — which usually comes in the form of publicly available source code produced by open-source projects. All that the developer has to do is ascribe in natural language what they want from the code. And viola! The tool does the rest.

With More Time in their Hands, Developers Turn into Superheroes

Artificial intelligence powered coding provides a new lease of life to financial software developers. With the power of AI, we are unlikely to see them frantic, their heads buried in the computer screen figuring out the next line of code or fixing a bug. Assuredly, when writing a boilerplate code for uploading a file, is no longer their sole preoccupation thanks to artificial intelligence and machine learning, they would have time to focus on the real core activities such as:

• Brainstorming with product teams and carrying out requirement analysis
• Bettering systems design and designing engaging user experience,
• Planning the development and other implementation details to ensure timeliness and accelerated time to market
• Continuously update and better their skills set
• And in the process metamorphizing from a mere developer to a superhero

Now, let’s move on to the tool that turns them into a superhero and how it accomplishes this.

Developer Companion: Elevating Platform Engineering for the Ultimate Developer Experience and Efficiency

The Developer Companion is an artificial intelligence powered coding companion or rather a teammate for developers. The Developer Companion empowers developers by taking away the mundane aspects of their work and providing them time to focus on core valuable and higher-level activities instead of repetitive administrative tasks. Whether you’re starting from scratch or enhancing existing applications, Developer Companion is here to empower you every step of the way, here’s how:

Increased productivity: With the Developer Companion, developers can save time, improve quality, and increase efficiency. By slashing down the administrative work drastically, the Developer Companion can enable developers to focus more on the design and functional aspects of the coding work, along with other valuable and higher-level activities.

Accelerate the time to market: Thanks to the Developer Companion, and AI-based code prompters, developers can ensure a faster time to market. Instead of carrying out mundane and time-consuming tasks, like writing unit tests or translating code from one language to another, developers can complete the tasks much quicker.

Empowering developers: Whether you’re starting from scratch or enhancing existing applications, Developer Companion is here to empower you every step of the way. It does much of the heavy lifting, leaving developers to focus on truly critical aspects of work.

Extremely intuitive: It will not only predict the next line of code, but to understand your intent and infer context from what you’ve already written (including comments) to generate valid code. Not to mention, it makes mundane and time-consuming tasks, like writing unit tests or translating code from one language to another much easier.

Advantages of Developer Companion that You Cannot Afford to Miss!

Provided below are the tangible benefits of Developer Companion, that you cannot afford to miss out on:

Generate Code Snippet with Ease: Code snippets are templates that make it easier to enter repeating code patterns. Developer Companion can automatically generate code based on high-level descriptions or specifications. For example, AI models can analyze natural language descriptions of a desired program and generate corresponding code snippets or even complete programs. This can help automate the initial stages of coding and reduce development time.

Review the Code with Confidence: Developers have to accept (or reject) automatically generated code as they work. For some developers, the need to review code constantly could be distracting. They may be able to work more efficiently if there was a tool to review all code.

Navigate Complex Codebases with Code Comprehension: Whether it is complex code or legacy code, navigating through both is tricky on account of the complexities involved, lack of documentation, interdependencies, scale (number of lines of code, file size, terms of lines of code, number of files, and overall project scope, and in the case of legacy code there are multiple iterations, updates, and maintenance issues involved as well). Codebase or source code also encompasses multiple modules, libraries, and frameworks. However, the Developer Companion can easily navigate through the complexity of the codebase.

Extract knowledge from the existing code and make enhancements faster and error-free: Complex codebases/source code often involve multiple levels of abstraction. They may consist of high-level architectural components, intermediate modules, and low-level implementation details. With Developer Companion, programmers can extract the relevant details quickly and efficiently.

Bridge the Gap between Programming Languages through Code Conversion: Whether you are migrating a codebase from an archaic programming language such as COBOL to a modern one like Java or C++ or translating functions between C++, Java, and Python 3, the process is difficult and resource- intensive, and moreover requires expertise in the source and target languages. With Developer Companion, developers can bridge the divide through code conversion.

