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Author: Amy Sariego

Machine learning – all a bit ‘Skynet’?

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Machine learning –
all a bit ‘Skynet’?

Machine Learning – Revolutionizing Financial Risk Analysis and Decision-Making

While the concept of Machine Learning (ML) may conjure up images of a dystopian future where machines have taken over the world, much like Skynet in the Terminator movies, the reality is quite different. While Skynet may have been a malicious and all-powerful AI system, Machine Learning is simply a tool that can help us better understand and leverage data. So, while Skynet may have been the ultimate villain, Machine Learning is more like the trusty sidekick that helps us save the day.

Here’s how ML is rapidly becoming a game-changer in the field of financial risk analysis and decision-making:

The Power of Data

Machine learning enables businesses to gather and analyze data faster, thereby arriving at insights quicker. This is because the software program uses pattern recognition to build automatic analytical models, eliminating the need for human intervention.

Dynamic Fraud Detection

Machine learning algorithms can learn from a customer’s previous transactions and use them to identify patterns of behavior, allowing for dynamic fraud detection. This eliminates the inconvenience of manual validation processes while also increasing fraud detection rates, saving considerable costs.

Huge Cost Savings

According to analysis firm Oakhall, global financial services firms could save $12 billion annually through machine learning fraud management. This underscores the tremendous potential for risk analysis and decision-making with machine learning.

Harnessing Machine Learning for Predictive Analytics

To fully benefit from the predictive analytics power of machine learning, financial institutions need a fast, simple way to connect their machine learning application to their credit and lending decisioning processes.

Machine learning is revolutionizing the financial risk analysis and decision-making process. Its power lies in its ability to gather and analyze data faster, dynamically detect fraud, and save costs. By harnessing its predictive analytics capabilities, businesses can unlock its full potential for risk analysis.

A Geek’s Guide to Machine Learning (AI), Risk Analytics and Decisioning

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IBS Intelligence Podcast – AskIf

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IBS Intelligence Podcast –
AskIf

According to The Rose Review, access to and awareness of funding was highlighted as the number one issue for female entrepreneurs. Women launch businesses with 53% less capital on average than men, are less aware of funding options and less likely to take on debt.

In honor of Women’s Equality Day celebrated on Aug 26th, Samantha Bamers, the Founder and CEO of micro-lending firm Ask Inclusive Finance (AskIf), discusses how far the financial services industry still needs to go to ensure equality and inclusion in lending.

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Loan Origination Software Plays Its Part in Banking’s Digital Transformation

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Loan Origination Software
Plays Its Part in Banking’s Digital Transformation

Loan origination — and, subsequently, loan origination software — is at an interesting intersection right now.

At a less institutional level, peer-to-peer lending is expected to grow at a CAGR of 53% between 2016 and 2020. But as lending technology matures, its impact could reduce profits in American banks by $11 billion per year, or roughly 7%.

This evaporation of margins is not a new problem for banks, though it is one that is increasingly disconcerting. In 2012, for example, the share of risk and compliance within general banking costs was 10%, a large portion of overall costs as they were. In 2017, risk and compliance are expected to consume 15% or greater. While costs are rising, it’s hard to actually mitigate risk with incremental risk management improvements. In large part, return on equity in banking often resides below the cost of capital, impacted by capital building projects and fines.

The result: to see increased growth into the next decade, banks are digitizing more processes. This has begun to happen, but a variety of studies — including many on millennial bankers — shows the digital transformation of financial services has not yet fully arrived. Since lending is a huge revenue source for banks across virtually all segments from small business to enterprise, making sure digital loan origination is properly executed is preeminent for many banks now.

As McKinsey has noted, the shift to increased digital transformation focus in financial services came about because of five distinct pressures (paraphrasing here):

  • Changing customer expectations: Consider the rise of mobile and on-demand experiences.
  • More regulations and risk-function effectiveness: Seen in increased regulations in most first-world economies, as well as more fines being dealt since the 2008 crisis.
  • Data management and advanced analytics are hallmarks of competitive banks now: Buzzword or not, we are living in a Big Data era.
  • Disruption: Risk management programs are essential for banks to compete with upstarts — if the upstart makes a big bet and misses, the established bank can favorably reposition.
  • Increasing pressure on costs/returns: And as noted above, risk management doesn’t necessarily deliver in this way on the balance sheet.

