Skip to main content

Tag: blog

7 Reasons to Use Salesforce for Credit/Loan Origination and Risk Decisioning

Written by Allison Karavos on . Posted in Blog. No Comments on 7 Reasons to Use Salesforce for Credit/Loan Origination and Risk Decisioning

BLOG

7 Reasons to Use Salesforce
for Credit/Loan Origination and Risk Decisioning

I had breakfast in an original Paramount Diner over the weekend. This authentic throwback to the 60s included fully restored jukeboxes on each table, letting diners choose their own private dining soundtrack.

So, what do my eating habits have to do with using Salesforce for loan origination and risk decisioning?

Well, this jukebox had a long list of song options that the diner needed to scroll through until they found something they liked. But the list was long, why? Because the diner wanted to include a range of tracks so that there was something for everyone.

It struck me as I watched the 10-year old at the table scroll through a range of classic tracks that he declared were ‘rubbish’ until he reached the pages of recent pop tracks that I declared were rubbish, that this experience was very much like shopping for financial services.

You’re often forced to scroll through the irrelevant offers until you find the one you’re ready to press play on. But, it doesn’t end there. You then you have to fill in the application and then if you’re lucky only wait a few seconds for your application to be approved.

But, financial services providers have the power to improve that experience when they combine the data within their CRM systems with their loan decisioning technology.

Using Salesforce to improve efficiency, make smarter decisions, and personalize user experience

Financial institutions want to serve customers well, so they strive for efficiency improvements. Process automation plays a big part in this. Manual, disconnected credit and lending processes are being weeded out and replaced with digital, automated solutions.

This is progress. But for complete efficiency, risk analytics and decision-making should be tied into other business systems. Salesforce is an excellent case in point. Its customer relationship management (CRM) solution is widely used by financial institutions to manage customer interactions.

Many banks, card issuers, and fintech companies manually extract and duplicate data from Salesforce to complete credit checks, risk scoring and due diligence processes using legacy systems.

This is slow and inefficient. And it can change. When credit and lending decisioning processes and Salesforce are connected, there can be seamless data exchange. Through connected ecosystems, a single data set can drive real-time risk analytics and decisioning.

The right technology, pre-integrated with Salesforce can help automate loan and credit origination. It can help your business:

  1. Increase use of Salesforce CRM data throughout the organization – listening for, reading and writing data into and out of Salesforce eliminates the manual moving of data from Salesforce to legacy systems. Technology can also enrich native Salesforce data with information maintained in other systems, which can be created and stored as custom fields within Salesforce.
  2. Automate originations and underwriting processes – by leveraging decisioning technology that can easily integrate to external and internal data sources and bureaus, organizations can make real time decisions based on the aggregated data, operationalize any risk models in minutes and use Salesforce to automate originations and underwriting. Also read: What is credit underwriting?
  3. Create a more transparent lending process – with a 360-degree view of your customers at a glance. You can unify your entire lending business through a single platform, giving borrowers, lenders, brokers, underwriters, and every member of your team a transparent view of the lending process.
  4. Provide end-to-end compliance and better reporting – automatically aggregated data from internal systems, KYCnet, and other external systems can be made available to a compliance interface built within Salesforce. Capabilities such as business rules that ensure only the right data is aggregated for each client simplify compliance end-to-end.
  5. Tailor product offers to the right customers – customers expect companies to know what they need when they need it. Combining a CRM such as Salesforce with a credit decisioning system allows businesses to collate the data they need by connected siloed data. So, you can take a consumer—not product—centric approach.
  6. Preapprove offers for existing customers – in addition to providing a customer focused offer, integrating Salesforce with a loan decisioning solution allows a business to preapprove customers for specific offers. This ensures that you only promote offers that are suitable for the customer and improves the application process.
  7. Target customers based on life events, financial triggers, or specific behaviors – data analytics can help your business predict the need for financial services based on event or behavior triggers such as marriage, saving habits, or even reduced the use of their existing products. With an integrated CRM and decisioning solution you’ll be able to not just predict the need for services but also choose the right product and preapprove the customer before reaching out through a tailored marketing campaign.

The benefits of using Salesforce for Credit/Loan origination and risk decisioning

The number of benefits that combining a CRM such as Salesforce are many and they don’t just offer small opportunities to advance your lending business. In fact, this perfect combination of technologies will empower your business to create a smarter, faster, and more customer centric user experience.

It will also bring many business gains such as the automation of manual lending processes, better KYC monitoring, and smarter decisioning to reduce risk. One huge opportunity these technologies, when used together, offer is the chance to grow and evolve your business. With analytics and customer knowledge deeply ingrained into your origination technology you’ll have a much clearer understanding of consumer needs, empowering your business to better target customers and develop products that best meet the needs of an evolving market.