Test Code with Automated Test Case Generation: Automatic test case generation is the process of identifying and creating test cases for an application without the need for any manual intervention. It involves utilizing various techniques and tools to automatically generate test cases for software applications or systems. The primary objective is to automate the creation of test cases, leading to enhanced test coverage, improved efficiency, and reduced effort required for manual testing.

Discover Hidden Code Vulnerabilities: Instead of racking your brains regarding what could be wrong, or where the gap exists, developers can unearth the hidden vulnerabilities with ease using Developer Companion.

Unravel the Data Maze with Unique Database Query Console: Do not get lost in the maze of data, as a unique query console gets you inputs way faster.

Unleash the Power of Developer Companion Today!

In essence, an AI assistant for developers was long due for ridding the irksome, repetitive, and mundane pieces of work that they are saddled with daily. An AI-enabled assistant not only grants them a new ease of life but raises the bar as well when it comes to programming. It improves the time to market, efficiency, while minimizing problems such as legacy code and tackling risks such as shortage of skilled labor, attrition, testing challenges, etc., with AI. Developer Companion is all set to revolutionize AI in financial software development by extending the possibilities and taking it to a new level.

Now, if that was not enough to ask for a demo right away, we will be more than glad to satisfy your curiosity and any further questions that you might have. You can write to us for more information on how we could give coding a new lease or reach out to us at mail@magicfinserv.com for fintech solutions.

The post From Wishes to Reality: Meet Developer Companion, a Modern-day Genie for Software Developers! appeared first on Magic FinServ.

We trust you were able to read our first blog (Are you ready for Sec T+1 Settlement reforms?) on the impending shift to T+1 settlement in the US, where we highlighted the reasons why broker-dealers and clearing brokers must automate and standardize communication related to trade. Here in this blog, we evaluate why regulatory filings must be automated as well.

Once a trade has been executed, the broker-dealer is expected to update the regulatory body as the case might be, with appropriate details related to the trade transaction. These reports or regulatory filings are a comprehensive summary of the trade that is submitted to the regulatory bodies on a timely basis. Regulatory filings involve trade status and timestamp details for all the actions like Order Initiation, Execution, confirmation, affirmation, matching, settlement, partially settle, rebook etc. In case there is a settlement failure or a rebooking, the broker dealer is expected to update the regulatory authority on that as well. The sole objective of this regulatory filing is to ensure transparency and to enable the regulator to assess and supervise the business being transacted by individual Counterparties within the marketplace. It is critical for protecting the interests of the investor and keeping the integrity and the security of the capital markets intact.

Typical Challenges in Regulatory Filings

Provided below are some of the typical challenges that broker-dealers face in ensuring a timely delivery of regulatory filings:

Operational Risk: Broker/dealers carry out trade lifecycle operations across multiple platforms and FinTech systems, often relying on complex manual processes to bridge the gap between these disparate platforms. However, they frequently face challenges due to outdated legacy processes and system performance issues and most importantly Data transfer issues due to Data compatibility, which hinder their ability to file regulatory reports in a timely manner.

Asset challenges: Investment managers face challenges related to diverse Asset types, including equity, fixed income securities, and ETD derivatives. Regulatory requirements for each instrument depend on the market in which it is traded, such as Organized Trading Facility (OTF) or Regulated Market (RM), as well as the specific guidelines set by regulatory bodies like the SEC, FINRA, and CFTC. As a result, the regulatory filing process becomes complex when broker-dealers do not automate or use a rule-based approach for FO-MO-BO data reconciliation and transformation.

Data quality and governance challenges: Excessive reliance on manual labor only for the classifying, aggregating, consolidating, and validating data during the multiple stages of the trade – initiation, confirmation, affirmation, rebooking, settlement constitutes a problem when it comes to meeting regulatory timelines or ensuring that all data is up-to-date and accurate.

STP challenges: All broker-dealers are typically required to report trade details to the SEC and other regulatory bodies in a timely manner. The reporting frequency and specific deadlines for filing these reports can vary based on the size and activities of the broker-dealer. In the absence of automation and STP, timely regulatory filings are difficult.

