Articles related to fintech (financial technologies) and fintech software development.

Robo advisors – new wave in FinTech

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In the space between DIY investing and personal — but pricey — financial advisors sits the robo-advisor, a crop of firms that manage client portfolios via computer algorithms, cutting prices and passing the savings on to investors. These online advisers have taken off over the last several years: There are currently a couple hundred firms in the race.

What’s a robo advisor?
A robo-advisor is an on-line financial advisory firm that leverages automation and algorithms to help manage client portfolios. That automation empowers robo-advisors to offer investment management services to consumers for a fraction of the price of a financial advisor that is human. Lower fees, joined with superior features like automatic rebalancing and tax-loss harvesting, can yield higher returns.

How they work
Most of the companies urge portfolios of low cost exchange-traded funds according to surveys that are on-line that investors fill out. The thought is that investors will do with generally diversified portfolios and low fees.

The companies use algorithms to put investors into various portfolios according to risk tolerance.

How to use Robo-Advisor

Automated Customer Onboarding – the questionnaire

The questionnaire is the first step of using Robo Advisor. User’s profile is being created with parameters like:

  • age (defining overall risk aversion level)
  • investment goals (defining users expectations)
  • users experience with losses/gains
  • making important financial decisions

Our Robo Advisory platform covers the interpretation of user’s answers into automated advise.

 

Balance projection

Balance projection gives the user quick view how his portfolio balance would look like in the future for given investment values. In order to make the projection more eye-catching we introduced possibility of generating balance curve based on either static growth or mathematical function development. For example, on average, portfolio increases 4% every year.

 

Asset allocation

Asset allocation is the selection process of the right instruments adequate to users risk profile. Our platform allows to automate managing the allocation, using defined algorithm. For example, with higher portfolio risk we can invest more into stocks and with smaller portfolio risk we invest more into fixed income products. Real asset allocation model has to be decided.

 

User Portfolio,

It is possible to monitor user’s portfolio balance in user dashboard. Platform provides history of portfolio balance over the selected period. User is able to check his current portfolio allocation grouped by three factors:

  • Instrument type
  • Instrument sector
  • Instrument region

 

Portfolio rebalancing

Automated portfolio rebalancing is a crucial functionality for robo-advisory service. Let’s assume that user got asset allocation with 60% stocks and 40% fixed incomes. Over the time, because of the reinvesting dividends or other user-defined factor, his portfolio allocation changed to 70% stocks and 30% fixed incomes. User does not want to take such a big risk so we do portfolio rebalancing to back to original allocation.

 

 

List of successful robo advisors

Betterment
Betterment is a perfect starting point for young investors. They make investing easy for beginners by focusing on simple asset allocation, goal …

Personal Capital
A free and easy-to-use service that syncs up all your financial accounts in one location. Personal Capital creates summaries of your spending, net …

Wealthfront
An automated investing service with an emphasis on asset allocation with low fees. Wealthfront’s service really shines with taxable accounts….

Stash Invest
Stash could be the perfect investment app for a new investor. Its $5 minimum initial deposit removes the single biggest obstacle to investing, but the…

Fidelity Go
Fidelity’s entry into the robo-advisor service helps beginning investors. Its pricing is very transparent, and if you have an existing account, …

Aspiration
Aspiration may be the perfect robo-advisor service for anyone who wants to invest in socially responsible companies. They have low fees, and the fee-…

Vanguard Personal Advisor Services
Overall a solid entry into the robo-advisor space. Though the service will exclude beginning investors because of the high minimum deposit. Other robo…

WiseBanyan
WiseBanyan is a free robo-advisor service with some decent features. Unfortunately, we question if the business model is sustainable….

Hedgeable
Hedgeable brings the techniques of hedge funds down to the less well-heeled masses, so everyone can have access to the investment industry “secrets.”…

TradeKing Advisors
TradeKing Advisors is a platform well worth investigating if you’re looking for professional investment management at a very low fee and $500 deposit …

Charles Schwab Intelligent Portfolios
Overall a decent service that deserves a looking into. Though we question its large allocation to cash and choice of some of the ETFs in order to make…

LearnVest
LearnVest is a decent free budgeting tool. Though compared to its competitors lacks investment reporting. Financial planning is available for an …

Rebalance IRA
Rebalance IRA provides insight into your portfolio and helps you make better decisions by not letting emotions get in the way and selling too often, …

AssetBuilder
AssetBuilder might be a reasonable service to use on large accounts, particularly over $20 million where the annual fee is just 0.20%. But on smaller …

Financial Guard
Financial Guard offers straightforward advice, to upgrade your current portfolio, pay lower fees, and choose better funds. Their business model is …

SigFig
SigFig itself isn’t a bad service, but their recommendations seem simple at best. There are better robo-advisors available….

Wealthsimple
Truewealth

Personalcapital 

FutureAdvisor 

 

Extending the customer base

With a customer base that the size of each of the competition combined, based on Stein, robo advisory Betterment can also be bringing folks, along with assets. It’s not difficult to chalk that up to Stein, and its $0 account minimum admits that some of Betterment’s accounts are modest. But he says all of the customers counted in that tally are saving into funded accounts, with most putting a sizeable amount that is “ away.”

That minimum — or instead, the lack of one — has set the pressure on other robo advisors as well as traditional advisors, many of which have dropped their own minimums over the past year. Private Capital, which has $1.8 billion in assets under management, recently lowered its account minimum by an ambitious 75%, falling from $100,000 to $25,000. The company might have the ability to get away with a minimum still in five digits because its customers also get a dedicated financial advisor.

TradeKing Advisors has lowered its minimum. It found its two tiers of service with initial deposit conditions of $25, and $10,000 000; those minimums now sit at $ and $5, 000. Rich Hagen, the business’s CEO, told NerdWallet that minimums were lowered to remain competitive.

And Wealthfront lowered its account condition 500, noting from $5,000 to $ in a blog post that it was reacting to a “surge in demand” from youthful robo customers . Those customers desired to take advantage of Wealthfront’s generous pricing arrangement, which manages the first $10,000 completely free (Betterment bills 0.35% on accounts under $10,000 that consent to a minimum $100 monthly auto-deposit; those without auto-deposits are charged a monthly fee of $3. That $3 a month — which amounts to more than 7% per annum on a $500 balance — is a point of contention between the two robo-advisors, including a public war of words on Medium.)

 

 

What to look for

To the reader that is causal, the differences between robo advisory companies might appear small but in reality isn’t. You’ve got a choice between:

  • Minimuml Deposit – Some robo advisories it is possible to start out with others and nothing need substantial sums to begin with
  • Yearly Fees – Know about ETF fees and hidden costs
  • Asset allocation – Asset allocation of each robo advisory may differ quite a bit based upon how old you are, and just how their risk assessment questions are answered by you
  • Account Type Support – Do combined, they offer individual, IRA, etc.
  • Automation – Some robo services are 100% automated vs human assisted advice
  • Tax Optimization – Services like Tax-Loss Harvesting
  • Custody of Funds – Handled by you in which they give advice to trading, or directly by the company
  • Management of Assets – Manage only a part or all of your assets
  • Ending-Target – Retirement simply, or other targets (i.e kids education)

 

Best Robo Advisors – Breakdown by Asset Size (2016 Ranking Comparison)

Below is the listing of this year’s top robo advisors by asset size.

