Artificial Intelligence

What is Explainable Artificial Intelligence (AI) or XAI ?

As time and learning progressed, consequently IV Generation Industrial Revolution changed the way we live, work, and relate to one another. Artificial Intelligence (AI), Blockchain, Deep Learning, Machine Language, and IoT came up spreading their wings and making enterprises and companies fly with infinite horizons.

Yes, AI systems like Machine Learning and Deep Learning indeed take inputs, with no decipherable explanation or context. The AI system makes a decision and we don’t know how and why the system has arrived at that decision. This is the Blackbox model of AI which is deeply mysterious.

Explainable Artificial Intelligence (AI) meaning

Explainable AI, as the name suggests, can be, explained and understood by human brains. The outcome of Explainable AI is more reliable & trustworthy.

Simply speaking, Explainable AI is transparent in its operations so that human users can understand and trust decisions. It makes decisions cheaper, better, and faster. The goal of Explainable AI is to help people to be more productive and arrive at decisions that are reasonable and understandable. In other words, people should have an idea of why and how they are making those decisions.

Making the Blackbox of Artificial Intelligence (AI) transparent

Most of the owners, operators, users, companies, enterprises, and organizations need answers to their questions like: Why did the AI system make a specific prediction? Why did not the AI system do something else? Why should we follow the decision of AI? Is the output of AI error-free?

So, far, there is only early, seed research and work in the area of making Deep Learning approaches to Machine Learning explainable. However, it is hoped that sufficient progress can be made to arrive at the required transparency and Explainability.

According to Priti Padhy, CEO and Founder of Cognino, “I will call for a “third wave” of AI, which can adapt to novel situations and, importantly, explain its decisions. It's no longer acceptable to just say "we don't know how it works." If the future is going to run on neural networks, we need to understand them now !” He emphasizes making existing AI systems transparent and explainable.

AI is an inspiring gift to mankind with new outcomes. But with the surprises comes the concern of trust. Explainable AI deals with this trust issue making the output explainable with insights. The dark black box of conventional AI systems is thus unboxed and decisions, outcomes, and predictions are made with a reasoning.

The black box of AI systems is converted into a Glass-Box by Explainable AI models. The lack of understanding of predictions made can cause large risks for companies. No matter how genius you are but if you are not able to explain to a third party how and why are you getting those wonderful predictions, then you might lose your reputation and left with nothing at all.

Explainable AI in Medicine

In fields such as Healthcare and Medicine, mistakes can have catastrophic effects, therefore the black box concept of AI makes it difficult for medical practitioners to trust the outcomes. If an AI algorithm is not trained properly, we cannot be sure that the patients will be diagnosed properly or not. Thus, xAI algorithms that are being developed for Healthcare and Medicine can provide an explanation and justification for their results.

Using advanced Natural Language Processing, Explainable AI can extract and relate some important and critical information from the previous records of the patients, giving doctors a faster approach to reach the patient’s Electronic Health Record.

One of the most important reasons for bringing Explainable AI to medicine is because the medical practitioners are working with complex, heterogeneous, complicated, and disturbed data. Therefore Explainable AI is a boon to the medical fraternity that not only organizes the unstructured data but also come out with predictions that can be explained and understood.

Explainable AI in Finance

Finance is another field that is graved with a lot of paperwork in the form of documents that are unstructured and complex, thereby making their work full of risk and uncertainty. Explainable AI comes in picture in Financial Services and Compliance by providing a directional approach to the consultants and clientele.

Explainable AI can spread its wings in Banking and Finance and extend its hands in the following departments, namely,

  • Know Your Customer (KYC)
  • AML/Fraud Management
  • Rogue Employee Detection
  • Internal Audit Compliance
  • Tax and Accounting Compliance

AI detects and correlated anomalies and forecasts compliance, threat, and performance in no real-time.

Explainable Ai in Public Sector

Artificial Intelligence has transformed several areas in the private sector, now it has started blanketing the public sector as well. Governments of all countries are always under pressure to create an efficient and effective system of citizen services.

There are various categories in this sector, and we can summarise it as:

  • Smart cities and spaces
  • Citizen services
  • Employee engagement

Explainable AI in Education

Educationalists need methods and modern techniques of AI to connect students all over the world and help them realize their potential. Challenges in the education field can be paved through solutions provided by Explainable AI.

Students, teachers, and administrators can utilize Explainable AI to enhance and improve their learning graph with improved outcomes and predictions.

