As an investment compliance team or an Asset Manager, one of the chief responsibilities is to monitor and administer the position holding of high-value institutional investors in a manner that is beneficial to the investor while meeting regulatory obligations. When it comes to investment monitoring, asset managers must ensure high levels of transparency. This is necessary as unethical practices such as short selling, account takeovers, disproportionate flow through, etc., not only harm the stakeholders’ interests but also result in massive fines and build a bad reputation. For example, an asset management company had been fined £7.2 million in 2013 for not heeding investment protection compliance regulations.

For private market investment, the buy-side asset manager (which acts as investor/LP) also needs to maintain transparency and identify or control the risk associated with their investment cash flow. To do this, the investment monitoring team gathers and monitors all the investment records and distribution received from the General Partner (GP) in a timely manner and relates this with the fund market value.

(A) What is Investment Monitoring in terms of Beneficial Disclosure and Position Limit Monitoring?

For asset managers and institutional investors who hold multiple securities (listed and traded) in a regulated market governed by different jurisdictions, shareholding disclosures continue to be a mammoth task. The challenge is further compounded by the fact that firms must also ensure compliance/make specific disclosure for:

  • Investing in a sensitive industry
  • Involvement in a takeover bid.
  • Accumulating substantial shareholding in a security
  • Engaging in short selling
  1. Monitoring Shareholder Information and Calculated % of Disclosure/Threshold
    • Shareholder information pertaining to the company’s share capital data and voting rights
    • Used for the calculation of the holding % ownership (threshold). When the value exceeds the threshold (depending on the jurisdiction) monitoring and reporting must be carried out accordingly.

Beneficial Ownership Reporting

“A beneficial owner is any individual who, directly or indirectly, owns or controls at least 25 percent of the ownership interest of the reporting company.”

Beneficial ownership reporting (against violation as per law defined by the jurisdiction) to the NCA (National Competent Authority). For example, Schedule 13/Form 13 filling to SEC in case the jurisdiction is in the US.

  1. Position Limit Monitoring

Position Limits represent the maximum number of holdings of the future/option contract corresponding to a given security.

The position limit or threshold is defined by regulatory bodies like CFTC, ESMA, etc., and the exchanges (CME, ICE, etc.) differently.

The investment manager must monitor the thresholds mentioned herewith and inform the respective bodies in case there is a violation.

  1. Exchange Position Limit: This limit is defined by exchanges like CME, ICE, etc.
  2. Regulatory Body: The regulatory body, for example, ESMA defines the position Limit in MiFID 2 Article 58/58

What does the typical investment monitoring workflow look like and why are asset managers not in control?

This is what a typical investment monitoring workflow looks like for Shareholder & Position Limit Monitoring:

When it comes to shareholding disclosures, here are some of the challenges that asset managers face:

  1. Data Consolidation from Multiple Sources system (IMS, OMS, 3rd Party Data Provider, Exchange)
  2. New Customer Onboarding Challenges
  3. Data Transformation, Tagging, Data Validation or Completeness.
  4. Netting/Aggregation of Position
  5. Monitoring the % Disclosure value on Timely manner due to dynamic effect of Corporate Action event.

Role of RegTechs!

When it comes to investment monitoring, it would be difficult to envision how to get things done without Regtech’s involvement. Regtech is the management of regulatory monitoring, reporting, and compliance within the financial industry through technology. Regtech systems can not only monitor the current state of compliance against upcoming regulations but ensure real-time compliance as well.

How Regtech Support the Business?

Challenges for RegTech?

Magic FinServ’s Operational Model paves the Way for Change for both Reg-Tech Partner and Asset Management Firms:

Before embarking on a new journey with automation and analytics, firms must ensure that the mapping of data is accurate and complete. And herein lies the biggest challenge. You can onboard a platform or system, but if the system does not recognize the data or information, automation is pointless and real-time updates are skewed or not verifiable.