Finding the right vendor: Finding the right vendors for automating processes without impacting the existing business activities might not be as easy as expected. And that’s why broker-dealers need a partner with a thorough understanding of the capital markets and are capable of designing solutions that are tailored to fit.

Automating Regulatory Filing with Magic DeepSight^TM : The 7-point advantage

Capitalizing on its immense experience in Capital and Financial Markets, and bespoke AI/ML platform that customizes solutions as per need, Magic FinServ ensures that regulatory filings are seamless and smoother than before – beginning with faster, smoother, aggregation and consolidation of data (using automation) and benefiting from a rules-based approach that adapts to evolving regulatory environment (including shift to T+1, and others) easily.

1. Ensures data quality and governance: An AI-enabled platform like DeepSight can make a huge difference in the quality of data. Instead of inaccurate, inconsistent, and incomplete data, from manual data entry, broker-dealers are assured of clean, complete, consistent, and accurate data, for submission to the SEC and other regulatory bodies. DeepSight also validates and cross-references data, further minimizing the likelihood of errors and discrepancies. Most importantly is also creates an audit trail thereby enabling replaying of the transaction if needed.
2. Simplifying reconciliation/transformation of trade data: An AI/ML and rules-based solution can ensure a faster, smoother, and more accurate reconciliation and transformation of trade data emanating between the front, middle, and back office when compared to the manual approach. This is most critical as the Data Models, Formats and Templates differ for each application and area, a key reason why the manual approach is simply not feasible for the impending T+1 settlement cycle.
3. Easy integration: DeepSight can be easily integrated with existing systems. It supports data in all formats. The platform is format-agnostic and has the capability to support all sorts of data formats such as Excel files and spreadsheets, CSV files, emails and attached documents, API integration from multiple systems, and unstructured data.
4. Shared database for data multi-purposing: Whatever the file format, DeepSight parses through data seamlessly from disparate sources such as back office, middle office, front office and processes, transforms, enriches it, and creates a single source of truth in a shared location or database.
5. Enables timeliness and compliance: With DeepSight, broker-dealers can ensure that regulatory filings are done as per the timelines set by the regulatory authority. By automating the workflows, extracting the data from multiple sources (the back, middle, and front offices) and compiling it together becomes easier.
6. Single solution: Straight through processing (STP) results in seamless and smoother regulatory filing. This integration enables seamless data flow and enhances overall workflow optimization. It reduces manual data transfer and improves the accuracy and efficiency of the trade reporting process.
7. Adopt new regulatory changes easily with a rules-based approach: In an evolving regulatory environment, a rules-based solution makes it easier to reconcile data and file reports with the regulatory body becomes easier.

As the market gears up for T+1, this was how we could enable your transition to it. For more you can write to us mail@magicfinserv.com.

The post Keeping up with Sec T+1 Settlement Cycle! appeared first on Magic FinServ.

In trading, time is of the essence, as every moment wasted in settling or reconciling a trade incurs higher costs and greater risks. Today, as the US proposes a shift to the T+1 settlement cycle, the primary objective is reducing the time it takes to settle a trade. And in the process, decrease the risks. That seems justified as the markets have experienced severe shockwaves in the last two years, due to market volatility, pandemic, fall of meme stocks, etc.

The T+1 settlement cycle essentially means that all settlements relative to trade must be carried out the next day and is expected to yield benefits like reduced costs, increased market efficiency, and reduced settlement risks.

So, while earlier, the settlement cycle (t+2) looked like this:

Now we have a settlement cycle (T+1) that looks like the one below:

Implications of Transition T+1: Unveiling the Key Challenges in Broker-Broker (Executive and Clearing Brokers) Communication

Though the transition to T+1 provides multiple benefits, the shift from T+2 to T+1 is not easy. We elucidate this using the example of brokers/dealers, who are a vital part of the trading chain. T+1 settlement of institutional trades lowers margins for broker/dealers. Brokers are required to pledge cash and securities to a clearing house, benefit enormously from the lower margin requirements (difference between the current value of the security offered the collateral and the value of loan granted). But it is not a win-win situation for them yet.