# Robo Advisors Total Assets Under Management*
1 Betterment $4,200,000,000
2 Charles Schwab $4,100,000,000
3 Wealthfront $2,800,000,000
4 Personal Capital $2,100,000,000
5 FutureAdvisor $600,000,000

Warsaw Stock Exchange certifies our Trading Platform

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Empirica’s Algorithmic Trading Platform has successfully passed the XDP protocol communication certification, issued by the Warsaw Stock Exchange.

From now on Empirica is officially listed as the ISV (Independent Software Vendor) for the Warsaw Stock Exchange.

WSE uses Universal Trading Platform delivered by NYSE Technologies. The same system is used by many other European and world stock exchanges. Fulfilment of technical criteria of Warsaw Stock Exchange makes certification for those markets only a formality for our platform.

The look at best companies in robo advisory space

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Some of the recent technology led disruptions in the financial industry are in the areas of giving, payments, money transfers, wealth management, data that was big and cybersecurity. Furthermore, blockchain has opened up endless possibilities for online transactions without need for an intermediary. Today Fintech companies provide financial services using different types of high tech alternatives, thereby competing with the conventional businesses.
More than 20% of financial services business is at risk to Fintech. The financial service players comprehend the threat, but, aren’t certain about the best way to react. E.g., 57% financial services players are unsure about how to respond to blockchain technology; though there is huge potential for transformation through adoption of blockchain in each area of financial market, e.g., capital markets.
FinTech in Wealth Management
The key FinTech led innovations in Wealth Management are in the areas of appraisal of risk profile of the investor, automatic asset allocation, advanced analytics for better investment support, integration of social data for enabling investment decisions, standardization of advice & products to appeal to the cost- conscious investors, scalable distribution design for tapping emerging markets, enhanced performance abilities from integration with decision support systems and shift to technology enabled investment guidance with exception based human intervention[iv].
Financial Advice
When selecting wealth managers clients value a business’s standing and trust more than a counselor’s standing. And though planning is an important factor in driving clients to wealth managers, it becomes more irrelevant when actually choosing an advisor/business. Over 50% customers speed digital channel and self- service capabilities as the top variable for client service encounter, followed closely by accurate account information and efficient procedure. Clients say sites and mobile capabilities will be their primary channels for receiving guidance (59%) compared to divisions (26%) in another two to three years. 46% customers are willing to start an account with robo advisor.
Robo Advisor technology has the potential to cause the largest disruption in Wealth Management, since it’s at the core of most of the above innovations. Robo Advisors basically transform the most significant element of the Wealth Management business, viz., financial guidance.
Products created banks, by asset managers, insurance companies and others to the investors are delivered by the Wealth Management Value Chain.
The whole Wealth Management value chain is influenced by Robo Advisors:
  • Investors – anticipate to get standardized advice through digital channels at any time of their choice, low cost, through self-service mode
  • Advisers- consequently align the merchandises and rely extensively on analytics capabilities of the Robo Advisor to examine investor’s profile and inclination
  • Dealer Groups & Product Makers- keep the standardized products off-the-shelf to satisfy investor’s demand, e.g., wraps
  • Asset Managers, Banks & Insurers – Create and distribute products especially targeted at the investors who need low cost, standardized products, e.g., index funds
With the growing competition from new Fintech players like WealthFront, Betterment, LearnVest, and FutureAdvisor, the mainstream adoption of Robo Advisors is bound to gain impetus.
Best Robo Advisors in 2016
 