Biggest Obstacle to Automation is Data: Resolving the challenge the Magic Way with DeepSightTM

Unsurprisingly, despite the advancements in technology, what remains the biggest challenge for Asset Managers, Portfolio Managers, and Investment Managers is data, or rather the state of data. No prizes for guessing that correctly, for data is always at the center of controversy. If it is in good shape, organizations reap rich dividends by being on top of the game, but poor data is no good. When it comes to investment monitoring and the data conundrum, some of the chief concerns that asset managers and hedge funds face are:

  1. Data onboarding and transformation: client data is not in the required format and is scattered in silos: When you have heavy unstructured data, data ingestion takes longer than required.
  2. Data incompleteness or missing data points – Another concern is data lineage or finding the source of data which is critical for data transformation.
  3. Data validation – Checking the quality of source data before processing data.
  4. Collaboration among diverse teams and appropriate knowledge sharing is another key challenge.

At Magic FinServ, we believe that the Investment monitoring mechanism can be simplified by understanding the client’s compliance requirements first. We need to thoroughly analyze the client’s data files and understand what is it that they really need support with before – is it the lack of data, the incompleteness of data, the lack of understanding of the regulatory mechanism, or quite simply process simplification, before integrating the system or aligning the product to requirements.

This would also imply supporting the client in data transformation and reconciliation. This means cleaning the data, loading it, and validating it.

For example, let us consider a scenario wherein the senior leadership of a company “X” who are also shareholders of the company decides to short-sell to a bank or Venture Capital fund, which has also invested in the company and thereby are shareholders of the company. Now depending on the Regulatory policies as per corresponding jurisdiction, this is a clear violation of Threshold and must be reported to the regulatory bodies accordingly.

Now for alerts or triggers to be generated for action, there must be a clear-cut definition for raising an alert. However, this is not possible in a vacuum.

Processes must be streamlined, a rule-based system must choose accurately from the fields and columns of the data provided, and quickly raise alerts in case there is a discrepancy (or a cause for an alarm) and update it on the compliance system.

DeepSightTM AI/ML automation solution has the capability to extract relevant information from multiple sources and reconcile it based on any applicable business rules. Provided below are some use cases where automation can transform processes completely.

Use Case 1: Maintaining & Monitoring dynamic values of shareholder data and voting rights due to Corporate Action event in Timely manner

Firms must keep up to date with real-time values of company shareholder data and voting rights because any corporate action change can cause a material change to a company and affect its stakeholders. Information about corporate action is published in the form of news alerts or web links which are unstructured data sources. With DeepSightTM firms can automate shareholder-managed services and support the compliance monitoring team.

Speedier Migration and Quicker Transformation of Data with Magic FinServ

Systems do not understand data and its sources. Hence, implementation remains a challenge. Even the most perfect tools and platforms lack the comprehensive (and comprehending) power of humans. The biggest misconception that organizations fall prey to is getting an expensive tool and hoping it will automatically run one fine day. It simply does not work that way. The system does not understand the rules of the game (investment monitoring). It must be taught. It must be provided directions.

Helping the system understand.

And how does the system understand? It is possible only when both files are understood, and a one-on-one mapping is done. Thereafter, the rules are applied as per the defined jurisdiction or client requirement. And here’s how we can help.

So, for example, there is a new client that desires to use a tool/platform for investment monitoring of shareholding business. The cornerstone for setting up the tool is understanding the set of procedures required for running the data on the system daily. The workflow must be onboarded to the automation tool – the system.

However, before that, some files such as the security and position files are shared as a sample. Thereafter the mapping is done – map all the information in it (files shared) with the automation tool’s data scheme. When the schema is completed mapped, then only can the desired impact of automation for investment monitoring be perceived.

Use Case 2: Client Onboarding made easy with DeepSightTM

Generally, client onboarding on a system is a laborious affair if it is done manually. It is also highly expensive and error prone. With our Agile Project Management approach, we ensure speed and transparency even under the most excruciating of circumstances. Migration and transformation of data that was unusually long and laborious is streamlined. The results are evident more quickly as we ensure support to analysts and SMEs during all the critical milestones.

DeepSightTM simplifies new customer onboarding. It aggregates position values (based on regulatory rules) easily. It can facilitate the setup of an exception and alert mechanism when threshold limits are breached. Overall, our solution saves unnecessary costs and efforts, and by eliminating challenges related to data profiling, data completeness, and data lineage, ensures compliance with established standards.