One of the biggest challenges in transitioning to the T+ 1 settlement cycle is the lack of automation in any communication emanating between broker-broker or the Executing Broker and the Clearing Broker when it comes to Trade File Processing. This broker-broker communication is centrally a part of the back-and-forth information processed by the middle office (MO) and settlement information/status received from the Clearing House or Back Office (BO)system.

Another significant challenge is the reconciliation of trade files and other reports. Without automation, manually updating these details, typically in Excel or spreadsheet format, can be quite cumbersome. The executing broker shares trade details with the clearing broker, usually in the form of spreadsheets, which are then processed and imported by the analyst team into the clearing system.

When investment manager, broker-dealer, clearing dealer rely more on manual processes than automated, time lags and delays are bound to happen as everything happens sequentially instead of bi- directionally. With automated processes, the majority of trades can be processed on the same day without requiring manual intervention.

Markets and prices are in a state of flux when it comes to trading. Hence, broker dealer, clearing broker must always be in a state of alert. Even remote chances of error or trade fails must be rooted out, unfortunately with manual mistakes that can have major consequences are higher.

Additionally, there are other unresolved issues such as:

• Manual entry of data from documents received via email or fax from the investment manager when a trade is blocked. There is also a substantial amount of manual effort involved in the reconciliation and communication between the executing broker, the clearing broker, and other parties, for final clearing and settlement that must be automated for ensuring SDA(Same Day Affirmation).
• There is still a substantial amount of paper involved
• Sliced, dicing, and digesting the unstructured data in emails and faxes in time for T+1
• Most firms are burdened by a crumbling legacy architecture that cannot scale up fast enough. If that were not concern enough, building a new one that could ensure adherence to t+1 from scratch would be time-taking and excessively expensive.
• For (T+1), broker/dealers and clearing broker must speed up affirmations, confirmations, and allocations processes. But how do they do that when they have not yet automated their processes and there is no STP.

So better late than never! We are here to help firms navigate the transition to T+1, by redefining and re- strategizing the options and integrating our magical solution DeepSight^TM that leverages the power of AI and ML to ensure a win-win. But first here’s a brief on T+1:

Automation is pivotal for T+1: How AI/ML and RPA helps reach the magical Same Day Affirmation (SDA)

The biggest challenge for T+1 transition is the lack of automation in institutional “allocations and affirmations.” This is one area that requires massive transformation to achieve the proposed settlement cycle timeframe. An automated solution can play a crucial role in facilitating same- day affirmation (SDA) processes for broker-dealers and clearinghouses.

With automation, broker-dealers and clearing houses can also:

• Reduce the risk: As the volume of unsettled trades over a single trading day and the time between trade and settlement are reduced, counterparty, system-related, and operational risk is reduced.
• Trade capture and validation: Perform real-time validations, ensuring that trades meet pre- defined criteria and are eligible for SDA.
• Enables seamless transition: By automating various aspects of the settlement workflow, broker- dealers and custodians can minimize manual intervention, reduce operational risks, and enhance overall operational efficiency.
• Eliminates the need for manual intervention and errors: Eliminating the need for manual intervention and reducing the risk of trade discrepancies.
• Exception handling made easier: Automatically identify and flagging trades that require manual intervention. focuses on the resolution of exceptional cases promptly, paving the way for smoother SDA processes.
• Seamless data validation and reconciliation: Validate trade data and reconcile it with external sources, such as market data providers or reference databases.
• Prompter resolution of errors: Potential discrepancies or errors can be identified and resolved promptly, reducing risks associated with inaccurate or incomplete data.
• Enables straight-through processing: Eliminates the need for manual rekeying or intervention at different stages.

Revolutionizing T+1 Settlement: Empowering Broker-Dealers and Clearing Houses with DeepSight^TM

Now is the time for broker dealers and clearing houses that have not yet implemented automation to take to aggressively pursue automation if they are to abide with the proposed new rules. For broker dealers and clearing houses, the focus would be on ensuring SDA.