The robo advisor field is getting crowded, with new platforms springing up consistently and changing frequently. These exciting algorithmic automated trading platforms comprise of many different players. Some robo advisors (or digital advisors) have higher minimums and more advanced investments platforms. Others use a low cost, low fee secure of index ETFs and mutual funds.
Picking the five finest robo advisor for 2016 is a job that is challenging, because the best robo-advisor for you might not be the best option to your neighbor. Having said that, we’ll analyze, several factors and standing robo -advisers based upon these criteria; low initial investment, low fees, and quantity of services. In general, each of the five finest robo-advisors for 2016 offer well-studied, low fee investment options.
In this evaluation we’ll assume that lower fees and lower investment minimums are preferable along with portfolio management services that are greater. This study presumes that more investment alternatives don’t automatically translate into a much better product while some investors prefer access to a greater variety of investment options. (For more, see: Are Robo Advisors and FA’s Worst Nightmare?)
1. TradeKing Advisors
TradeKing an affiliate of TradeKing Securities, Advisors , LLC is a web-based investment advisory service that offers professional portfolio management to all investors at an affordable cost. The investment process is not difficult. Several questions are answered by you from a risk tolerance questionnaire. Next, TradeKing Advisors provide you with a diversified investment portfolio, managed and designed by the industry experts at Ibbotson Associates, a Morningstar firm.
TradeKing Advisors offers two investing strategies, Center and Momentum portfolios. Additionally, TradeKing is the only advisor in this list that offers the momentum approach.
To develop a portfolio you need at least $500 for a Core Portfolio and $5,000 for the Impetus Portfolio. The five Core Portfolios include a maximum of 17 asset categories with a mix of exchange traded funds and notes. The advantage types comprise national equities, foreign equities, fixed income securities as well as real estate assets. The Momentum Portfolios attempt to harness the market movements and trends.
There is no minimum investment amount to start an account. Fees for portfolios worth more than $5,000 are competitive at TradeKing. The yearly fee for any size Momentum portfolio is 0.50% AUM.
For an additional fee, investors in Core Portfolios may subscribe to Risk Support, an application that tries to stabilize your investments by reducing equity exposure ’ values. The cost for adding Threat Help to Center Portfolios is an additional 0.50% or 0.75% (0.25% 0.50%).
In return for the advisory fee your preferred portfolio is constructed and manages by the adviser. This consists of reinvestments and rebalancing. There are no transaction fees. Unlike most of another robo advisors, TradeKing does n’t offer tax loss harvesting. (For more, view: TradeKing vs. TradeStation: Which Meets Your Needs?)
2. SigFig
Unlike the other robo advisers mentioned, you do a distinctive account is opened by n’t but keep your present investment accounts.
SigFig begins with a quick risk quiz, based upon how old you are and time horizon. The platform has a robust portfolio tracker program which reveals investment yields, your asset allocation, fee breakdowns and more. They have two kinds of services, Asset Management and Diversified Income. This post targets the Asset Management offering.
Funds are recommended by the SigFig strategy based upon a variety of standards, including risk-adjusted three-year historic performance, fees, evaluations and various other variables. That is a $2,000 minimum balance.
SigFig is free for accounts less than $10,000, and the first $10,000 is always handled for free The accounts worth more than $10,000 also have access to an on-line personal investment . that is advisor
This tool optimizes your portfolio and helps minimize fees and maximize returns. When managing a portfolio, SigFig asserts to pick lowest fee funds considering tax impacts and while optimizing returns.
3. Wealthfront
Wealthfront manages a personalized, diversified investment portfolio with a variety of low fee ETFs and builds. The portfolio asset categories are allocated based on the results of a threat survey that was short
Wealthfront’s investment strategy is grounded in modern portfolio theory passive investing strategy. This strategy strives to give the investor the best yield for the least number of danger by using low cost funds.
Wealthfront recently lowered its minimum investment amount to an affordable $500. Additionally, there are not any management fees for accounts valued at less than $10,000. Once you hit $10,000 the Wealthfront platform fees are 0.25% of AUM. Similar to SigFig, always is the first $10,000 handled free. There are no trading fees and the underlying mutual fund fees average a low 0.12%.
Wealthfront offers several portfolio management services that are added. The single-stock diversification service addresses the ‘overweight in company stock’ problem for employees with an abundance of business stock. The company claims to practice ‘tax- optimized direct investing ’ a strategy for tax-loss harvesting and minimizing investing prices. In lieu of the actual index ETF, individual stocks representing an index are bought under this particular practice in order that particular stocks may be sold for tax loss harvesting. The company also performs ‘day-to-day tax-loss harvest’. Finally, Wealthfront offers regular rebalancing.
4. Betterment
Wealthfront’s closest competition, Betterment offers a low cost, investing approach that is passive, index fund. Betterment starts out with a brief hazard questionnaire. Betterment guarantees to get each customer and the greatest yields for the least amount of risk the optimum fund mix. Their offerings include 12 asset classes that account for time horizon and your risk inclination.
Similar to Wealthfront, Betterment’s investment alternatives include low- index reciprocal, fee or exchange traded funds. The Betterment platform allows for up to 12 stock and bond funds signifying both international and U.S. investment opportunities.
Betterment’s fees range from 0.15% to 0.35%, depending upon the AUM and auto-deposit pick. Betterment does not have a minimum investment amount. For accounts valued at less than $10,000 there are 2 pricing options; with at least a $100 per month auto deposit, the management fee is 0.35%, without automobile deposit, the fee for lower balance account is $3.00 per month. There are no additional transaction fees, except the fundamental low expense ratio fees billed by the fund companies. The ETF management fees range from 0.09% to 0.17%.
Eventually, services that are additional are additionally offered by Betterment. Consumers receive personalized advice, intelligent rebalancing, tax efficiency that is extreme and tax loss harvesting. (For more, see: Wealthfront Versus Betterment)
5. Schwab Intelligent Advisor
Schwab’s recent entry into the robo advisor domain makes a splash on account of its model that is free. This platform guarantees no advisory fees, account service fees or commissions. Schwab Intelligent Portfolios calls itself an “on-line investment advisory service that rebalances your portfolio, and assembles, monitors -so you don’t have to.” Similar to Betterment, Schwab is aims- established and helps you keep on top of your savings and income targets.
Schwab requires at least $5,000 to open an Intelligent Portfolios account. That is the highest minimum prerequisite for each of the robo-advisor discussed in this article.
The first 12 question query form gives Schwab the advice to design your portfolio. Although their ETF portfolio allows for up to 20 asset categories, your individual account may not contain each of their offerings. Schwab has the broadest asset classes and investment options of any of the former advisers that are automated and includes property, fixed income, stock, and commodity ETFs. Where Schwab differs is in the allocation to cash. Each Intelligent Portfolio has a percentage invested in cash. Schwab clarifies that cash is not unimportant to some well-diversified portfolio and enhances stability, liquidity, diversification, and protects against possible inflation.
Schwab can afford to offer a no-fee service because they’ll get earnings on the consumers’ investments their ‘Schwab- money market funds’ and branded ETFs. Additionally they may be compensated by the firms which make the trades. As with all of the companies, there are annual management fees for the underlying ETFs. According to Schwab, “ETFs offered by other online advisors have operating expense ratios in ranges similar to that of Schwab Intelligent Portfolios.” The total operating expense ratio of a typical portfolio will range from 0.12% for a conservative portfolio for 0.25% AUM for the more aggressive investor.
Schwab’s services include the typical automatic rebalancing. Eligible for the automatic tax loss harvesting .
In accordance with the criteria of low fees, diverse index fund offerings, and robust services, the best robo advisor for 2016 goes to SigFig. SigFig offers the most extensive collection of services, including an online private adviser for accounts greater than $10,000. Their app is state of the art and the portfolio corrector is powerful. That said, it’s a rough contest to call the winner of the ‘best robo advisor’ because it is important to think about your own personal situation. If you will want platform which holds your assets within their custody, then certainly one of the other robos might be a better fit for you.
 
 
Why humans are not best at wealth management
 
Most financial advisers are human. And that’s an enormous difficulty.
Humans come hardwired with cognitive biases that frequently lead them to make best choices that are financial. Research implies that people see patterns in data where none exist, they believe they’re more knowledgeable or skillful than they actually are, and they overlook possibly important advice, even when it’s as clear as a gorilla on a basketball court, as a well-known experiment proved.
And, regrettably, financial professionals are equally as individual as their customers, leaving them just as vulnerable to cognitive biases. Studies have found that mutual-fund managers—professionals who are arguably very inspired to beat their inclinations that were adverse — make expensive investment mistakes, just like others.
The effect of those errors is important underperformance. One of the big appeals of advisers that are human is active management—the thought that these are investment experts who make moves that deliver returns that are larger than simply tracking an index, for instance.
Yet the evidence consistently demonstrates that managed funds have a tendency to underperform passively managed ones. So pick an unpredictable although active human advisor as opposed to a robo advisor, which will typically take a passive approach that produces yields that are more consistent?
If investors feel confident that cognitive biases can be defeat by their human adviser, there’s another issue to consider: Human advisors have financial incentives that don’t constantly work to the benefit of their clients.
An investor with deep pockets might sidestep this issue that is particular by seeking an independent advisor who charges an hourly consulting rate in the place of relying on commissions or performance fees. But many individuals may not be able to manage this alternative.
Consider an investor socking away a handful of thousand dollars every year over a lifetime. A human advisor might charge that investor an annual fee of 1% to 2% of assets versus a robo-advisor fee of 0.25% to 0.50%—a difference that can amount to tens of thousands of dollars in lost wealth. Robo advising offers a viable, low cost investment option that’s within reach even of investors that are new starting out with little nest eggs.
Needless to say, the robo-advisor name is a tiny misnomer; some of these services offer their clients the opportunity to connect to a person if they believe they want additional hand holding. That fuels the argument that robo advisers can’t supply the in depth, hands-on services that people can.
Yet, in several cases, digital advisors are fully capable of providing cogent evaluation and helping investors understand aims and their needs. Actually, in some instances, a robo advisor is even better equipped to provide service to customers than a human adviser. But a robo adviser could send all its clients electronic messages at the same time to remind them that their portfolio was selected with their characteristics in mind, and it remains appropriate in the face of market changes.
It’s additionally important to note that while investors may feel comforted by the idea of the “human touch,” the conflicts of underperformance and interest at traditional advisors help it become clear that the human touch may cultivate a false sense of security.
Needless to say, robo advising won’t fit every situation. Investors with complex company, estate or tax circumstances may benefit from the more customized guidance of a conventional financial adviser. But for the majority of investors, robo advising offers advantages that can interpret into a more buxom bottom line as opposed to typical adviser that is individual can deliver.