By integrating and configuring the customer source system using DeepSightTM automation tool and including steps such as data profiling, data completeness, transformation, and mapping data, the process is made smoother without any manual intervention.

The biggest benefit that you get with Magic FinServ is a less irksome and less time-consuming client onboarding (on the compliance system for investment monitoring). With analysts spending less time monitoring the tools, your teams can engage in more productive tasks and leave us to take care of how real-time data will be integrated in the system.

(B) Investment Monitoring: Private Equity (PE) Investment by Buy-Side Asset Manager (Acts a Limited Partner (LP)

Now let us take the specific case of Investment monitoring by the Endowment Investment Institute, which is a Limited Partner in private equity, venture capital, and private market investment funds.

DeepSightTM helps customers manage all requests and documents in a digital library. The strategy for managing documents is based on the company’s investment fund strategy, making tracking, monitoring, and auditing processes easier.

It also helps customers manage and reconcile private equity fund cash flow information, along with other calculated values such as total commitment, funded commitment, recallable capital, and unfunded commitment for each private equity fund.

DeepSight’s AI/ML-enabled automation solution for Private Equity Fund can create Delta or Comparison reports based on internal data reconciliation and generate reports related to the Private Investment’s cash flow in a timely manner for each fund investment. It also creates alerts in case of any violations. It can also export information through an API or any other mechanism and generate reports using standard metrics.

Use case 3: Extract and reconcile data (from multiple sources) and carry out reporting for all the private equity investment cash flows and market value/fund performance:

With DeepSightTM ‘s automated solution, compliance, and investment performance teams can easily extract and reconcile all the cash flows and investment performance information from the structured and unstructured sources. Investment performance teams can also identify the delta and create an alert if the fund administrator fails to execute the order on time.

DeepSightTM can make things easier for you. For more on how we can be of help, write to us

In this world, headwinds are far more prevalent than winds from the astern (that is, if you never violate the Pythagorean maxim). – Author: Herman Melville

In our earlier blogs on investment monitoring and transaction regulatory monitoring, we provided a detailed description of the challenges that institutional investors, hedge funds, and asset managers face with respect to filing and monitoring of reports. And along with the challenges, the panacea – an automated rules-based solution that speeds up the data extraction process by a zillion times, enriches and transforms data with tags and maps, while integrating easily with the required workflow and facilitating last-mile process integration. So that regulatory filings no longer remain the nagging pain for business heads and analysts that arises every time it is filing time. And that is every quarter!

Here in this blog, we will be discussing another monumental legacy of entrepreneurship across the world -private equity funds. Along with it, the obstacles, or the headwinds that financial advisors to hedge funds, and hedge funds and asset managers themselves face while filing their reports such as form PF, and alternative asset management funds.

Considering that volatility of the markets, the inglorious end of the Credit Suisse chapter (plagued by constant reprimands from the regulators in the last couple of years for financial irregularities) and Silicon Valley Bank closure that is creating a ripple effect that reverberates throughout the financial and capital markets, and increasing pressure to conform to the regulatory requirements, this blog will be on how Magic FinServ and DeepSightTM purports to be the “wind beneath the wings.”

What are the key filings?

We begin with a definition of the key filings and the historical relevance of these funds. In the global business eco-system, private equity funds hold an elevated place as these have not only resurrected or reinvigorated companies but have provided them with the much-needed capital leverage during their start-up or fledgling phase. You need to look no further than what is considered the most valuable company in the world today – Apple – which too received funds from private equity during the initial phases.

Because the funds in question are huge, hedge funds and asset managers, and financial advisors that manage them are required to ensure that risks are mitigated, and there is transparency. Some of the key regulatory filings that are applicable to funds include:

Form PF: A registered investment adviser with at least US$150 million of ‘private fund’ is required to file Form PF with the SEC, which requires disclosure pertaining to

  • gross and net performance,
  • gross and net asset value,
  • the aggregate value of derivatives,
  • a breakdown of the fund’s investors by category (e.g., individuals, pension funds, governmental entities, sovereign wealth funds),
  • a breakdown of the fund’s equity held by the five largest investors.
  • summary of fund assets and liabilities
  • including Sections 2a (Aggregate Positions) for $1.5 billion in hedge fund assets under management, 2b (Risk Measure),

Form CPO-PQ: As per CFTC regulations most derivatives are included as ‘commodity interests’ that cause a private equity fund holding such instruments to be deemed a ‘commodity pool’ and its operator to be subject to CFTC jurisdiction as a CPO or its adviser (typically the investment adviser) to be subject to CFTC jurisdiction as a CTA, and, unless an exemption is available, to become a member of the National Futures Association (NFA), the self-regulatory organization for the commodities and derivatives market. Source: Regulation of private equity funds in USA.