Here’s how Magic FinServ’s AI Optimization framework – DeepSight^TM that has at its core AI/ML and Data builds tailored solutions that reduce the need for human intervention stoking up processes and ensuring optimal levels of efficiency for processes related to confirmation, allocation and affirmation and trade matching.

Magic FinServ’s innovative digital solution leverages the power of data and AI/ML technology to standardize business processes related to trade file processing by automating the broker-broker communication. Our highly intelligent and scalable solution shifts through data sources in different formats: Excel/spreadsheet/CSV files/Email body/Email attachment/API integration from multiple systems/ and other unstructured formats with ease and creates the “Reconcile Report” for other market player. It also supports the setup of the Golden Copy Data Management for multiple other sub activities related to the trade lifecycle. Other aspects of our solution include – Exporting the reconciled trade file, configuring any Business Rule/Mathematical rule which is required for generation of trade file, and generating reports based on customer need, i.e., in JSON, API, excel or any standard template.

While DeepSight^TM can help automate processes, the move to T+1 settlement will still require fundamental changes throughout the trade processing lifecycle.

• Consolidation of data feeds between new and legacy systems to centralize data management.
• It is necessary to adopt technology (e.g., DTCC’s ITP CTM) and/or messaging protocols (e.g., FIX) to automate the communication of allocations and CTM’s Match to Instruct to facilitate more timely trade affirmations.
• As firms move to T+1 settlement, they must adopt technology (e.g., DTCC’s ITP CTM/M2i) and/or messaging protocols (e.g., FIX) to automate the communication of allocations.

The Incredible Benefits of DeepSight^TM

When broker-dealers, whether they are small boutique firms or subsidiaries of investment banks, consider their options, they can reap several benefits.

Eliminate the friction: Firms can eliminate the friction that exists at multiple touchpoints when data is entered manually. They can leverage the AI/ML capabilities to extract relevant data from documents, pdfs, mails/faxes, etc.

Fasten the post-trade agreement and affirmation by almost 50%: A solution like DeepSight^TM can scale quickly and is ideal for periods when trade volumes are high or market volatility is high or both, as it trained to extract the appropriate data from the swathes of information available infinitely faster than humans.

Benefit from data-driven approach: Trade is ultimately about data. As the data experts, we can quickly identify which are the processes that would require automation. So, whether investment managers/portfolio managers who need help analyzing their performance or peers and counterparties/broker-dealers, custodians, our solutions can ensure that the transition to T+1 is smoother.

Reduce operational risk: With standardization and STP, operational risks are reduced considerably. When organizations opt for a solution like Magic Deep Sight, that leverages the power of AI and ML, and that can be easily integrated with existing systems, allocation, conformation, and central matching is given a boost. With SDA, firms can easily ensure the next day’s settlement.

Reference data management: Reference data management is a critical part of data management. To ensure transparency and efficiency, firms must update their reference data (e.g., the asset type, counterparty information), security pricing data, and standardized settlement instructions (SSIs). With DeepSight^TM , the processes are streamlined and there is no chaos.

Easy and seamless integration with legacy architecture and workflows: No need to replace legacy: DeepSight^TM biggest advantage is the heuristic approach wherein firms do not have to replace the existing workflows, as our solution can be integrated with traditional workflows and legacy architecture.

Exception Management: This metric assesses the ability to identify and resolve exceptions or discrepancies promptly during the settlement process. Efficient exception management helps streamline operations, reduces manual intervention, and enhances overall settlement efficiency.

Conclusion: A Shorter Settlement Cycle Benefits All!

Shorter settlement cycles benefit all. Some of the benefits are:

Shorter settlement cycles benefit all. Some of the benefits are:

• Improved straight-through-processing (STP)
• Quicker settlement
• Less margin required
• Reduction of operational and systemic risk
• Decrease in costs and resources from reduced number of unsettled positions

Irrespective whether it is an investment manager, broker dealer, clearing dealer or clearing house, custodian, or settlement agent, T+1 is good for all. Ideally, T+0 settlement cycle offers the best deal; however, it would require a massive overhaul of the existing architecture, hence the SEC and other regulatory bodies have opted for transition to T+1 for the time being. Though some amount of re- strategizing is required to get in sync.