Benefits of robo advice

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Benefits of Robo Advice according to ESMA

Robo advice has had a major impact on the wealth management industry. Several wealth managers have already started a robo advice alternative; others are or have a choice in development reviewing strategic options.
Measures for Wealth Managers
Wealth management companies assessing their choices associated with robo advice should assess five essential factors:
1. Alternatives will be developed in house,through a venture, or via theacquisition of a current supplier.
2 The robo advice will be placed—as a standalone offering, within a full service financial advisory program a hybrid vehicle of both.
3 Whether the company has the analytics customers and to get the tips and insights to work efficiently with them.
4 How the product will provide an intuitive and satisfactory customer expertise. That is usually reached through an iterative procedure involving prototypes, client laboratories and high-speed revisions and improvements.
5. Internal and external advertising management plans undertaken
We consider the effects that are most significant on the business, nevertheless, will come from capacities which haven’t yet. Which, although been released to the marketplace are legitimate extensions of robo advice abilities. As well as cognitive these comprise the add-on of investments besides ETFs, eventually, alternate investments such as property and hedge funds. The increase of robo adice matches up with that being indicated by business trends. More cooperation is being sought by investors and integration with their advisers. Rather than just being told how their cash is how it’s and invested performing, robo advisory gives investors a manner to connect to their advisers, raising their participation.

Benefits to financial institutions

Benefits relating to cost
Financial institutions incur fewer costs to deliver financial advice
It may be cheaper for financial institutions to provide advice through automated tools, for example because automated advice does not require the employment of human advisers, or because fewer costs are incurred from potential human errors. Although a period of initial investment is required, once the cost of system development has been met, the marginal cost of each new transaction may be relatively low, enabling financial institutions to benefit from economies of scale.
Benefits relating to the size of the potential client base 
Financial institutions have access to a wider range of consumers if they provide advice through automated tools
By providing advice through automated tools financial institutions may have access to a wider range of consumers, not only due to the relative ease of attracting a potential clients from across the EU via an online presence, but also because they can attract new categories of consumers that prefer to use online channels as opposed to face-to-face or telephone channels. Financial institutions can thus benefit from automated tools to increase their distribution platform to deliver advice.
Benefits relating to the quality of service
Financial institutions use automated tools to deliver a consistent consumer experience
Automated tools may be seen by financial institutions as a way to deliver a more standardised consumer experience by removing the potential for differences due to human interpretation.
An automated tool may also enhance the quality of the service provided to consumers by providing a direct link with current market or other relevant data. Automated tools can more rapidly process large quantities of evolving data and consequently update the advice output on a real-time and ongoing basis, if needed.
The provision of advice by financial institutions is more easily auditable because automated tools are more easily interrogated
Automated processes that are documented ex ante, for example in the logic of an algorithm or decision tress, can be easily reviewed and monitored by financial institutions (e.g. by Compliance, Risk or Audit functions).  It may be also be easier on an ex post basis to interrogate decisions made by an automated  tool, which performs tasks in a highly consistent manner than decisions that have been made by a human being.
As automated tools can generate an automatic record of the information that has been captured, the decisions made, and the output provided, it may also be easier for financial institutions to maintain records of the advice process, and to provide such records, for example in the event of a consumer complaint.

Benefits to consumers

Benefits relating to cost
Consumers pay less when they receive advice through automated tools
Automation in financial advice could decrease the costs of providing advice, which might make advice more affordable to a wider range of consumers. Most automated advisers market their offering as a low cost alternative to human advice.
Benefits relating to consumer access
A wider range of consumers has access to advice through automated tools
Consumers that may not normally contact a human advisor to obtain financial advice (e.g. because they feel that they are not wealthy enough to consult a financial advisor, or that the advisor is not objective enough) might feel more confident using robo advice tools. Increasing automation may therefore democratise access to financial advice.
Some categories of users  do not have experience in consulting a human financial advisor (for example, younger consumers, or less affluent consumers where the cost of financial advice may not be worth the benefit of the advice provided). These consumers might feel that robo advisory tools, which can also offer financial advice at a lower cost and with limited investment of time, are more accessible than advice provided by a person. This might give some investors greater motivation to act upon financial matters that they would not if they were using a human adviser.
Consumers have access to a wider range of service providers using robo advice tools 
As automated financial advice tools are usually available online they more readily facilitate cross-border transactions, compared to human advice. This makes it easier for consumers to access a wider range of advice providers, including from other jurisdictions.
Consumers obtain financial advice in a faster, easier and non-time-consuming way
Because robo advisory services are available online 24 hours a day, 7 days a week, and are aimed at reaching a wide range of consumers, consumers may feel that automated tools that provide advice are easier to use than a human adviser. For example, online automated tools may present information to users in a short and digestible way. It also usually takes only a few moments after an initial questionnaire is answered by the consumer before the advice is obtained as a result of the underlying algorithm.
Benefits relating to the quality of service
Consumers receive more consistent advice when they use automated tools 
A well-developed algorithm may be more consistently accurate than the human brain at complex repeatable regular processes, and in making predictions.  Robo advice tools could therefore reduce some elements of behavioural biases, human error or poor judgement that may exist when advice is provided by a human. A well-developed algorithm could ensure equal and similar advice to all investors with similar characteristics. This might improve the consistency of advice provided, regardless of the investors’ geographical residence or ability to identify and access a quality human adviser.
Robo advisory tools may also enable users to receive advice without feeling pressured or led as a result of personal relationships. Without the human interaction with an advisor, some consumers may feel they can take their decisions more freely and objectively.
Consumers obtain advice based on the most up-to-date market information when using an automated tool 
Because robo advisory software tools are able to rapidly process large volumes of complex data, it is possible for an automated tool to quickly assess and reassess the recommendations it makes against current data, on an ongoing basis. For example, robo advice tools can incorporate market changes continuously, to provide real-time, personalised feedback to consumers. Human advisors may find it more challenging to be as constantly up to date with relevant market developments.
Consumers find it easier to keep a record of the advisory process
The use of robo advice tools allows investors to easily receive and retain the details of their financial transactions online. For example, as robo software tools systematically record all the stages of the advisory process, they can easily provide a print out of the questions and answers which lead to the recommendation. This may help users in the future, for example if they have a query about the advice provided

Robo-advisers are systems that use algorithms to handle users’ investment platforms. And they may be threatening to upend the tremendous wealth management business that is international.

BI Intelligence predictions that robo-advisers will handle around 10% of overall worldwide assets under management (AUM) by 2020.

In a fresh report from BI Intelligence, we examine the marketplace for robo-advisory services, the motorists behind consumer adoption of robo- guiding the robo-adviser marketplace presents a chance to wealth management businesses that are conventional, and how startup robo-
As substantial legacy businesses start offering their own services counselors can triumph.

Big riches supervisors that are incumbent will not lose out to startups like Wealthfront and Betterment. Rather, they establishing their own products, which are scaling fast and are adopting the technology.
Consumers across all asset types are open to robo-advisers — such as the rich. 49% of the group would consider investing some of the assets using a robo advisor.
Many assets managed by robo advisers will come from those who have some investments.

Startups will have to identify their products to triumph, and are likely to find it hard to scale. They may be doing this by supplying riches managers with white label services, and more customized stand alone options.
Next steps for robo advice
We believe that robo-advice will, however, finally have an outsized impact on the wealth management business. The capabilities will, for instance, accelerate the process of fee compression which is already affecting the industry. The lower cost for robo-guidance services probably will put pressure. Wealth management companies must keep a close attention on methods to automate processes and transactions that are currently performed manually and on operating costs.
Robo advice may also give accessibility to a big new marketplace of millennials who are interested in amassing wealth, but have had only limited choices when it comes to investment management to wealth management firms. As these individuals develop and assemble assets (through their own efforts and through inheritance from their boomer parents and grandparents) they can represent an important growth opportunity for wealth management companies.
Ultimately, improvements in technology— particularly in cognitive computing and “smart machines” capable of complex reasoning and interaction with people — will transform the investing landscape in ways that are potentially disruptive. For wealth management firms, robo-guidance services can be a bet on the future — a method to get customers and financial advisors acclimated to working with machines that can enhance and expand human operation.
The time to think about this new FinTech wave, and prepare for it is now.