AI tools like real-time language translation can overcome all language barriers and help them learn and grow. Narration of surroundings for blind students enable them to know the insights of any field.

Explainable AI in Retail Industry

The retail industry is one of the most growing concerns with increasing expectations and personalized requirements. This sector is deeply intent-driven and needs an understanding of customer needs, wants, influences and relationships.

Retailers should think more about structuring the data through a glass-box of Explainable AI. It provides a window of “why and how” of an outcome. There are also performance metrics and can track a particular output. Think of AI as another worker. All the risks involved in a business are minimized thereby, increasing revenue and customer retention.

Summary

Explainable Artificial Intelligence (AI) or Xai is an Intelligent Core Platform that makes predictions, outcomes, and decisions understandable and explainable to humans. Actions of AI are traceable to a certain level. These levels depend upon the complexity and sensitivity of consequences that may arise from an AI system. Thus, Explainable and transparent system of AI should “know everything when anything goes wrong”.

Deep down, AI has become an important and substantial part of our lives, Explainable AI has become even more important.


Digital "Inter-preneur" Intern

Reimagine business with Artificial Intelligence

 

Cognino - We enable organisations to leapfrog into the future with the help of Artificial Intelligence (AI) and with the world’s first explainable AI.

 

Cognino is a research led Artificial Intelligence organisation, working with cutting-edge AI technology and world class data . We are currently creating solutions and solving real world problems across various use cases such as Enterprise Insight, Early Warning System, Risk, Fraud, Compliance across industries like Financial services, Healthcare, Government, Regulators etc.

 

We are lean, global, young and a very dynamic company that has bold ambitions to democratize AI.

 

Our values are simple but core to our belief system:

 

  • Focused – We only exist to help customers transform into new AI era
  • Innovation – We are open, curious and always learning
  • Respect – We recognise everyone is different
  • Strategic – We believe in strategic and long-term views
  • Integrity – We are honest, accountable and trustworthy

 

We are looking for a Digital "Inter-preneur" Intern

Do you want to learn about the possibility of Artificial Intelligence and how AI will change the world? Come and join Cognino. We are looking for extra-ordinary talent, who is hungry to learn, innovate, work with integrity and loves to have real fun.

 

About yourself:

You must have a clear reason for why you want to work with an AI first business such as Cognino other than to get out of a predictable corporate internship, brag to your friends about the cool start-up you now work with, or simply place entrepreneurship on your CV. Some of us have an uncanny “need” and “eccentricity” to want to change the world, lead from the front, challenge the status quo even if it came with difficulties and pain. Only reach out to us if you think you are the latter.

 

You Love:

You must love Digital Medium and believe that Technology like Artificial Intelligence can change the world. You really like learning new things, aren’t scared of researching market and data. You may want to build your own business and want to learn and own the end-to-end process. You have a natural talent to see big picture while solve any problem thrown at you.

Regardless of background, we believe there exist individuals with entrepreneurial spirits, resilience, and an outcome driven attitude, who with the right coaching and mentoring can achieve the near impossible. We expect intern-preneurs at Cognino to approach his or her career like an entrepreneur: able and eager to get things done and willing to innovate with limited resources. They think ahead and want to learn how companies and careers grow. We would especially like to hear from those professionals who are thinking of embarking on a change of career or a simple career break. Some of our top employees have come this route and we would love to have some more! Sound like you? If yes and you have 20 hours to spare per week to change your life, read on :)

 

Ideal Skills

  • Grit, determination and a never say die attitude;
  • Growth mindset - Love of ideation and storytelling;
  • Knowledge of, and passion for, the power of communication solutions to drive change;
  • A good understanding of business fundamentals. And Technology background can be ideal!

 

Depending upon your skills and experience, responsibility includes:

  • Owning research assignments and digital marketing as a whole
  • Impacting or even leading Operations / Business Development / Sales / Marketing / Finance
  • Assisting the CEO/CPO/CMO in the day to day running of the company
  • Building best practice processes that make us more efficient and effective as a team
  • Leading & developing other interns

 

What can Cognino do for me?

Gain a business education, startup experience, and some pretty amazing connections. If you're not ready to launch your own venture or don't quite know who you want to be professionally, we are a great foundation. Get in on the ground floor of an awesome and innovative company - and have some fun along the way! We equally love working with professionals with prior experience AND students, especially those who are looking fulfil course requirements and gain credits by completing an internship programme. We are also a global team, with guys in London, Brazil, India, USA and may be your own home!! Flexibility is key!