By embracing automation and STP, broker-dealers and custodians can enhance their operational resilience, reduce settlement risks, and improve client experience. They can focus on value-added activities and provide faster and more efficient services to market participants. If there is more that you would like to know as a broker dealer or clearing house, you can drop a mail at mail@magicfinserv.com

The post Are you ready for Sec T+1 Settlement reforms? appeared first on Magic FinServ.

An airport lounge is an ideal place to relax and recharge. With free food and drinks, Wi-Fi enabled workstations, and clean facilities, travelers can take advantage of these amenities to unwind or catch up on work. Additionally, the lounge provides a networking opportunity with colleagues and friends. For those who desire a highly personalized or exclusive experience, the Polaris lounge (United Airlines) or Lufthansa’s super exclusive First-Class Terminal offer even more luxurious amenities such as a full bar, cigar lounge, plush sofas, buffet, and salon.

Now, a big pause! Many of you may be wondering if this is a build-up for Premier Lounges or the credit card companies that sell them. The answer is – no, it is not! This is about the parallel between the plight of passengers whose flight gets delayed or cancelled and the fintech’s journey in recent times. While travelers can recharge themselves at airport lounges, financial lounges like Magic FinServ can help fintechs recharge by providing super exclusive, hassle-free, and streamlined services. Magic FinServ’s advisory services and technology solutions can boost the pace of modernization/transformation by a significant 10X times.

The Many Stressors of Fintechs

Similar to how travelers face many stressors such as connecting flights, delayed and cancelled flights, fintech companies can also experience frayed nerves, especially when struggling with legacy workflows, redundant tools and technologies, unending migration problems, data swamps, and potential industry- wide disruptions caused by unexpected forces such as generative AI. Additionally, they must account for past mistakes such as overspending, which has resulted in big banks failing one after the other. The latest to bite the dust is First Republic.

If you are a fintech or financial services provider struggling to keep up with the massive disruptions occurring in the world today and are looking for a way to de-stress and energize, a Financial Lounge is what you need. A financial lounge is perfect for de-stressing your cluttered, siloed workflows and legacy engines from decades ago. Let us explore how.

Welcome to Magic FinServ! The Financial Lounge for FinTechs and Financial Services

