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Industry: Data

Data-as-a-Service: The Next Transformation for India’s Financial Institutions

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Data-as-a-Service:
The Next Transformation for India’s Financial Institutions

With India’s analytics market expected to reach INR 11,200.42 billion by 2027, financial institutions in the country will become dependent on more data to speed up innovation, deliver unparalleled customer experiences and build the resilience. 

In this Dataquest article, Varun Bhalla, General Manager, India for Provenir, explains how data marketplaces provide easy access to many types of data, allowing businesses to deliver higher value, eliminate risk and become the disruptor instead of the disrupted.

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Ten Companies Using Alternative Data for the Greater Good

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DaaS: a New Frontier for Credit Decisioning

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DaaS:
a New Frontier for Credit Decisioning

The Manila Times

In this interview with The Manila Times, Bharath Vellore, General Manager, Asia Pacific for Provenir, discussed how Data-as-a-Service cloud software can help the banking and finance industry gain deeper insights on credit risks so financial institutions could better serve the unbanked and improve fraud detection.

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Ten Companies Using Alternative Data for the Greater Good

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Using Data to Redefine Decisioning

ON-DEMAND WEBINAR

Using Data
to Redefine Decisioning

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We are living in a perfect financial storm: Covid has driven consumer engagement online and with increasing inflationary pressure, consumers are looking for both traditional and alternative sources of credit.

In order to meet the rising demand and holistically assess risk, alternative data aggregation and data insights are increasingly being used in innovative ways to help financial institutions decision on their loan book.

From increasing growth and reaching new customers, to preventing fraud while maintaining a frictionless consumer experience, data is changing credit decisioning.

Representatives from leading fintech and bank lenders discuss trends, challenges and opportunities in 2022.


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Welcome Home: The Benefits of Unified Access to AI-Powered Decisioning + Data

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Welcome Home: The Benefits of Unified Access to AI-Powered Decisioning + Data

What if your decisioning technology came with the same benefits as a smart home system?

Are you working with multiple products, vendors and UIs in order to make decisions? What if you could have a single user interface to manage all of your technology solutions and save you from a disjointed, incomplete view of the credit risk lifecycle?

Check out our latest eBook and discover how one unified solution for data and AI-powered decisioning can change the way you think about your risk strategy. And bring you to the forefront of tech innovation, just like today’s smart homes.

Learn how unified access offers:

  • Built-in controls to manage risk, security and identity
  • Preconfigured data integrations to get you up and running quickly and easily
  • Flexibility to expand as your needs evolve
  • Automation to improve efficiency and power better user experiences

Ready to get smarter?

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

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Webinar: Tackling Industry Priorities With a Different Approach to Data and AI

ON-DEMAND WEBINAR

Tackling Industry Priorities
With a Different Approach to Data and AI

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Struggling with data integration and AI adoption?

There are vast amounts of data available to the financial services industry, yet many organizations struggle with data integration and AI adoption that delivers value to their customers. Join us as Carol Hamilton, Provenir’s Chief Product Officer, sits down with Holly Hughes, CMO of BAI, for a discussion on data and AI trends influencing the industry.

Discover:

  • How many providers plan to deliver a high level of responsiveness and superior customer experiences with new sources of data and the right predictive models
  • The ways simplified access to alternative and non-traditional data can reshape your business
  • How organizations of all sizes can accelerate AI/ML adoption while removing the typical barriers to implementation

Speakers:

  • Holly Hughes

    CMO, BAI

  • Carol Hamilton

    Chief Product Officer, Provenir


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Machine Learning in Banks: The Solution to the Data Scientist Talent Gap

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Machine Learning in Banks:
The Solution to the Data Scientist Talent Gap

In 2023, the shortage of skilled data scientists is still a challenge for financial institutions. According to Indeed.com, the popular recruiting site, searching for “Data Scientist Financial Services” returns 1745 results. McKinsey & Company studied over a dozen banks in Europe that have replaced older statistical-modeling approaches with machine-learning techniques and saw significant improvements in their business metrics.

The Talent Gap Challenge:

With the increasing importance of data analytics in banking, the shortage of skilled data scientists is becoming increasingly serious. Tools for collecting, sifting, and sorting data become faster, cheaper, and better, but people with the skills to make use of the results are harder and harder to find.

Cloud-Based Machine Learning Services:

Cloud-based machine learning services can help fill the talent gap by opening up opportunities for junior or internal hires to augment risk analytics teams, provide immediate value, and grow into more advanced roles. Machine Learning can train and deploy a credit risk model in about 20 minutes, even by someone with little to no experience.

Benefits of Machine Learning:

Machine learning is not just a temporary solution to a talent problem. McKinsey & Company’s study of European banks revealed increases in sales of new products, savings in capital expenditures, increases in cash collections, and declines in churn after replacing older statistical-modeling approaches with machine-learning techniques.

Automated Risk Decisioning:

Combining machine learning with automated risk decisioning can prove invaluable to a financial institution’s bottom line. Automated risk decisioning helps make better credit decisions and improves overall portfolio performance.

Machine learning is the solution to the data scientist talent gap in the banking industry. Cloud-based machine learning services can provide immediate value and help junior or internal hires grow into more advanced roles. The benefits of machine learning are significant and can positively impact a financial institution’s bottom line.


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2022 Global Fintech Agenda

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2022 Global Fintech Agenda

What’s driving the agenda for fintechs and financial services in 2022?

Pulse and Provenir surveyed 400 decision-makers in fintechs and financial services organizations globally to find out what they believe will be the biggest challenges, opportunities and trends of 2022 and how they plan to address them with data, AI and decisioning.