Alternative Investment Fund Manager Directive (EU AIFMD): Any manager that operates a fund in the EU is subject to AIFMD regulation. The Alternative Investment Fund Managers Directive (AIFMD) is a European Union (EU) regulation that applies to alternative investments, many of which were left largely unchecked prior to the 2008-09 global financial crisis. The directive sets standards for marketing around raising private capital, remuneration policies, risk monitoring and reporting, as well as overall accountability.

Where does the challenge lie?

Finding the needle in the haystack: As apparent, the regulatory filing is a massive exercise involving humongous amounts of data from which relevant field items or data points must be picked. The entire process can be likened to finding a needle from a haystack. Manually filing and reporting is an extremely time-consuming exercise. It disrupts normal business as additional effort is required to process it in time. And to make matters worse, the manual approach is also massively error-prone

Lack of process standardization results in duplication of effort: When filing and reporting is being conducted manually, firms due to time constraints are not focusing on information generation, rather they try to meet the deadlines. Whether it is Form PF or Form CPO-PQR filings, the processes are different, and with no efforts made to standardize the information, firms end up going through the same set of information again and again. The absence of a centralized repository complicates results in rework. Creation of a compliance data repository for all the relevant and necessary data, as well as the creation of business values for calculating measures and risk metrics.

Different systems complicate processes: Another headwind is the task of compiling, netting, aggregating, and validating data from the different business ecosystems as each functions differently. Each ecosystem could rely on processes, approaches and workflows that are different from the others making it tough to validate and reconcile data.

Testing and creating a sample for automation. Ensuring last-mile process optimization and coordinating with the regulator

Lack of collaboration and process standardization are the headwinds: Siloziation culture, and lack of process standardization come in the way of timely and accurate filings. Working out a sync between internal and external parties – exchanges, data vendors, compliance teams, and third-party vendors so that important action items are not missed and reported in a timely manner constitutes another operational challenge.

Navigating the challenge with an automated and rules-based data-driven tool

In order to meet the Form PF and Form CPO-PQR filing requirements in a manner that is accurate, transparent, and up-to-date while ensuring that it is in consonance with the regulatory and compliance guidelines of SEC, CFTC, and European Union’s AIFMD among others, hedge funds and asset managers must adopt a clear-sighted and streamlined approach that funnels the power of cutting-edge technologies such as artificial intelligence and machine learning while concentrating on data-centricity so that there is a centralized data repository, and streamlined processes that can be can be leveraged for optimal utilization of resources. In case there are additional filings for regulators in other jurisdictions as per need, streamlined processes can easily meet the need. It also requires a standardized data gathering and compilation process, and consistent data usage across business units.

An automated and rules-based approach tool is ideal for cutting the slack and for ensuring timeliness and accuracy, and we combine that with our knowledge in the financial services domain and our team of experts who are well-versed in the nitty-gritty of regulatory compliance practices to make fund regulatory filings a pain no more.

Here’s how we can make monitoring and reporting streamlined and hassle-free.

The Roadmap

Assessing Needs and Gaps: Begin by assessing and analyzing the requirements.

  1. Find out what it is that the firm requires.
  2. What are the reports that are to be filed (Form PF, and Form CPO-PQ, and in addition additional investment)

Identify the sources of data, extract relevant data & transform data using DeepSightTM

Identify where it is that you get the data, the websites or external sources, and the internal systems such as the portfolio management system(IMS, etc.) What are the gaps that exist? What could have been an extremely complicated exercise, is simplified with DeepSightTM

Using a rules-based approach, and leveraging its AI and ML capabilities, DeepSightTM intelligently captures data from different sources – websites and internal systems and transforms it in a manner so that data is accurate, complete, and validate it.