Empirica in the press – ‘The age of robots … ‘

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On the first of July 2014 large polish economic magazine Puls Biznesu published an article “The age of robots comes to Warsaw Stock Exchange’. Article is quoting, among others, Empirica’s representatives speaking on the topic of the growth of algorithmic trading in Poland. Excerpts below.

‘Popularization of algorithmic trading on conferences like this one is step in good direction, says Michal Rozanski CEO of Empirica, a company which delivers Algorithmic Trading Platform. Expert says that computers will never replace a human in all the tasks. First and the foremost machines are taking over the processes that human traders had to perform manually. ‘I am sure that the development of algorithmic trading will not change the soul of the markets. It will not change to the race of engineers. It is and always has been the race on new, better ideas.’ says Michal Rozanski. 

 In his opinion both small and big investors will benefit. ‘Appliance of algorithmic trading tools increases liquidity and descreases bid/ask spreads which in turn decreases transaction cost born by all investors’ adds expert.

Michal Rozanski stresses that appliance of algorithmic trading does not limit to transactions with shortt time horizon, e.g. counted in miliseconds. Each trader can designs algorithms adjusted for it’s own requirements. ‘Let’s imagine an investor who would like to open a large position on KGHM shares or futures on WIG20. To make it happen it’s best to divde the order to tens or hundreds of smaller orders, which allows to hide her intentions from other market participants. Investor remains anonymous and minimizes market impact of her large order.’ explains Michal Rozanski. 

‘I am convinced that development of algorithmic trading can be a breakthrough moment in the history of our market, as long as we will treat the matter seriously and deliberately. On Wall Street share of algorithms in total turnover is estimated at 50%, in Europe at 40%, and in Poland still at below 20%. ‘ says Adam Maciejewski, CEO of Warsaw Stock Exchange.

Link to article…

artykul_pb_era_robotow

Empirica holds workshop on Warsaw Stock Exchange

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Algorithmic trading workshop took place on 27th of July 2013 as a part of the second conference held by economic magazine ‘Puls Biznesu’ and Warsaw Stock  Exchange.

Michał Różański, representing Empirica, held workshop on the practical aspects of selecting tools for algorithmic trading by financial institutions. He stressed and covered in detail, especially one aspect of algorithmic trading which is from our practical experience constantly undervalued – namely proper testing of algorithms.

Very interesting was also a lecture of Emil Lewandowski who showed an algorithm which was able to detect a flash crash an hour before it actually happened. Algorithm was implemented, backtested, executed and presented to all the participants our Algorithmic Trading Platform. It was indeed very interesting example of application of algorithmic trading!

Among other guest were representatives from IBM, Sungard, List and M10.

Link to event:

http://konferencje.pb.pl/konferencja/705,handel-algorytmiczny-cz-ii

Artificial intelligence in FinTech

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FinTech : It is just starting

FinTech sector is producing businesses with scalable products and has seen rapid growth over the past few years. Senior executives at banks are responding to the challenge these companies have started by setting their own incubators up to capture this high-speed initiation.

Technology was once centralised, with companies being run on big databases and transaction engines. Nowadays, it is massively distributed. New businesses have sprung up to take advantage of the chances this shift brings, while leading banks still operate using the old technology. The term “peer to peer” captures some of the phenomenon, in that it is now potential for financial transactions to take place on a platform without needing a bank or indeed any entity as an intermediary.

The financial services marketplace is all about information exchange that is reliable, secure and efficient. In many cases the new alternatives can be cheaper and quicker than traditional models. A broad variety of potential models exist, which explains the increasing number of new fintech startups that have entered the market.

Needless to say, fintech is not new and technology has consistently brought gains to consumers. Back in the day, however, development costs were high, while the technologies of today are more broadly available, affordable and, most importantly, worldwide scalable.

The huge banks are setting up their own initiation arms to investigate opportunities presented not only mobile but also by by P2P and micro-payments cryptocurrencies like Bitcoin,, and distributed ledgers for example blockchain.

But as progressive as traditional financial institutions strive to be, they will remain hampered by their legacy systems and processes. I see the banking landscape continuing to change quickly as fintech businesses with talented management, viable products and clever advertising using new and traditional media take market share. Moving fast, nimbly and economically to capitalise on opportunities is the key.

Artificial intelligence in FinTech

Since its inception in the 1950s, artificial intelligence (AI) has found at least two major boom cycles and long winters of disillusionment. While artificial intelligence endured through the recent disullusionment cycle in the 1990s to today, its easing and corollary technologies have flourished, and we’re now entering into a fresh boom in applictions of the technology.

Financial services have been revolutioned by the computational arms race of the last twenty-plus years, as technologies like big data analytics, expert systems, neural networks, evolutionary algorithms, machine learning and more have enabled computers to crunch much more varied, diverse, and deep data sets than ever before.

While most of the businesses built around machines making decisions are’t true AI, they may be using data-intensive technologies that will help technologies and firms continue to get closer to executing AI in commercial applications.

Despite the hype of intelligent machines, the first uses of AI are’t replacing humans and human intelligence but augmenting them. Text-based conversational chat was adopted by many startups as a way to deliver a personal assistant-like expertise in many industries, and in fintech we’ve seen the case of businesses like Kasisto utilising AI to scale the impact of people using technology. Instead of being bounded in customer support uses by humans reacting to users through chat windows, AI and related technologies are being implemented to deliver a human-like chat encounter without the need for nearly as many human helpers.

By using smart agents that can examine and crunch data about individual behaviour and compare to broader datasets, small and big businesses could have the ability to deliver personalized financial services as a scope and scale never possible before. Consumer banking, advisory services, retail financial planning, investment advice and wealth management, all of these services can be delivered using a conversational user interface with artifical intelligence software behind. The combination of technologies can empower firms to supply services to customers where they were unable to supply human service profitably (i.e. lower net worth sections of personal financial, investment and retirement advisory), but can now function using codified knowledge and AI-powered software.

In addition to new segments, they are able to be more personal, supplying guidance at the transactional level (i.e. every individual transaction). This is the story behind smart wallets like Wallet.ai. Picture having an assistant with you to allow you to assess, price, and consider every single thing you spend money on, at a granular level that you could not be assisted by any human helper with. Is a roboadvisor that offers rule based advice using only a couple of predefined parameters AI? Likely not, but newer technologies as time goes by which are based around learning and viewing about your behaviors at the individual level, could give guidance and outcomes which might be personalized in a way never possible formerly.

AI can also power technologies that overlay humans to supply workers activities with an tracking and oversight mechanism, helping with compliance, security, and the observation of employee actions. Monitoring discrete, repetitive data entry tasks, computers could watch and learn as time passes to verify test and data entry for particular events, evaluate danger, and find fraud. Any segment of fintech that is regulated creates the chance for companies to install AI-powered employee and systems supervision.

AI technologies that allow computers to process information could augment underwriting and lending products and make decisions more easy and better than individuals alone. While it’s still to be determined how new data sets created by technologies like wearables and internet of things can be used for insurance and credit decisions, AI-based technologies make it more potential for businesses to use these new datasets in highly personal ways .

