Banking-as-a-Utility: The Consumer Finance Revolution

Cryptographically Enforced — AI Powered

Within our team, we discuss the concept of Banking-as-a-Utility quite a bit and we wanted to share our longer-term vision. This piece will deep-dive into Jibrel’s approach to revolutionizing consumer finance, specifically, lending — but first, a little background reading…

Consumer banking, retail banking or individual banking generally refers to the services banks provide to consumers — as opposed to corporate or institutional banking, which renders services to corporations, institutional investors and other banks.

Consumer lending is the category of financing centered on individual and household consumers. It includes home and auto loans, as well as personal loans extended to people who use the funds for individual or family purposes.

Part 1: Loan Underwriting

The first piece we will be looking at is loan underwriting. When a consumer applies for a loan — e.g. a mortgage, the bank is primarily trying to assess the likelihood or probability that the consumer will fulfill his obligation and not default on the loan.

Traditionally, lenders have used a tried and test formula, based on the applicants credit score or ‘worthiness’, available collateral, and his capacity to repay the loan.

More recently, lenders have started augmenting this traditional data with additional informative features — including untraditional metrics such as email age, email domain strength, and social media activity — in extreme cases, models may even take into account what browser the consumer is using to complete his online application.

This wave of data augmentation in the field of consumer lending has been observed with SME lenders in developed markets and consumer lenders in emerging markets, where credit scores may not be readily available.

Once an overall assessment of an application is complete, including data verification, credit assessment, etc. the application is approved or rejected.

In leading financial markets, we have seen an increased level of automation of this step. Whereby a portion of the application funnel is automated (i.e. approved or rejected algorithmically) and a significant percentage is then routed to manual inspection.

So even today, an encouraging portion of certain lending funnels, are automated.

Part 2: Securitization

Securitization is the transformation of an illiquid asset into a security (e.g. a group of consumer loans can be transformed into a publicly-issued debt security).

Once we have a portfolio of debt instruments, carrying on with our mortgage example, the bank then places these assets into a trust, pool or special purpose vehicle (especially popular with real-estate based assets).

This can be considered a separate off-balance sheet entity that will house the assets and the associated cashflows.

The bank moves to securitize the assets for several reasons:

1. Securities are tradable — i.e. they are highly liquid, more so than the underlying loan or receivables.
2. Securitization of assets can lower risk, add liquidity, and improve economic efficiency.
3. Regulatory or capital constraints may imply that it is in the interest of the bank to move certain assets off their balance sheet.

With a pool of mortgages now available, the issuer of the soon to be security divvies up the pool into large tranches or parts. This allows the issuer to create different products with different risk profiles from the same pool.

These securities can then be sold to institutional investors. For example, high risk / high return seekers such as hedge funds will buy the lower credit securities, while the pension funds will buy-up the low-risk high credit backed securities.

A Convoluted and Costly Process

Examining the securitization further shows how many steps are needed to generate trust, through guarantees and contractual agreements.

Green donates Cash-flow, Red denotes Initial Capital, Blue denotes Contractual Obligation

The entire process is to facilitate what is largely two cash-flow — The Lendee’s periodic payments into the SPV, and the Investors returns from the security.

In addition, deep-diving into the activities undertaken by the financial institution in facilitating this transaction shows how little technologically enforced the process is.

Extract: Jibrel — Leveraging DLT for Debt Issuance, Securitization, Trading and Settlement

Part 3: Credit Enhancement, Bond Structuring and Ratings

Choosing the assets that go into the SPV is just the start - there are a few key steps that must be undertaken:

1. Bond structuring: properly understanding the size of the issue and how the offering will be structured
2. Credit enhancement: improving the overall credit or rating by using a third party guarantor or providing additional collateral
3. Ratings: each security must go through a cumbersome verification, validation and assessment process

Securitization is a long and cumbersome process to facilitate what are fundamentally simple transactions

These elements of the process seem most likely to be demoted to auxiliary functions in the future landscape that will be powered by Distributed Ledger Technology (DLT). For this reason, we won’t deep-dive — but it is important to note that as part of the rating analysis the agency investigates the underlying assets pre-securitization — i.e. they conduct an assessment of the underlying loans. In addition, they examine the overall legal structure, the credit worthiness of the participants, protocols and procedures, amongst other things.