Further, in case gaps exist, liaise with the data providers and exchange where requisite information can be available. Ensure that a golden copy of data is in a centralized data repository for further aggregation and analysis as per need.

Validating data and calculating key business values using DeepSightTM

Our powerful AI and Machine learning enabled DeepSightTM to analyze and validate data for completeness and accuracy. Data is enriched and categorized as well. Lastly, when it comes to the analysis of certain key elements required by Form PF, such as portfolio duration, turnover, liquidity, and market risk metric, DeepSightTM can be an invaluable ally.

Another key functionality of DeepSightTM is related to the calculation of key business values or metrices.

For more on what how we can make fund regulatory reporting less painful, reach out to us, at

Transaction monitoring is “the process of reviewing, analyzing and administering the transactions processed on a business application or information system”. It is extremely critical for Asset Managers, Hedge Funds, Banks, and Financial Institutions for downsizing risks in a volatile market and ensuring that the most stringent regulatory requirements are met.

Considering recent fiascos such as Silvergate and Silicon Valley Bank and the Black Monday of 2020 when global stock markets crashed on 16 March, and US stock markets suffered from the biggest single- day fall since the 1987 crisis, there is a lot at stake for Portfolio Managers, Asset Managers, and Financial Institutions as situations such as the above could have far-reaching consequences and create a negative ripple effect.

While Silvergate and Silicon Valley Bank suffered an ignominious ending, the Black Monday of 2020 resulted in banks and reserves globally cutting their interest rates and bank rates and offering unprecedented support to investors so that a repeat of 2008 would not happen.

Decoding the challenges faced by Asset Managers and Financial Institutions

Regulatory compliance: From a regulatory perspective, banks, investment firms, and asset managers must comply with certain transaction-based regulatory standards like the Money Market Statistical Reporting (MMSR) Regulation, the Markets in Financial Instruments Directive II/Regulation (MiFID II/MiFIR), European Market Infrastructure Regulation (EMIR), and the Securities Financing Transactions Regulation (SFTR). For banks and financial institutions, failure to monitor and report in a timely manner could result in massive penalties and further corrode their reputation.

Bogged down by bad data: However, monitoring and reporting in a timely manner is not easy. Asset Managers, Banks, and Financial Institutions are bogged down by many challenges, particularly those related to data. The data collected by old and archaic systems are constrained and rules/scenarios are not applicable or fail to produce the desired results. Banks and Financial Systems must also counter the fact that data is generally of poor quality – that is incomplete and inaccurate. With data emerging as the mainstay of an effective transaction monitoring system, inevitably, there is a lot that must be done to ensure accuracy, consistency, and fewer false positives.

Tackling potential disruptions quickly: Whether a Bank or an Asset Manager, they must make a case for dynamic transaction monitoring for gaining insights quickly so that potential scenarios can be tackled quickly. However, when they are burdened with humongous amounts of false alerts, monitoring becomes a challenge, and banks and financial institutions either need bigger teams or smarter technology and AUTOMATION.

Other challenges: Some of the other micro and macro challenges faced by Asset Managers and financial institutions today when it comes to regulating and streamlining transaction monitoring are:

  • Lack of standardization in the labelling of data.
  • Incompleteness of regulatory data information as per business need.
  • Monitoring and controlling data quality issues.
  • Lack of expertise for the implementation of regulatory requirement workflow in the financial system.
  • Managing the regulatory database and monitoring streamlined data flow
  • Reconciliation and distribution of feedback status from NCA, ARM to the Client.

How Big is the Risk? For Banks and Asset Managers

  1. In 2018, the US Bank National Association of Cincinnati, Ohio, (U.S. Bancorp) was fined $598 million. There were deficiencies in its AML program. To quote the experts, “systemic deficiencies in its transaction monitoring systems, which resulted in monitoring gaps…” It had among many deficiencies “outdated systems to conduct appropriate monitoring and due diligence.”
  2. Similarly, we can also consider the example of UBS which was fined $15 million for weaknesses in its automated monitoring system that resulted in poor monitoring or less than thorough monitoring of wire transfers by FinCEN in 2018.
  3. The worst single-day dip in the stock market happened on 16 March 2020, when the Dow Jones plunged by 2,997 points (earlier, on 9 March, there was a dramatic 2,014-point drop in the Dow Jones Index was followed by two more drops of 2,353 points on 12 March). This could have easily led to a seismic shock in the stock market, but a repeat of 2008 did not happen through the bullish phase of the stock market came to a halt.