If what you have just read resonates, get in touch with your CV and cover letter explaining your motivations for applying and goals for the internship.

 

Good luck and have a great day!

APPLY NOW


data, artificial intelligence, biddata, python, technologgy

It's time to make All Data Actionable

A “fasten your seatbelts” moment could soon be here. If history is any guide, and depending on the severity of a downturn, large enterprises with weaker balance sheets that have sailed under the radar due to their strong in-year performance could hit the ropes. The current economic climate suggests we are here for a long haul! It's time to make all data actionable.

By contrast, more agile enterprises, who are improving their early warning systems using advanced analytics, creating mechanisms to be able to increase the resilience of their balance sheet may have a better chance to emerge as winners.

Advanced analytics focused on Asset Quality and capital adequacy could prove as valuable guideposts as BFSI enterprises prepare for a turn in profitability.

A closer look at problem loans, loan loss provisions as a percentage of gross loans might play an important role as large and medium-size banks take steps to access their preparedness.

Normally, the approach to problem loans has always been via some mixture of loan workout programs or in worse cases a foreclosure on the underlying collateral.

Loan workout processes during slower economic cycles can take be structured as simple renewal or extension of loan terms, restructuring of loan terms based on simple concessions, or more complex TDRs (Troubled debt restructurings).

A prudent approach in preparing for a downturn will need to focus on developing strategies to:

• Recognize deterioration of credit quality early enough for efficient response.
• Build structures that will signal a decline on time.
• Develop ongoing systems to deal with problem credits as they arise.
• Create an effective plan of action to address troubled situations and maximize recovery.

Banks today have extensive processes and mature capabilities to address some of these issues.

The challenge with these existing processes is that they have not been overhauled to be more efficient with the availability of additional information.

Customers conducting businesses with Banks have expedited the use of information and now process transactions over numerous channels. Some of the new brands for example manage a majority of their transactions via sophisticated online marketplaces while others have dedicated chatbots in place to guide customers.

Does your IT support have processes in place to get a pulse around this new information? Do your early warning systems have the right intelligence to access declining asset qualities and sound an alarm?

Cognino specializes in utilizing explainable AI to augment your existing enterprise analytics. We provide rapid assessment work surrounding critical FISB scenarios and can work hand-in-hand with your existing resources to bring forth impactful insights that will better prepare you in the case of a bad downturn.

Our intelligent CORE platform can easily ingest large volumes of data sets from diverse enterprise systems, monitor social media noise to signal quality of economically impacted customers, provide rapid benchmarking of problem loan metrics with established industry studies, and can help you formulate strategies to mitigate troubled situations and maximize recovery.

Reach out to Cognino.ai and learn how we can augment your core analytics work by pursuing a simple yet sophisticated artificial intelligence strategy to get you prepared and ready to deal better with any potential business outcomes. Let's make our data actionable.


Artificial intelligence, machine learning in finance, machine learning applications in finance, machine learning and reinforcement learning in finance, python, bigdata, machine learning, deep learning, python

Machine Learning in Finance and Insurance Sector

Machine learning or Explainable AI, unlike the conventional AI model, is more likely to predict outcomes with Intelligence, reasoning, and Explainability. The finance sector all over the world is graved with a lot of paper-work, documentation and never-ending government rules and policies.

The presence of AI can be felt everywhere around us, right from the smart speakers to banks who are better able to decide whom to extend a loan to. AI has huge potential to help Financial companies and the Insurance sector make better decisions.

Restructuring the Finance model

The new Physics of Financial Services is Explainable AI. This has restructured the model of the Finance sector by transforming the past building blocks of success into new and better versions which will provide a better process efficiency and will help sustain the cost advantage. Let us summarise and see what these conventional building blocks will be transformed into:

  1. Scale of Assets into Scale of data
  2. Mass production into Tailored Experiences (revenue will be generated from personalized interactions)
  3. Exclusivity of relationships into Optimisation and matching
  4. High switching costs into high retention benefits, and
  5. Dependence of human ingenuity into Value of augmented performance

Though the older model generated revenue but it was always clouded by risks. Now with Explainable AI solutions, success in Financial Services and Insurance sector can be estimated as under:

  1. Companies will no longer require large scale assets for building a successful business, they will require data flow for cost efficiency.
  2. Revenues will not be generated only by standardization of products but it will also depend upon the tailored needs of customers and individual approach.
  3. Exclusive relations will pave under the ability of digitalization to create well-matched connections.
  4. Customers will stay, not because they can walk away, but because their benefits are better there than anywhere else, and
  5. Human and artificial strengths will interplay for better results.