But AI is creating bigger opportunities to go beyond testing and fitting data to create trading systems and more “intelligent ” dealers, using robotraders to optimize and test predictions and trading rules. AI can help manage and augment rules and trading decisions, helping process the data and creating the algorithms managing trading rules.

Some investment firms have implemented trading algorithms based on sentiment and insights from social media and other public data sources for years, but technology companies like Dataminr are installing platforms for a larger set of businesses to use. Getting and utilizing large, heterogenous datasets is now potential for far more companies to use, so how will companies leverage and build on top of these datasets?

The future of AI in FinTech

While much of the investment in artificial intelligence has been into multi-purpose platforms which are figuring out their specific, high-value usecases, the chance in fintech is somewhat different. Fintech has a base of technological prowess in the technologies supporting AI and several immediate high value uses.

Initially, AI was used more in backend technology settings to power large scale decisioning in financial analysis , trading and lending, but now it is becoming a technology that expands how everybody interacts with financial services companies. A number of problems consumers are facing when using financial services are around the problems in getting to quality, personal service. And possibly it’s an artificially intelligent agent that helps deliver cheaper, private services that are better and faster.

Empirica with lecture at ‘Algorithmic Trading Conference’

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Conference on the subject of ‘Algorithmic Trading’ was held at Warsaw Stock Exchange headquarters on the 28th of February 2013. The event was open by the WSE president, Adam Maciejewski. Among the invited guests were:

  • Peter Van Kleef, Lakeview Capital president
  • Michal Rozanski, CEO of Empirica
  • Andrzej Endler, CEO of M10
  • Michal Kobza, Warsaw Stock Exchange.

Michal Rozanski from Empirica made lecture on topic ‘Tools supporting financial institutions in algorithmic trading’. He showed not only common functionalities and architectures of available solutions, but also talked about practical aspects of hard decision every financial institution faces – to build software tools by own IT department or to buy from external vendors.

Very interesting was lecture held by Peter Van Kleef. Among other topics he shared his experiences from high frequency trading and how it has changed during last years.

We have informations that organizators intend to prepare soon another event relating to topic of algorithmic trading.

Link: GPW conference

Why Robo?

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Why Robo?

With the advent of Automated Digital Wealth Management options (aka robo advisers), the conventional wealth management industry is facing perhaps its most tumultuous threat since low-cost online stock trading emerged in the mid 1990’s

  • The Millennial generation’s predisposition to “do-it-yourselfthrough-an-app”
  • Availability of highly credible digital wealth management options
  • Providing scalable advice
  • Suffering in the comparative shift in appetite towards ETFs the mutual fund business, and other passive investment vehicles in particular seems farther threatened since most of the solution providers by digital wealth management solutions use ETFs as their underlying investment vehicles
  • At the absolute minimum, all wealth supervisors should be highly focused on “digitizing” their businesses as consumers of all ages and demographics will expect an “Amazon and Uber – from all of their financial service providers like expertise that is ”
  • Fintech disruption in all areas of finance and investments (online banking, big data, AI, sentiment analysis)
  • New consumer brands are appearing in the digital wealth management sector (such as Betterment, Wealthfront and Personal Capital) while conventional companies are striking back by either offering their own in house options (including Charles Schwab and Vanguard) or partnering or getting to speed time to market

EXECUTIVE OVERVIEW

As a wealth advisory service, robo-advisors have already been growing in popularity for recent years. Low minimums, low fees and the guarantee of sound yields, attract new investors, particularly millennials.
Now while this kind of service created considerable asset increase at first, that increase has leveled off. Although the usage of robo-advisors continues, a tendency that is more comprehensive is replacing the service, with financial advisors using computer programs to help them in managing customer accounts and offering investment advice.
There stays a comparatively small section of investors for whom robo-advice and most of the demands can match with.
The truth is, the popularity of robo-advisers, and the lessons learned from their execution, point to online brokerages, a fresh manner advisors and other financial institutions can do business. These investment and advice suppliers obtain or can construct a platform offering much more than just advice that is digital. It can rather power an environment where a personalized investment software is successfully provided through call center, advisors and digital stations, determined by the route that is best, together with client setting.
Call it an automated advice platform—a package of applications that can direct investment choices and more, from tax-loss harvesting and rebalancing to predictive analytics and data mining, helping the adviser and business socialize with the customer through the route that is most suitable. This type of system drives cost savings and efficiencies, together with an increased customer experience.
You’ll find choices and many variables that businesses should consider when planning and installing these systems.

THE DAWN OF AUTOMATED advice

The financial advisory business was limited and included much more manual task by now’s standards, in and to whom.
advice delivery was ineffective and slow, along with exclusive (largely limited to rich or well-off investors). Eventually, it was not difficult for fiscal preparation to become disconnected from your real execution of the investment advice.
When technology increased rate and consumers needed immediate info delivered at their convenience and increased transparency these shortcomings became clear. Many financial advisors, working with insufficient and ageing applications, cannot fulfill with those requirements.

Robo-advisors arrive

Robo- prejudices that are behavioral could be eliminated by advisors and manage regular account maintenance while conserving prices—so the pitch went.
Some of the early robo-advisors came like Betterment and Wealthfront from pure play robo companies. Well-recognized product producers like Vanguard, BlackRock and Schwab got into the space, also. Conventional advisory companies, also as independent broker dealers and custodians, embraced automated investment technologies, looking to attract younger customers (nearly 40% of millennials are thinking about robo-advice) and smaller accounts, together with maintain their peers. Still nowadays, we see niche-oriented robo-companies like WorthFM coming to market, as businesses that are other add artificial intelligence with their platforms.
By investing in a automated platform that is advisory, companies can construct and power an omni-station surroundings—one where advice that is customized is delivered through digital versions, call center and adviser.

Robo-advisors:

Growth rates have dropped, and average earnings per robo-advisors customer is decreasing, which doesn’t bode well for his or her long term prognosis.
If the portfolio is simply an apportionment of various ETFs that are passive, then it’s not more expensive to buy through a self directed account.
The robo-adviser also leaves no selection —once the asset allocation is discovered, it’s impossible to change investments. Other criticisms of pure robo-advisors are that they’ve yet to work during a long bear market or downturn (remaining invested is essential to the investing theory), and it’s not clear how they’ll manage occasions like post-retirement drawdowns. And, while many younger investors are wonderful with fiscal advice that is only digital, many others aren’t. Additionally, many facets of the fiscal advice relationship continue to demand human intervention, like tax strategies and estate planning.
Many of the notions that drove the adoption of robo-advisers in the first place stay sound, and advisers and companies have a prime chance to employ robo-advisory technology more generally across practices and their company. Really, robo- alternatives that are advisory will continue to develop to address these shortcomings, placing pressure that is on-going on advisory businesses that are conventional. By investing within an platform that is advisory that is automated, companies can construct and power an omni-station surroundings—one where advice that is customized is delivered through call center, advisors and digital versions.