1. Beat the Stress
   • Managing financial data is one of the biggest challenges faced by fintechs and financial services. It is complicated as it involves a lot of sensitive information. Another significant challenge is compliance. Fintechs must stay up to date with the latest standards and work with regulators to ensure that all obligations are met in a timely manner. However, organizations no longer need to worry about these challenges as Magic FinServ can get them up to date.
   • We can help you prioritize data security and privacy, maintain accurate and up-to-date records, and ensure that data is easily accessible and actionable using the cloud and our AI and ML- enabled solution.
   • We can help you streamline your workflows quickly and assist you in embracing disruption.
   • DeepSight^TM analyzes vast amounts of data in real-time for use cases such as risk management, fraud detection, AML, KYC, portfolio management, regulatory compliance (Shareholding and voting rights, ESG, T+1, investment and fund monitoring and reporting).
   • You can also count on our team of AI and Machine Learning specialists and FinTech engineers to identify gaps and provide sound advice on how you can leverage technology such as AI to speed up your processes at minimum costs.
2. Relax and Recharge while our bespoke AI platform crunches numbers faster than Speedy Gonzales
   • Rest and relaxation are important for both physical and mental well-being. Like airport lounges offer a place to unwind and recharge during a stressful time, Magic FinServ’s financial services acts as financial lounge for fintechs providing them with the needed “rest” and allowing them to focus on their core business. Our tools and services can help fintechs manage their finances with ease and confidence. Here is how
   • For humans, sleep is more than a biological requirement. It helps them recharge their batteries for another day of work. However, because of the existence of multiple time zones when markets are alive and active in one part of the world, our analysts weary and tired after a full day of work could be fast asleep, missing several critical incidents in another part of the world. So, when they come back to work the next day, they have their hands full. Most of the work that they would be required to do to keep the processes up to date would be of a manual sort, such as data entry, uploading and downloading files. Making the analyst feel tired like Jack – because all work and no play makes Jack a dull boy.
   • Now you can slay stress and be up-to-date faster than it takes to say I do! Unlike humans, our AI- powered platform does not need any sleep at all. So, while you are fast asleep, our powerful AI-powered solutions are deep at work automating facets of operations that were time-taking and tedious, ensuring that when you come fresh to work the next day, you only have to fine tune or take a summary, as the rest has been taken care of by AI.
3. Experience a Seamless Transition
   Passengers go through an agonizing period when they wait for a connecting flight, and fintech companies experience a similar sense of anxiety while awaiting the results of cloud migration and modernization efforts. However, with financial lounges such as Magic FinServ, the desired transformation can now be achieved more quickly. Our three-step approach for cloud migration includes:
   • Conducting a cost-benefit analysis with the help of our dedicated cloud team. This analysis takes into account the costs of migration and ongoing maintenance, as well as the savings that organizations can expect to see.
   • Optimizing the cloud environment with the use of automation and orchestration tools.
   • Utilizing cloud-native services such as containerization and managed databases to reduce costs and improve efficiency.
4. Utilize Time Profitably
   • In today’s fast-paced world, time is a valuable commodity. Similar to how airport lounges with workspaces allow travelers to catch up on work while waiting for their flights, our financial solutions enable fintech companies to leverage the power of AI and ML to stay prepared for any unforeseen consequences. By automating time-consuming and repetitive tasks, our solutions allow fintechs to focus on high-value work and take advantage of opportunities as they arise. This way, they can make the most of their time and operate with maximum efficiency, ultimately leading to increased profitability.
5. Remain Exclusive
   • People go to these lounges not only when their flights are delayed but also for novelty- it offers a unique experience. So it is for the financial services, we are their niche partner offering them the unique space to innovate and experiment. Because it has become apparent now that despite indications that recession may have set in finally, organizations, especially the bigger ones, are earnest about prolonging investment in moonshot projects. Some of the most common moonshot projects relate to robo- advisory, de-fi, embedded banking.
   • If you are keen on continuing moonshot projects, ensure STF and automation of back and middle-end processes first, because unless these two ends are unified and compatible, it would be unreliable to expect long-term benefits from other areas.

Magic FinServ: an Oasis for FinTech’s

In today’s fast-paced world, FinTech companies face numerous challenges that can impact their ability to succeed. From managing legacy workflows to keeping up with constantly evolving technologies and regulations, it can be challenging to stay ahead of the curve. That is where Magic FinServ comes in – as an oasis for FinTechs.

As experts in data and AI for FinTechs, Magic FinServ provides customized solutions that help companies manage the stress that comes with operating in this turbulent environment. We understand the unique challenges that FinTechs face and work with our clients to develop solutions that are tailored to their specific needs.

Our services act as a refuge for FinTechs, providing them with a much-needed break from the chaos that often surrounds their operations. Just as an oasis provides water and shade to travelers, Magic FinServ provides FinTechs with the support and resources they need to thrive in an ever-changing landscape.

Our clients can count on us to help them manage complex data sets, navigate legacy workflows, and keep up with the latest technologies and regulations. With Magic FinServ by their side, FinTechs can take on new challenges with confidence, knowing that they have a partner who understands their unique needs and can help them achieve their goals.

In conclusion, Magic FinServ serves as an airport lounge or oasis for FinTechs, providing the support and resources they need to navigate the challenges of the modern business world. With our expertise in data and AI, we help FinTechs manage the stress that comes with operating in a constantly evolving

landscape and enable them to thrive in the face of adversity. Contact us today at mail@magicfinserv.com to know more.

The post Navigating Turbulent Times with Magic FinServ’s AI-Driven Financial Lounge appeared first on Magic FinServ.