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Guest blog: How mobile data secure solutions can help prevent fraud throughout the customer journey

GUEST BLOG

How mobile data secure solutions
can help prevent fraud throughout the customer journey

  • Sarah Small, Global Partner Marketing Manager, Sekura Mobile Intelligence

It’s clear that the events of the last two years have forced the business world to undertake a digital reality check and left organisations racing to address the challenges created by the rapid and unexpected adoption of online services. This double-edged sword of rapid consumer behaviour change has created the ideal environment for organisations to rethink their business model towards a digital-first strategy, whilst unfortunately also exposing them to digital fraud and online scams in unprecedented volumes.

Changes to consumer behaviour – a playground for fraud

Much has been written since the pandemic hit about the impact of Covid 19 and the changes that society has had to make in both personal and working lives. High streets are struggling, major retailers have closed or moved exclusively online, and for a period of time our working and in part social lives became an online activity only.

But as ever, where the genuine consumers are, the fraudster will follow. With the dramatic shift to online digital transaction has come the inevitable increase in online fraud – social engineering-enabled scams, account takeovers and theft.

In the first half of last year, criminals stole a total of £753.9 million through fraud, an increase of 30% compared to the first half of 2020. UK Finance

And so, controls are needed. To create the appropriate level of protection in online channels, these controls must be applied across the customer lifecycle, from the initial account set up and throughout a user’s transactional journey, including verification of a customer’s identity at account application and onboarding, confirmation of ID at account login and by verifying device ownership and authenticating the user during transactions, payments, money transfer and through all sensitive online activities.

The ultimate goal is to achieve a secure and frictionless online experience for the genuine customer while making it as difficult as possible for bad actors to succeed. Mobile operator data can offer the solution.

The power of mobile data

While the world has been going through rapid digital change, global mobile operators have been working to get mobile identity services prepared and optimised in readiness to support the explosion of new services and the use cases that this has created.

Worldwide, mobile operators are recognising and commercially deploying their digital identity services and resources to provide a unique set of tools and to enable secure customer authentication, user identity verification and account protection solutions. Their entry into this market has been carefully considered (for example to align with data privacy regulations) and now more operators are offering authentication services and other mobile identity tools and are gaining traction in the market.

Monthly active users of operators MSISDN-based authentication services alone are approaching 1 billion and are estimated to be growing at over 17% a year. Furthermore, several dozen innovative mobile operators are developing their mobile identity services, building on new investment and capabilities in big data, AI, machine learning and APIs to bring more advanced mobile identity products to market.

How Sekura is utilizing this data

The Sekura prediction: 2022 will be seen as the year that mobile identity intelligence data became a truly fundamental enabler for the ongoing growth of the global economy.

Now is the time that the global identity challenges and the increased availability of mobile solutions align to create a market in which mobile data can address real world problems using frictionless, seamless, real time mobile services to simplify customer journeys and prevent bad actors.

The mobile phone provides unique data in that it is the only available source of ‘dynamic’ data about what is happening right now – in ‘real time’. This capability allows mobile data to be used as a source of valuable signals in the fight against fraud, even in the fast-moving digital world that we live in.

Sekura have harnessed this ‘dynamic data’ to flag whether a device has been lost or stolen, signal that a SIM card has been recently swapped, that Call Forwarding has been set to divert calls to another device, or that a device has been recycled and is no longer used by the previous owner. The signals that it can reveal are available immediately so that if any of these actions occur, the data can be checked within an online banking or retail flow and used to help prevent fraudulent transactions or transfers before they happen.

Even better, by using mobile data to keep fraudsters out, it is also possible to easily identify the good guys – you and me – and ensure that, with simple mobile data checks behind the scenes, we are able to access our online services securely, quickly and easily and get on with our lives.

Ten Companies Using Alternative Data for the Greater Good

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Artificial Intelligence, Simplified.

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Artificial Intelligence, Simplified.

How to Level Up Your Risk Decisioning in Under 60 Days

Artificial intelligence in financial services is a $450 billion opportunity – but most AI projects never even get off the ground. Using AI in combination with the right data and the right decisioning tools means you can take a bite out of those billions of dollars of opportunity – and you can get there in less than two months.

Discover why you should implement AI in your risk decisioning, and how to do it.

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What is a decision engine and how does it help your business processes?

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Data on Demand: The Power of Real-Time Data for Risk Decisioning

EBOOK

Data on Demand: The Power of Real-Time Data for Risk Decisioning

How real-time data enhances risk decisioning and wins new customers.

In a digital first world everything is available on demand. Consumers expect instant gratification, not just for small things like movies or music, but for everything, including financial services. If you’re not approving a loan application in real-time, there’s a competitor who will.

In our latest ebook, we explore what the future of data for risk decisioning looks like. And, how real-time, on-demand data will:

  • Enhance decisioning accuracy
  • Power world-class consumer experiences
  • Support innovation across your business strategy

Download the ebook today to discover how curating a single source for historical and real-time data simplifies data access, enhances data science and machine learning strategies, and democratizes data use across your organization.

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

Read the Blog

RESOURCE LIBRARY

Blog: The Future of Collections for Wireless Carriers/Telcos

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The Future of Collections for Wireless Carriers/Telcos Best practices and recommendations for more efficient, personalized ...
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Mitigating Risk and ...

NEWS Mitigating Risk and Maximizing Customer Value Through Effective Case Management Case management in financial ...

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Embedded Finance: En...

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BLOG Tackling Tech Bloat: Slimming Down to Boost Efficiency, Security, and Innovation How Major Banks ...
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In-Person Event: Navigating the Future of Digital Transformation and Customer Experience September 27, 2024 | ...

Continue reading