Using Provenir within your Salesforce environment

With the Provenir pre-built integration adapter for Salesforce, financial institutions can automate complex analytics and decisioning processes for credit and loan applications from within their Salesforce environment.

Watch the Demo

LATEST BLOGS

Continue reading

Simplifying the Merchant Onboarding Process with Automation

Written by Allison Karavos on . Posted in Blog. No Comments on Simplifying the Merchant Onboarding Process with Automation

BLOG

Simplifying the Merchant Onboarding Process
with Automation

The Challenges of Manual Merchant Onboarding

Merchant onboarding is a critical process for acquiring businesses that involves acquiring, analyzing, and integrating large volumes of data. However, the manual and time-consuming nature of this process often results in delays and errors. For instance, if data or knowledge of the merchant is lacking, then identity can’t be validated. Compliance with Know Your Customer (KYC) and other governmental regulations has to be determined, as does creditworthiness. This takes days and can still involve a high degree of manual handling. To streamline this process and make it more efficient, automation is the way forward.

Compliance with KYC and Other Regulations

KYC stands for “Know Your Customer” and is a process that financial institutions and other regulated companies use to verify the identity of their clients. This process involves collecting and verifying various types of information about the client, such as their name, address, date of birth, and other identifying information. The objective of KYC is to prevent financial crimes such as money laundering, terrorist financing, and other fraudulent activities.

During the merchant onboarding process, compliance with KYC and other governmental regulations is required. Failure to comply with these regulations can result in fines and other legal consequences. By automating the merchant onboarding process, companies can streamline the KYC process, making it quicker and more efficient, while also ensuring compliance with regulatory requirements.

The Benefits of Automation

Simplified Data Integration

To simplify data integration, acquirers need to access and efficiently handle and analyze all data sources such as bank account information, commercial data, address verification, KYC checks, credit score, and more. To achieve this, a merchant onboarding solution with integration capabilities that can rapidly aggregate data from various sources is required. Non-standard data, such as that from social media, can supplement sources – if the acquirer has the means to get at it and pull out what’s relevant. To achieve this, the best solutions offer pre-built adaptors built on industry standards.

Operationalized Risk Models

Operationalized risk models play a critical role in the merchant onboarding process. They integrate with the other elements that make up the end-to-end merchant onboarding process, ensuring that risk decision-making is not a bottleneck in the process. Technology and model-agnostic solutions can integrate with SAS, Excel, and anything else besides. Business-defined rules lay down the terms and conditions for each merchant and identify exceptions that require further investigation. A visual interface lets business users quickly establish the relationship between the risk model and the automated onboarding process.

Effective management of data is essential to a rapid, efficient merchant onboarding process. Technology for automated risk analytics and decision-making integrated into the onboarding process taps into multiple data sources and systems for a streamlined end-to-end process. To learn more about simplified data integration and operationalized risk models for merchant onboarding, check out our guide on our website.

Learn how you can choose the best merchant onboarding automation solution.

Get the eBook

LATEST BLOGS

Continue reading

Machine learning – all a bit ‘Skynet’?

Written by Allison Karavos on . Posted in Blog. No Comments on Machine learning – all a bit ‘Skynet’?

BLOG

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.

Deploy Machine Learning in Your Financial Institution Rapidly

Get the Whitepaper

LATEST BLOGS

Continue reading

Blogs by our Clients: Breaking down the Barriers to Financial Inclusion

Written by Allison Karavos on . Posted in Blog. No Comments on Blogs by our Clients: Breaking down the Barriers to Financial Inclusion

BLOG

Blogs by our Clients:
Breaking down the Barriers to Financial Inclusion

New research, supported by Oakam, highlights need for shake up in the way the financially excluded are assessed for credit worthiness

In Oakam’s experience those using ‘high cost’ credit is a diverse group which includes those on low incomes and those with little credit history such as recent migrants.  These consumers are usually borrowing with a very clear understanding of the costs associated with their borrowing choices.  In fact, as recent research by Which magazine revealed, a ‘high cost’ loan is very often a cheaper option for consumers than an overdraft facility on their current account (which begs the question…high cost in comparison to what?).  However, it appears that even responsible users of ‘high cost’ credit – those that make the required repayments and manage their other debt obligations at the same time—suffer from constrained future access to credit.  This is clearly unjust.

There is no doubt…the way credit is accessed in the UK is broken for millions of people.

It was designed for big banks with credit bureaus developing credit scores for mortgages, credit cards, and personal loans for Prime borrowers.

However, for those on the low end of the economic spectrum, credit scoring tools today may in fact be trapping consumers in high cost debt.

Taking a small loan, even with a high APR, can be the right decision for a consumer if it lowers the chance of default on other obligations.