In all the stories that have been mentioned above, we can observe a common thread, the regulators coming down heavy on banks and financial institutions for failing to meet the regulatory standards- and the chief culprit – an outdated and archaic mechanism that is unable to cope up the fluctuations in the market. When it comes to trading and stock market fluxes due to unforeseen circumstances, handling the spike in guideline violations, or emails can be tricky but with automation and a post-trade monitoring workflows that incorporate multiple levels of alerts, we can be

Today, as risk management teams are spending more than 10 % of the revenue on compliance adherence and regulatory announcements associated with fraud and Anti-Money Laundering (AML) have increased by more than 500% globally, there is increasing pressure to de-risk with automated and Artificial Intelligence and Rules-based solutions. And this is where a tool like Magic DeepSight TM comes in. A highly proficient rules-based data extraction platform that leverages technologies like artificial intelligence, and machine learning to provide massive (70% cost savings), exceptionally higher data accuracy, while streamlining your internal and regulatory transaction monitoring workflows and navigating the complex world of transaction monitoring with ease.

Automation, Rule-based, Process Standardization, and Data-Centricity – The Key Levers of Smarter Transaction Reporting

Automation is the key to keeping up to date and ensuring timely resolution of the alerts and triggers thereby saving time, money, and manpower and ensuring quality and standardization. Here’s how processes can be streamlined.

Magic FinServ raising the bar with DeepSightTM

  1. For comprehensive data transformation (and delivery), firms can count on Magic DeepSight™ for the delivery of results within a shorter span of time and from the widest range of data sources. DeepSightTM aggregates data from different sources (websites). It trawls different websites and identifies the data (for example corporate actions) and downloads it. DeepSight TM extracts only the relevant information from the massive amount of information available, saving considerable time in comparison to manual work. Thereafter, data is reconciled with a static database. In the process, data is transformed – and a Golden Copy dataset for all static data related to the customer account and securities is created.
  2. When it comes to process optimization, the capability of Magic DeepSight TM in bringing the required changes is immense. Process standardization, wherein a standard workflow is defined in sync with the business solution. The approach also involves defining a standard template and creating artifacts and documents for tracking and monitoring the regulatory workflow.
  3. DeepSightTM adopts a rules-based approach which makes the extraction of data more relevant. Business Rule engine implementation is another critical lever or pillar for streamlining transaction monitoring and reporting and ensuring transparency in pre- and post-trade and email reporting. For defining and implementing the business rules, the reference comes from the Regulatory Technical Standard (RTS), XML schema released by Regulatory Authority bodies such as the ESMA.
  4. DeepSightTM can be easily integrated with custom and industry platforms, so firms do not have to waste time figuring out how to do it. Lastly, a standard workflow for the Audit and Status report incorporation based on the feedback/acknowledgment received from the NCA enables another critical milestone – last-mile process optimization – without which the actual benefits of automation cannot be reaped.
  5. Below is a pictorial depiction of how Magic FinServ enables compliance and transparency of post-trade and email transactional regulatory reporting business MiFD II, SFTR – data as per ESMA with a data- centric, automated, and rules-driven solution for one of our clients.

Regulatory Reporting Business Process

Case Study: Ensuring System Integration for Back Office Automation Rollout for our Client

One of our clients is involved in all the post-trade transaction regulatory reporting business (MiFID II, SFTR, email, etc.). All the post-trade transaction data must be per the regulatory body ESMA. ESMA provides guidelines on how an asset manager must send all post-trade information to regulatory bodies, for ensuring transparency of business in terms of email reporting, MiFID II reporting, SFTR, etc. We implemented a solution where we got the information (data) from the customer and mapped the data to the XML schema, which is provided by ESMA. Thereafter, all the information defined in XML schema is shared with the NCA, the regulatory body for validation. The body decides whether it is correct or not. If data is missing, they revert to asking for more information to ensure that the regulatory needs are met.

Conclusion: What is in it for you?