By investing in a platform that is advisory that is automated, companies can assemble and power an omni-station surroundings—one where advice that is customized is delivered through digital versions, call center and adviser.
In this hyper-linked information age, a large proportion of investors, no matter account size want professional advice. The fiscal advisory businesses that can best provide this advice—in a sense which is still rewarding to the business, and in the quantity, frequency and format the customer needs —will function as ones that prosper and live. There are lots of newer “tumultuous” suppliers which are using innovative methods to deliver this advice that is professional, such as call centre and the only on-line -based advisory business Personal Capital. This places those conventional advisory companies that manage to completely comprehend their present and prospective customers at a clear edge and to develop their abilities. Companies must have the capacity to serve customers in just how they need. Technology is critical to provide the customer experience that is appropriate, fulfilling the customer’s needs consistently and economically. But, the real innovators are the ones that will push on their technology -advisory. With the proper preparation, they are able to set up an all-inclusive advice platform that is automated.

Advantages of an automated platform that is advisory

Companies which make an investment in applications and the hardware that enable an automated platform to run with omni-station advice stand to reap tremendous gains. Possibly the most noticeable is client satisfaction; customers who are receiving advice through their favorite channel and at their favorite frequency are substantially more likely to be met with the service they’re receiving and, therefore, are more likely to remain with advisors and the company. An automated advisory platform’s first job will be to identify customer needs and vector those customers into the advice delivery channel that is proper. But, that can not go considerably deeper than the platform. advisors can also use data mining to help them comprehend a customer’s obligations and total assets, much more precisely than before. The sophisticated platforms with artificial intelligence can examine behavioral profile is ’sed by a customer and call possible attrition and life events, then propose methods for the advisors to manage such occasions. The platform may have the capacity to identify possible areas for new product development centered on tasks and customer needs. The real innovators are the ones that will push on their technology -advisory. With the proper preparation, they are able to set up an all-inclusive advice platform that is automated.

Raising price efficiencies

Advisory platforms that are automated enable advisers and companies to be cost efficient in performance and their advice delivery, helping keep gains if fee income declines.

There are, needless to say, upfront prices to add applications and hardware, but automated platforms that are advisory enable advisers and companies to be more cost efficient in performance and their advice delivery, helping keep gains if fee income declines. These platforms also enable adviser and the company serve more customers of every size and kind and to scale up operations.
Past robo-advisory, technology may be a tremendous support in regards to routine account tasks, many of which are never seen by customers.
Likewise, regular coverage—quarterly, annual or as frequently as the customer needs—can be readily automated too.
Eventually, aside from the station, each interaction will be recorded by the finest automated platforms, together with any customer comments, both for to improve future interactions and regulatory functions.
Best interests: The Department of Labor’s fiduciary rule Regulations that are new are about to get stricter, especially in regards to advice on other retirement accounts and IRAs. Additionally, it sets strict rules on advisers becoming paid through commission.
With present adviser practices, the new rule WOn’t probably allow it to be rewarding for advisers to service accounts that are smaller. Nevertheless, technology— especially applications leveraging robo-adviser strategies—can empower companies to service these accounts that are smaller while still fulfilling with the fiduciary rule’s no- best-interest and commission mandates.
The fiduciary rule is more extensive than that, nevertheless, and technology will be critical to fulfilling with all its precepts. Any advice that’s given to some retirement customer must take the customer’s best interest, irrespective of how little or large the customer and no matter what station that advice is delivered through.
The appropriate technology can ensure that occurs, ensuring an adviser or an algorithm doesn’t advocate the investment merchandise that is incorrect, for instance, and making certain the advice is consistent across all stations. Technology also will keep an eye on what advice is given it is simple to demonstrate to regulators that the performance of that advice and the advice were in the customer’s best interest.
Advisory platforms that are automated enable advisers and companies to be cost efficient in performance and their advice delivery, helping keep gains if fee income declines.
CHOOSING AND APPLYING AN AUTOMATED ADVISORY PLATFORM

The best automated advisory platform will do much more than simply offer investment merchandise suggestions and rebalancing and tax- lost harvest

While the notion of a robo-adviser is not useless, the current use of the technology does not go far enough. This creates an opportunity for forward-thinking financial institutions and advisers reap benefits and to expand the notion significantly, including cementing long-lasting and rewarding client relationships.

The greatest automated advisory platform will do much more than just offer rebalancing and investment merchandise ideas and tax-loss harvesting. The platform also must be incorporated with client relationship management (CRM) programs, so that the adviser can get up to the minute info on an account, regardless of that customer’s main advice delivery channel.

Many of these items can be handled digitally. Others will need call center advice as well as face-to-face meetings between customer and the advisor. Pivoting between channels completely understands each client’s settings and WOn’t be an issue for the company or advisors that has put in place the technology that is correct.

The finest automated advisory platform will do far more than just offer investment product suggestions and rebalancing and tax-lost harvest.

Six steps for delivering automated advisory To construct and produce this vision of a robust, technologyenabled platform, it’s essential the platform be thought out before any changes are made. We have identified six important steps that any automated advisory platform must support while particular functions will differ depending on a firm’s own settings, capabilities, client roster and plans for growth.

Step one – Client vectoring: This critical first step involves getting to know new clients, their assets and their investment aims, and then slotting them into the proper investment and servicing software. Clients can be sifted into groups for example mass market, mass affluent and high net worth, and the platform can devise investment plans for each class (e.g., UMAs for the rich and wrapping accounts for mass market investors) and based on how each client will probably prefer to be served. This assessment must be nimble enough to account for personal tastes.

Measure two – Preparation and product selection: This is the phase that perhaps most resembles now’s robo-adviser. Using information collected through questionnaires and other customer interactions, the algorithm advocates underlying securities which might be suitable to each customer and an asset allocation. The difference is the platform can also help train the client on these options—via online or call center, for example—and may also make adjustments to the recommendations based on how complicated each client’s portfolio and individual financial situation is.

Step three – Implementation: The application or the financial advisor subsequently clarifies the rationale behind the proposed investment program and makes any corrections predicated on client interaction.

Step four – Monitoring: After the automated advisory platform makes an investment, the algorithms continuously track how that investment is performing. The action could be as easy as monitoring rebalancing and drift as needed. The activity also could be more sophisticated, for example tax-loss harvesting, transaction cost optimization, or flagging an issue for additional actions by adviser or the call center.

Step five – Performance and servicing: Here we see the complete advantages of the omni-channel servicing version that an automated platform that is advisory supports. How account statements, investment reports, funding requests and other regular customer messages are best delivered depends on customer setting and adviser commitments, also as on the content of the communications themselves.

Measure six – Event-driven reinvention: Client scenarios continuously change (e.g., new job, inheritance, health complications, retirement). These life events may necessitate significant changes. Many will demand the intervention of a human adviser, although a few of these changes can be managed automatically by the platform. The platform and advisors, working in tandem, can come up with the best solution, such as a brand new investment product, changing to a new service station, or going into an UMA or UMH.

Concerns when choosing provider and a platform

Transforming a current IT system can be expensive, complex and uncertain, but this is offset by the many clear advantages of transitioning to an automated advisory strategy. Questions to consider when looking to purchase and deploy an automated advice platform comprise the following:

• What attributes does the platform The platform also needs to work within a business’s present IT infrastructure, or the business will have to upgrade its systems. Likewise, can the new platform integrate readily with a firm’s present software and with the workflow that’s already in place among its advisers, call center representatives and other professionals?

Scalable have to be addressed? Are there gaps in a firm’s existing data collection systems? Is the company’s online security robust and up up to now? The type of upgrades or changes will be needed to advisers ’ backgrounds and dashboards? What about the call center?