However, Oakam has evidence that even when taking a small loan improves how that customer services their debt obligations, their credit score can suffer long term damage.

The impact of this damage means the customer finds they have fewer options for accessing credit, forcing them to rely even more on high cost credit and the cycle continues.

At Oakam, we recently supported the work done by academics from The London School of Economics and Political Science, Sussex University, and New York University looking at the long term impact of the use of ‘high cost’ credit.  The full study can be downloaded from the Social Science Research Network.

In their paper, the authors found evidence that “using high-cost credit may leave a stigma on a borrower’s credit history: if borrowers that take up high-cost loans are tagged as high-risk by lenders, they may as a result face higher borrowing costs in the future.”    If users of high cost credit actually showed deteriorating repayment behaviour this increase in future borrowing costs might make sense. However, the authors also found “that borrowers that take up a high-cost loan suffer an immediate decline in their credit rating. This decline cannot be explained by the repayment behavior of the borrower, because, if anything, taking up high-cost loan improves repayment behavior.”

At Oakam, we view our success as synonymous with our customers’ success.  As one company we alone can’t change the plight of the financial excluded.  What we can do is make sure that our product and services are designed to create the best customer outcomes, which we believe are access to credit today to address a pressing need and the option to access to more credit at a lower price in the future.  For example, we lower customer’s interest rates over time, offer small weekly repayments, and always allow a loan to amortize as opposed to being rolled over into an even larger debt.

But there is only so much we can do when the broader system is stacked against ‘high cost’   borrowers.

Some companies, like Aire, are pioneering new ways of assessing borrowers credit worthiness.  And, other companies such as Pockit and TransferGo are making financial services more accessible to lower income consumers.  But more needs to be done.  That is why we urgently calling for policy makers and like-minded Fintech companies and lenders to address the systemic problems relating to access to credit for lower income or financially excluded customers.

This blog post discusses the impact of the current system for assessing credit worthiness on the well- being of ‘high cost’ borrowers.  A future blog post will discuss how the underlying costs of providing credit to the financially excluded is a key driver of the higher costs these customers face.

Oakam is backed by Cabot Square Capital LLP, a leading financial services private equity firm.

LATEST BLOGS

The Importance of Customer Experience in Driving Loyalty Across the Subscriber Lifecycle

Blog: The Importance...

Discover how telcos can enhance customer experience across the entire subscriber lifecycle with automated onboarding,
Read More
telco fraud

Three Steps to Fight...

BLOG Minimize Risk, Maximize Activations:Three Steps to Fighting Telco Fraud Do you have billions of
Read More
auto fraud blog

Blog: The Growing Th...

The Growing Threat of Fraud in Auto Lending andHow to Combat It How intelligent decisioning
Read More
Blog: Election Economics

Blog: Election Econo...

Election Economics: How to Navigate Risk Decisioning in an Uncertain Political Landscape How Political Outcomes
Read More

Continue reading

The ‘under banked’ foreigners are an untapped customer base for lenders in the US

Written by Allison Karavos on . Posted in Blog. No Comments on The ‘under banked’ foreigners are an untapped customer base for lenders in the US

BLOG

The ‘Under Banked’ Foreigners
are an Untapped Customer Base for Lenders in the US

In 2015, the U.S. Department of State issued 477,780 temporary work visas to foreign nationals

These people represent 0.3 percent of the U.S. labor force and are a largely untapped customer base for U.S. businesses. Why? They do not have traditional credit history established in the U.S. and so businesses are not comfortable taking on the risk of their business. When I moved from Australia four years ago on a work visa, I could not even get a cell phone contract.

I approached multiple phone providers and they all told me the same thing. That I did not have enough of a credit history to merit a long term phone contract with their company. This is because most companies – not just phone providers – use traditional databases and resources like the FICO score to determine the creditworthiness of an individual.

FICO scores are a purely U.S. based metric and so, while I own property in Australia and hold a job in the U.S., I was requisitioned to a month to month plan on a lesser phone carrier. This month to month plan has allowed me to build my “financial reputation” and one day I hope to graduate to a regular cell phone plan within the U.S.

My new credit reputation will then also give banks the confidence to one day give me a business, home or auto loan. But it will have taken them over two and a half years to do so. In the meantime, my phone carrier and other traditional lenders have lost out on millions of dollars on potential long term contracts with me and thousands of other “under banked” foreign nationals.

As financial tides turn around the globe and the makeup of the U.S. workforce continues to diversify, many alternative and P2P lenders are realizing that relying on the limited data of a FICO score to provide a credible risk assessment of a potential customer is no longer viable. Casting a wider net to incorporate data from international bureaus and an individual’s social media profile can provide a better risk profile for customers who come from overseas, so that both customers and businesses can benefit in a more positive way.

LATEST BLOGS

Continue reading