Magic FinServ is an apt partner in your automation journey. We can help firms leverage their automation plans related to transaction monitoring with our incisive approach to data and process optimization. Here is how we do it:

  1. Understand the problem statement for filing transaction regulatory reporting
  2. Comprehend why is it that the organizations are not able to file
    • Is it a data problem – incompleteness of data, or,
    • lack a standard process or,
    • firm lacks the ability to understand the regulatory process
  3. Based on the inputs, we define a roadmap
  4. Then either use automation tools or develop internal automation tools on one’s own for streamlining the transaction regulatory monitoring. The biggest advantage is that Magic FinServ brings the technology to automate some of the processes that are extremely time consuming. Our bespoke tool takes away the pain navigating complex transaction monitoring (internal and regulatory). DeepSight TM is purpose-built for the financial domain and can meet the strictest standards to ensure streamlined operations (monitoring and reporting).
    • As it integrates seamlessly with platforms both custom-made and industry-leading, it obliterates needless work and ensures smooth workflow across business applications; with the capability to scale up or down as per the need.
    • Magic Deepsight™ pre-configured exception-handling rules weeds out errors more proficiently than before.

For more information on how we can add more value to your transaction monitoring, with our solutions you can write to us

The Diors and Chanels have ruled the World of Perfumes long enough! It’s time to get a scent that is custom created just for you!

A new-age algorithm perfumery is creating waves in the niche space dominated by Channel, Gucci, Louis Vuitton, and Versace where they are creating custom-made perfumes with the help of AI. However, what is a buzz in the beauty business is a critical requirement for the financial services sector. Customized solutions powered with AI and cloud are fully entrenched with the fintech and financial services objective is to facilitate full-scale digital transformation and elevate customer engagement by providing quicker, faster, and better services.

What comes to mind when we think about perfumes?

Chanel, Gucci, Versace, and Louis Vuitton…and the distinctive scent of each bold, fruity, citrusy, etc.

These perfumes are so exclusive and niche that even the brand ambassadors have a personality that resonates with the distinctiveness of the perfume. So, while Chanel favors the quirky, edgy boldness of Kristen Stewart, Louis Vuitton taps into the mystique of Emma Stone for its Coeur Battant fragrance. The perfume is available in pear, jasmine, ylang-ylang-ylang, and narcissus aromas.

Each of these perfumes is extremely exclusive, expensive, and sometimes a limited edition, and available at only a few high-end couture stores across the globe or in duty-free shops at the airports.

But what if the customer desires something new… or a mix of scents? Something that is super exclusive. – a distinctive perfume blending scents that is different from anything that the client has ever used before!

Now thanks to Algorithmic Perfumery, customized perfumes can be crafted on-demand. A US and Netherlands-based tech company is helping customers create their own perfume/custom fragrances in sync with their tastes and body chemistry. The customer can choose from an exclusive palette of scents and aroma molecules; and the perfumery using a proprietary AI algorithm and the customer’s preferences create a customized fragrance.

Sprinkling the scent of AI in the financial services organizations

While the use of AI for creating customized fragrances in the beauty business is a recent development, fintech and financial services firms have been using AI for creating customized solutions for some time now. In a way, AI has become an indispensable ally for the financial services sector, because of its ability to process copious amounts of structured and unstructured data within minutes and provide clear-cut insights with its inbuilt intelligence and rules engine and automation capabilities. In fact, by leveraging AI and automation capabilities, customized solutions can be delivered at a scale unimaginable. Behind that reminder for payment, or stock update, or timely notification there is the hand of AI.

Band of AI

A Brief History of use of AI and the Rise of Expert Systems

The fintech and the financial services sector have come a long way from 1982, when the quantitative hedge-fund, Renaissance Technologies, became the first organization to rely on AI to parse through petabytes of data in warehouses for analyzing securities prices in any market. Today, its AUM is worth US $ 130 bn (April 2021).

Many financial services organizations were also beginning to use AI-enabled expert systems. One of these was the PROTRADER expert system for program trading. The advantage of the PROTRADER over traditional systems was that only it had the intelligence to provide the insights and keep track of the rapid changes in both markets futures and stock markets usually several times a minute.