• What are the integration challenges? offer? As we’ve seen, there is certainly a broad range of attributes that are possible a platform will offer. Companies will want to decide how complicated and thorough they desire their first platform to be. In addition they will want to make certain it can be expanded to feature new products and services without an excessive amount of trouble as the business’s needs change.

• What other challenges is the platform? As the company’s novel of business grows firms must ensure the platform can grow with regards to the variety of advisors and clients it can support.

JUDGMENT

It must not be a question of “if” but instead “when” a company will set up an automated advisory platform. The future of the financial advisory industry will tend heavily on technology, and those companies that lag behind are bound to miss out on the advantages to advisors, customers and the firm overall.

Top companies will put in place platforms that consider the needs of advisors and clients, ensuring that advisers develop a strong instrument that helps them serve their clients more economically and effectively. The robo-adviser tendencies in recent years gave rise to fears that technology would casts aside advisors. But, it is now clear that advisers are as important as ever. An automated advisory platform can augment advisers’ expertise, ensuring that customers receive the best advice—no matter what channel they prefer.

Apache Spark Software Development FinTech

Apache Spark – fast big data processing

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Businesses are using Hadoop widely to analyze their data sets. The reason is that Hadoop framework is founded on a straightforward programming model (MapReduce) and it enables a computing solution that is scalable, flexible, fault-tolerant and economical. Here, the main issue would be to keep speed in waiting time to run the program and processing large datasets in terms of waiting time between queries.
Apache Software Foundation for speeding up the Hadoop computational computing software process introduced Spark.
As against a standard idea, Spark is not a modified version of Hadoop and is not, really, dependent on Hadoop because it’s its own cluster direction. Hadoop is only one of the methods to implement Spark.
Spark uses Hadoop in two ways – one is second and storage . It uses Hadoop for storage function only since Spark has its own cluster direction computation.

Apache Spark

Apache Spark is a lightning-quick cluster computing technology, designed for fast computation. It’s based on Hadoop MapReduce and it expands it to be economically used by the MapReduce version for more types of computations, including interactive queries and stream processing. The principal feature of Spark is its in-memory cluster computing that increases the processing speed of an application.

 

Spark was created to cover a wide variety of workloads such as streaming, iterative algorithms, interactive queries and batch applications. It reduces the management burden of maintaining different tools, besides supporting all these workload in a specific system.

Evolution of Apache Spark

Spark is one of Hadoop’s sub project developed in 2009 in UC Berkeley’s AMPLab by Matei Zaharia. It was Open Sourced in 2010 under a BSD license. It was given to Apache software foundation in 2013, and Apache Spark has become a top level Apache project from Feb-2014.

 

Characteristics of Apache Spark

Apache Spark has following attributes.

 

Speed − Spark helps to run an application in Hadoop cluster, 10 times faster when running on disc, and up to 100 times faster in memory. This is possible by reducing amount of read/write operations to disk. It stores the intermediate processing data in memory.

 

Supports multiple languages − Spark provides built in APIs in Java, Scala, or Python. Consequently can write applications in distinct languages. Spark comes up with 80 high level operators for interactive querying.

 

Advanced Analytics − Spark supports ‘Map’ and ‘ reduce’. Additionally, it supports SQL queries, Streaming information, Machine learning (ML), and Graph algorithms.

Spark Assembled on Hadoop

The following diagram shows three ways of how Spark can be assembled with Hadoop parts.

 

Ignite Constructed on Hadoop

There are three manners of Spark installation as described below.

 

Standalone − Spark Standalone deployment means Spark inhabits the place on top of HDFS(Hadoop Distributed File System) and space is allocated for HDFS, explicitly. Here, MapReduce and Spark will run side by side to cover all spark occupations on bunch.

 

Hadoop Yarn − Hadoop Yarn deployment means, only, spark runs with no pre-installation or root access needed on Yarn. It helps to integrate Spark into Hadoop stack or Hadoop ecosystem. It enables other components to run in addition to stack.

 

Spark in MapReduce (SIMR) − Spark in MapReduce is used to launch spark occupation in addition to standalone deployment. With SIMR, Spark can be started by user and uses its shell with no administrative access.

Parts of Spark

Apache Spark Software Development FinTech

Apache Spark Core

Spark Core is the inherent general execution engine for Spark platform that all other functionality is built upon. It provides In-Memory computing and referencing datasets in external storage systems.

 

Spark SQL

Spark SQL is a part in addition to Spark Core that introduces a new data abstraction called SchemaRDD, which provides support for structured and semi-structured data.

 

Start Streaming

Spark Streaming leverages Spark Core’s fast scheduling capability to perform streaming analytics. It ingests info in mini-batches and performs RDD (Bouncy Distributed Datasets) transformations on those mini-batches of data.

 

MLlib (Machine Learning Library)

MLlib is a distributed machine learning framework above Spark due to the distributed memory-based Spark design. It is, according to benchmarks, done by the MLlib developers against the Alternating Least Squares (ALS) enactments. Spark MLlib is nine times as rapid as the Hadoop disk-based version of Apache Mahout (before Mahout gained a Spark interface).

 

GraphX

GraphX is a distributed graph-processing framework in addition to Spark. It supplies an API for expressing graph computation that can model the user- . Additionally, it provides an optimized runtime for this abstraction.

 

Spark vs Hadoop

 

Listen in on any conversation about big data, and you’ll probably hear mention of Hadoop or Apache Spark. Here is a brief look at what they do and how they compare.

 

1. They do different things. Hadoop and Apache Spark are both big-data frameworks, but they don’t actually serve the same functions. Hadoop is basically a distributed information infrastructure: It doles out huge data collections across multiple nodes within a cluster of commodity servers, which means you do not need to buy and keep expensive custom hardware. In addition, it indexes and keeps track of that info, empowering big-data analytics and processing far more effectively than was possible previously. Spark, on the other hand, is a data-processing tool that operates on those distributed data collections; it doesn’t do distributed storage.

 

2.  You can use one without the other. Hadoop includes not only a storage part, referred to as the Hadoop Distributed File System, so you don’t need Spark to get your processing, but also a processing part called MapReduce. Conversely, you can even use Spark without Hadoop. Spark does not come with its own file management system, though, so it must be integrated with one — if not HDFS, afterward another cloud-based info platform. Spark was designed for Hadoop, however, so many agree they’re better collectively.

 

3. Spark is quicker. Spark is usually a lot quicker than MapReduce because of the way it processes data. Spark functions on the entire data set in one fell swoop while MapReduce operates in measures. “The MapReduce workflow looks like this: read information from the cluster, perform an operation, write results to the cluster, read updated information from the cluster, perform next operation, write next results to the bunch, etc.,” explained Kirk Borne, principal info scientist at Booz Allen Hamilton. Spark, on the other hand, finishes the full data analytics operations in-memory and in near real time: “Read information from the bunch, perform all the necessary analytic operations, write results to the cluster, done,” Borne said. Spark can be as much as 10 times quicker than MapReduce for batch processing and up to 100 times quicker for in-memory analytics, he said.

 

 

4. You may not need Spark’s speed. MapReduce’s processing fashion can be just fine if your data operations and reporting conditions are mostly static and you’ll be able to wait for batch-mode processing. But if you must do analytics on streaming data, like from detectors on a factory floor, or have applications that need multiple operations, you probably want to go with Spark. Most machine learning algorithms, by way of example, need multiple procedures. Common uses for Spark contain real-time marketing campaigns, product recommendations that are online, cybersecurity analytics and machine log monitoring.