Part 4: Settlement and Clearing

In the absence of ‘trust-less transactions’, we’ve had to rely on intermediaries to facilitate the settlement and clearing of transactions. These intermediaries have gotten more and more efficient and processing, clearing and settling transactions, however, they cannot compete with the cost efficiencies of blockchain technology and smart contracts.

For this reason, it is likely that we will see very quick adoption amongst key players such as the DTCC (The Depository Trust & Clearing Corporation). The risk is “keep up or be replaced”.

Jibrel Build-out — Key Considerations

Before we begin considering the automation of the processes outlined above, we’ll require:

1. Crypto-fiat tokens to interface with the real-world — Jcash
2. Institutional grade storage and transaction solutions — Jwallet

We won’t go into these in too much detail, if you want to learn more, please read our Roadmap. The key message here is that these are critical components to our success and are finalized / will be released in the coming weeks.

the Jwallet is an institutional grade ERC-20 token storage / transaction solution

The next component is the decentralized securitization, settlement and clearing solution.

Additional CryptoDepository Receipts

Jibrel’s smart tokens, CryDRs, are fully programmable — and while the first roll-out, Jcash, will be six fiat currencies, the future roadmap has a strong focus on debt instruments and their eventual securitized form.

Beyond Jcash, we will require three additional CryDR types to facilitate the automation of debt underwriting, securitization, settlement and clearing:

1. Loan CryDRs: a loan cryptodepository receipt is an ERC-20 token that receives a deposit, pays out a lump-sum and expects period payments based on a pre-calculation — this pre-calculation can be fed directly from existing loan underwriting systems (Plug and play — including legacy solutions) — it also contains programmed logic around delayed payments, defaults and provision generation
2. Trust CryDRs: a trust cryptodepository receipt is an ERC-20 token that contains multiple Loan CryDRs — trust CryDRs can be built manually by aggregating segments of Loan CryDRs or automatically based on a desired output (risk profile, rating, etc.)
3. Asset Backed CryDRs: an asset backed security cryptodepository receipt is the securitized Trust CryDR. It can be bought and sold and the holder of the token receives the periodic cash flow payments of the underlying loans — asset backed security CryDRs embed smart regulation, ensuring they are always traded in a compliant manner

Using these CryDRs, the Jibrel can facilitate the seamless securitization of debt instruments and the settlement and clearing of those securities.

Regulators, rating agencies and watchdogs play an observer role as the underlying data is 100% verifiable

Banks can underwrite debt, securitize and trade it, whereby customer repayments are used to directly pay-out investors holding the asset backed security.

Banking as a Utility

For those who are following the convergence of crypto-technologies and artificial intelligence probably understand that its not far-fetched to envision the entire process being fully AI powered.

Once that is the case, we end up with a system where those with capital can give it to AI to allocate, while those requiring capital can access it if they are credit worthy.

Access to capital is already available to credit worthy applicants, almost like a basic right, but driven by capitalistic gears. Its not hard to imagine an ecosystem in which we have fairer and more transparent credit scoring systems and where capital is allocated effectively, efficiently, transparently and fairly — free from human subjectivity and falleability.

This is what we mean when we say Banking as a Utility — in the decentralized world, if you are credit worthy, you should have access to capital — if you have capital, you should have low risk stable return investments to safely store your money and make gradual stable returns.

This ‘Banking as a Utility’ revolution is one of the things we’re constantly working towards at Jibrel, but we still have quite a long-way to go before realizing this vision. While we’ve built out the core components as a standalone solution, it is going to take some heavily lifting before this is a production ready solution for financial institutions.

Compatibility with legacy systems will also be a gradual and grueling process, where certain compatibilities are added in piece-meal fashion.

We didn’t cover a lot of different elements, but hopefully we can get to them in future posts!

Some Key Risks / Pitfalls we didn’t talk about:

1. Block Times and their implications on trading
2. Front-running (Public Blockchains) and how to prevent it
3. Bad actors and how to prevent / identify unlawful collusion