As such, rapid-fire, on-demand loan origination programs and software have begun cropping up in the financial services world. Why? When risk decisions are made in seconds, loan origination cycles shorten for the customer. Shorter cycles create positive customer experiences, brand loyalty, connection to the bank and its relationship managers, and continued business. Speed can be good.

But, banks attempting a new approach to loan origination need more than speed. While quick risk decisioning and credit scoring is crucial, a loan origination software program also needs:

  • The ability to process both structured and unstructured data: This would allow for the incorporation of both standard and alternative decisioning, i.e. credit documents vs. items from a loan applicant’s blog.
  • Compliance: Perhaps the most important at the bank level, compliance calculation and True in Lending Act (TILA) disclosures need to be compliant, and documents must be in compliance with the Electronic Fund Transfer Act.
  • “Look for initiatives within easy technological reach:” That’s advice from McKinsey above, and it makes good sense. Some loan origination software barely requires advanced coding anymore, so your IT side can work on more value-add internal projects.

There are other considerations such as ease to operationalize risk models that should be deployed.

Financial services, and especially loan origination have long suffered from a lack of transparency and simplicity. It oftentimes seemed that financial services firms were underserved by technology, or “square-peg/round-holing” the problem. That’s not the case anymore, and loan origination software and approaches are of huge value for established banks as a way to drive a growth culture forward. The crucial step is the right partner for your specific needs.


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Loan Origination in the Golden Age of Instant Everything

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Loan Origination in the Golden Age
of Instant Everything

It may look like the golden age of “instant.” The casual iPhone user can get an Egg McMuffin delivered to their door while it’s still steam-hot in the bag. The average Twitter user can use their ampersand key to swat through a brand’s customer service obstacles like Arnold Schwarzenegger cutting through the jungle in Predator. It may look like we’re in the golden age of immediate-results technology, but we’ve only just reached the earliest, primordial stages in its existence, and consumers have already and instantly adjusted to the instant  age.

As the world of apps grows, consumers have, and will, expect every corner of our daily lives, especially the institutions that manage our financial loans or our medical information, to be as cloud-efficient and scalable as the app that schedules an undergrad to walk your dog while you’re in a meeting. Technology tends to evolve inwardly and sensitively, finding it’s way into our banks and homes–not broadly and impersonally. Notwithstanding, loan origination systems are a deeply personal technology.

As a microcosm-example, a 2016 piece in Forbes summarized that brands who engage in direct customer service via Twitter see a 19% increase in customer satisfaction. Loan origination is one of life’s sensitive areas–vulnerable like our medical information or mortgage payments–that needs to adapt to this instant-evolution.

Picture the expectations of instant response when we have an artificially intelligent platform accessible from a contact lens. How long do you think a customer will tolerate waiting for approval or a green “success” check or a loan when all of the technology around us has already reached the speed and accessibility only dreamed up in Ray Kurzweil novels?

Waiting, whether for your breakfast sandwich or your loan decision, is as a dead and dusty a concept as your CD-RWs. Instant technology that learns for the individual and can execute in real time is the present and future. We’re already expecting banking to happen in the blink of an eye. In the future–especially in light of the cascading failures in recent financial technology–it will need to happen even faster, more efficiently, and securely.

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BNPL: Delivering Solutions that Match the Speed of Market Growth

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BNPL:
Delivering Solutions that Match the Speed of Market Growth

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Like a runaway train, Buy Now, Pay Later continues to gather speed in North America. While more providers enter the increasingly attractive (and crowded) market and diversify their offerings, consumers get more and more demanding.

Sixty percent of customers abandon applications for unsecured lending products during digital onboarding, due to slow or complex application processes and a lack of (real or perceived) security. If you’re a BNPL provider, nailing the entire experience is critical.

But how can you get to market faster than the competition, ensure scalability in your product offerings, provide a superior customer experience AND still manage your risk effectively?

They key is in the data and the technology you choose. Hear Kathy Stares, EVP of North America at Provenir, discuss the critical factors to consider when selecting technology partners to grow (or start!) your BNPL business – and how to stay ahead of the competition.