Then in the 1990s, the biggest concern for firms was tackling fraud and anti-money laundering activities that was systematically chipping away the brand value that they had created. Around the same time, FinCEN’s Artificial Intelligence system (FAIS) managed to review 200,000 + transactions, and FIs realized how AI would make their life simpler. The same system then identified 400 potential money laundering cases that could have cost organizations $1 billion. This was the wake-up call for the FIs.

How is AI being used in Fintech Industry – New Frontiers and Predominant Trends

Today AI and modern technology has an ever-growing list of use cases in the fintech and financial services sector. The unprecedented proliferation of data – structured and unstructured and the increase of computing power, along with changing customer preferences, have resulted in AI adoption in back, middle and front offices, – from the conversational bots to data transformation engines working quietly in the backend going through tons on data, AI undoubtedly has emerged as a key player. Here are some of the prominent use cases for AI.

  • AI and ML solutions are used for predicting market trends and customizing portfolios.
  • Make intelligent underwriting decisions using a rules-based system
  • Carrying out keyword searches from extensive documentation – SEC filings, company releases, filings, transcripts social media, etc., using a rules-based engine.
  • With AI, ML, and OCR the processing time for KYC and onboarding is cut by half.
  • For streamlining fraud management and anti-money laundering processing by ensuring timely triggers are raised.
  • Protecting the rights of minority shareholders, and the investment company from libel in the worst-case scenario by ensuring accuracy in shareholding and voting rights disclosures.
  • With Artificial intelligence, you can reduce process automation time considerably by taking over repetitive tasks.
  • For algorithm trading – trading robots (or bots) carry out operations using the algorithms and data

Magic FinServ: How we customize solutions for every customer with AI, ML, and Cloud

As a partner, enabling the fintech growth journey, Magic FinServ has been providing customized and extremely niche solutions for every stage of the fintech journey. Our services ranging from quality testing and support for application development, smart contracts, cloud support during migration and application development, and intelligent data extraction and insight-building powered with our very own home-grown tool that uses artificial intelligence and machine learning for digital transformation. Here’s the milestones that cover the journey from start to finish.

  1. Identifying the need: Whether the client is in search of a scent for a fintech solution, the first milestone is to identify the need. When a customer approaches Magic FinServ, our team of experts comprising the best in finance and technology, take a deep dive into what they truly want. We utilize a mix of extensive research and prototyping to provide solutions that are tailored according to the client’s needs.
  2. Design process: Once the need has been identified, it is time to design the solution. We know that a customer’s requirement changes across every milestone of the journey, and so we scale up accordingly. Our teams are proficient in working in a highly competitive landscape and use the industry best practices to provide a solution that is customized as per your need. We make special mention of the ability to design interfaces that are in sync with industry best practices by combining the collective synergies of the client product management team and our magicians.
  3. Evaluating the samples: As in the perfumery business where multiple iterations are required before a final version of the perfume is handed over to the customer, ideas and innovations whether it is a database transfer or a new product or feature launch, must be exhaustively tested. Tests for performance, latency, bugs, integration, APIs, and acceptance, functionality, etc., are crucial to ensure the desired results.
    We offer the entire range of testing services under one roof for the financial services business along with extensive experience with on-cloud, on-prim & mobility products. Today, as citizen developers are playing a more proactive role in all phases of the app development journey, Magic FinServ provides the much-needed boost to platform engineering experience of enterprise application development and financial industry domain knowledge with new-age technologies to power your digital transformation.
  4. Customizing the cloud journey: No talk of customization is complete without a mention of cloud technology. Today, as fintech and the financial services sector become synonymous with cloud-nativity, enterprises must also build the right cloud architecture for their needs. Whether it is hybrid, or public and private approach that they desire, Magic FinServ helps them optimize the journey.
  5. And lastly, Magic DeepSightTM that takes care of all your data and deep insight needs: As a technology company with years of experience in AI and financial services, Magic FinServ understands the importance of data in the financial services business to re-engineer existing applications, design new platforms and validate machine learning solutions. We have a team of data scientists and engineers dedicating their efforts to develop systems that become smarter over time and reduce operational effort considerably while enhancing decision-making capacities.

We have a library of AI-driven fragrance formulas to inspire you in this Fintech Transformation Journey.
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