These new building blocks will create an unfamiliar environment that will deliver new kinds of value and reshape operating models.

Use cases of Machine Learning in Finance and Insurance Sector

 The high-end technology of neural networks that make Ai explainable has several use cases in every industry. But here, we will talk about and highlight the most important and commonly applied use cases in the finance and insurance sector.

  1. Know Your Customer (KYC)
  2. AML / Fraud Management
  3. Rogue Employee Detection
  4. Internal Audit Compliance
  5. Tax & Accounting Compliance, and
  6. Compliance Staff Tools

I think we should discuss these use cases in detail

  1. Know Your Customer

Know Your Customer or simply KYC is the process of a business verifying the identity of its clients and assessing their ability. This verification process of the clients also includes the elimination of the potential risks of illegal intentions towards the business relationship.

Explainable AI can play a very significant role in reducing risks of laundering and fraud. Maintaining KYC operations internally leads to :

  • Inefficiencies
  • High cost of ownership

But if we inculcate Explainable AI in KYC documentation, then it will:

  • Improve output quality
  • Increase risk management, and
  • Accelerate counterparty onboarding
  1. AML / Fraud Management

Financial crimes are one of the biggest challenges facing corporations today. It is not defined by geography or type of enterprise. The vast is the complexity of the organization, the more is the threat of financial crime. Financial risk in the banking and insurance sector prevails at every organizational process.

Machine Learning in finance sector here, plays a very crucial role in identifying the underlying threats and risks. Let us have a look :

  • AI can intelligently extract risk-relevant facts from a huge volume of data
  • This makes the process of identifying high-risk clients easier preventing any sort of financial crime, and
  • It can track changes in regulations all over the world
  1. Rogue Employee Detection

Every organization around the world has rogue employees. When we hire employees, we never expect them to go rogue. But the fact of the matter, employees do go rogue. Companies miss many of the impending signs that would help them to prevent the activity.

Explainable AI can very well identify these employees by:

  • continuously monitoring in real-time, the entire employee communications including emails, chat logs, phone recordings, etc.
  • Ai can also track their behavioral patterns
  • Conduct deep contextual analysis.
  • Reducing the risk of document leakage, and
  • Eliminating chances of financial crimes
  1. Internal Audit Compliance

Now, more than ever, the internal audit department is recognized as a key pillar in an organization’s overall governance structure. Unfortunately, past incidents of corporate wrongdoing and, more recently, risk failures have again served to highlight the critical role that internal audit plays and have shone the spotlight squarely on internal audit to step up and deliver on increasing expectations.

By leveraging Machine Learning in Finance sector, an enterprise would be able to achieve:

  • Significant improvements in the quality and effectiveness of their internal audit
  • Automated audit approaches is time-saving for the organization, and
  • Ai systems automatically identify risks, controls, and other key entities within all audit universe documentation.
  1. Tax and Accounting Compliance

Today, organizations are facing increased challenges to handle the ever-changing regulatory landscape and compliance pressure. Functions such as Tax Compliance, Payroll Processing, Consolidation and Financial Accounting demand dedicated time, resources and a high level of

competence.

Tax and Accounting Compliance relies on intensive human capital and is also time-consuming. Companies should adopt an Explainable AI platform to overcome these underlying risks and reduce threats. AI solutions can help the organizations, enterprises, and companies in Tax and Accounting compliance by:

  • Detecting tax computation errors
  • Proposing beneficial tax strategies
  • Enabling dynamic dashboards for sophisticated scenario analysis
  • Automatically categorizing the taxable income into appropriate country-specific tax buckets, and
  • Tax forecasting and reporting
  1. Compliance Staff Tools

Compliance Staff Tools is a new concept that can be structured through the system of Machine Learning in finance sector. AI enables additional support tools for compliance management teams such as:

  • Dynamic dashboards
  • Data visualization tools
  • Case management tools, and
  • Alerting and alert investigation tools

Summary

Role of Explainable AI in the Finance and Insurance sector is far more extensive and massy. Thus, AI helps the organizations in making predictions, outcomes, and decisions which are far more reliable and factual.

The finance and Insurance Sector needs to understand that both the company and AI specialists need to work together to benefit from this upcoming technology which can prove as a boon for them.