You will learn: 

  • To easily access a variety of data sources (including alternative data) via a single API for a more holistic view of the creditworthiness of your customers
  • Why a unified platform for data, AI and decisioning can help you analyze and action your data (including decisioning performance data, credit risk, fraud and compliance) for flexibility and scalability throughout the entire customer lifecycle
  • How to automate decisioning for real-time approvals and a frictionless customer experience
  • To develop, deploy and adapt sophisticated risk models without heavy reliance on your vendors/partners – getting you to market faster than your competition


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The Fintech Times: What is Holding Back Financial Inclusion?

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Financial inclusion and financial capability continue to be top priorities for global governments and financial services providers. Kim Minor, Senior vice President, Global Marketing for Provenir, shares her perspective on the role data and AI can play in closing the gap to inclusive finance.

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Dow Jones

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Dow Jones Risk & Compliance

Key Benefits

  • Best-in-class structured risk data. Our proprietary risk data provides the structure, speed and flexibility needed to conduct efficient and effective customer and transaction screening for AML, sanctions and other financial crime risks.
  • More secondary identifiers, fewer false positives. Our screening data is enriched with additional identifying details including company and corporate identification numbers, securities identifiers and year of birth, reducing false-positives and the time wasted by your compliance team in investigating them.

About Dow Jones Risk & Compliance

Our proprietary risk data and enhanced due diligence tools provide the structure, speed and flexibility needed to conduct efficient and effective customer and transaction screening for anti-money laundering, sanctions, anti-bribery and corruption and other financial crime risk.

Our content includes sanctions and politically exposed persons (PEPs) details, as well as adverse media, high risk factors and trade compliance data.

About Dow Jones

  • Products

    • Watchlist
    • Adverse Media Entities
    • State-Owned Companies
  • Regions Supported

    Global

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Driving Growth in an Economic Slowdown

ON-DEMAND WEBINAR

Driving Growth
in an Economic Slowdown

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Hear from Provenir and TransUnion Experts

The Canadian economic landscape has changed dramatically this year. Recent increases in inflation and interest rates have driven uncertainty and volatility into the market and fraudsters are growing more and more sophisticated – digital fraud attempts rose a whopping 218% in Canadian financial services from late 2021 to early 2022. On the flip side, unemployment is at its lowest rate in decades and immigration hit an all-time high in 2021, opening up more opportunities to extend credit.

Watch now aas leaders from TransUnion and Provenir share their outlook on the current state of the Canadian economy and discuss how lenders can use data and AI to become more agile in meeting customers’ needs and capitalize on growth opportunities, while efficiently mitigating risks.

Tune in to:

  • Discover strategies needed to quickly react to changing market dynamics
  • Identify opportunities for growth through financial inclusivity
  • Understand how data can be used for growth as well as risk management
  • Learn about new trends in fraud and how to mitigate business exposure

Speakers:

  • Matt Fabian

    Director, Financial Services Research and Consulting, TransUnion Canada

  • Cheryl Woodburn

    Country Manager, Canada, Provenir


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Being Scalable, Robust & People Centric Helps in Building Successful AI Implementation: Varun Bhalla

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In this fireside chat with Bfsinxt.com’s Kailash Shirodkar, Varun Bhalla, Provenir’s Country Manager for India, talks about how fintech players can leverage and improve their risk decisioning capabilities by enhancing their AI and ML capabilities. 

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Your Ticket to Decide – Tackle Risk and Drive Growth

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Your Ticket to Decide –
Tackle Risk and Drive Growth

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In an era of instant-everything, speed is a distinct competitive advantage.

According to PwC, 80% of consumers rank speed as a key buying factor. Whether it’s how fast your customers are able to apply for credit, how quickly you can approve their application, or how soon they get their funds – speed is key. With the rapid pace of digitization and the increase of competition in all forms of financial services, the pressure of consumer demands has never been higher.

How do you balance speed and business growth while maintaining the health of your risk strategy? By ensuring that your decisioning technology can make the most accurate decisions, quickly. In this webinar and live demo, we’ll show you how unified access to AI-powered decisioning and the data that fuels it can help you make smarter decisions, faster, AND help mitigate your risk.

Tune in and hear from Provenir experts how a unified risk decisioning platform offers:

  • Full assessment of risk across identity, fraud and credit
  • Automated, real-time decisioning at onboarding and beyond
  • The ability to scale, diversify and launch new products without fear of compromising your risk strategy


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